Community Quality-of-Life Indicators: Best Cases II

COMMUNITY QUALITY-OF-LIFE INDICATORS Social Indicators Research Series Volume 28 General Editor: ALEX C. MICHALOS Uni...

Author: M. Joseph Sirgy | D. Rahtz | David Swain

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COMMUNITY QUALITY-OF-LIFE INDICATORS

Social Indicators Research Series Volume 28 General Editor: ALEX C. MICHALOS University of Northern British Columbia, Prince George, Canada

Editors: ED DIENER University of Illinois, Champaign, U.S.A. WOLFGANG GLATZER J.W. Goethe University, Frankfurt am Main, Germany TORBJORN MOUM University of Oslo, Norway MIRJAM A.G. SPRANGERS University of Amsterdam, The Netherlands JOACHIM VOGEL Central Bureau of Statistics, Stockholm, Sweden RUUT VEENHOVEN Erasmus University, Rotterdam, The Netherlands This new series aims to provide a public forum for single treatises and collections of papers on social indicators research that are too long to be published in our journal Social Indicators Research. Like the journal, the book series deals with statistical assessments of the quality of life from a broad perspective. It welcomes the research on a wide variety of substantive areas, including health, crime, housing, education, family life, leisure activities, transportation, mobility, economics, work, religion and environmental issues. These areas of research will focus on the impact of key issues such as health on the overall quality of life and vice versa. An international review board, consisting of Ruut Veenhoven, Joachim Vogel, Ed Diener, Torbjorn Moum, Mirjam A.G. Sprangers and Wolfgang Glatzer, will ensure the high quality of the series as a whole.

The titles published in this series are listed at the end of this volume.

COMMUNITY QUALITY-OF-LIFE INDICATORS Best Cases II Edited by

M. JOSEPH SIRGY Virginia Polytechnic Institute & State University, Blacksburg, VA, U.S.A.

DON RAHTZ College of William & Mary, Williamsburg, VA, U.S.A. and

DAVID SWAIN Jacksonville Community Council, Inc., Jacksonville, FL, U.S.A.

A C.I.P. Catalogue record for this book is available from the Library of Congress.

ISBN-10 ISBN-13 ISBN-10 ISBN-10

1-4020-4624-3 (HB) 978-1-4020-4624-7 (HB) 1-4020-4625-1 (e-book) 978-1-4020-4625-4 (e-book)

Published by Springer, P.O. Box 17, 3300 AA Dordrecht, The Netherlands. www.springer.com

Printed on acid-free paper

All Rights Reserved © 2006 Springer No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed in the Netherlands.

Table of Contents

Preface

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The Jacksonville, Florida, Experience J. Benjamin Warner

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Indicators as a Structural Framework for Social Change Charlotte Kahn Indicators in Action: The Use of Sustainability Indicators in the City of Santa Monica Genevieve Bertone, Shannon C. Parry, Dean Kubani, and Jennifer Wolch

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A Measure and Method to Assess Subjective Community Quality of Life M. Joseph Sirgy and Don Rahtz

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Perception and Evaluation of the Quality of Life in Florence, Italy Filomena Maggino

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City of Winnipeg Quality-of-Life Indicators Peter Hardi and László Pintér

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Sustainable Seattle: The Case of the Prototype Sustainability Indicators Project Meg Holden

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Using Community Indicators to Improve the Quality of Life for Children: The Sacramento County Children’s Report Card Nancy Findeisen

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Living in a Post-Apartheid City: A Baseline Survey of Quality of Life in Buffalo City Robin Richards and Ellen Kamman

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Making Community Indicators Accessible Through the Census Information Center: Howard University, Portals to the Community, and the New American University Rodney D. Green, Maybelle T. Bennett, Haydar Kurban, Lorenzo Morris, and Charles C. Verharen

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TABLE OF CONTENTS

Quality Indicators for Progress: A Guide to Community Quality-of-Life Assessments Marian Chambers and David Swain

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Contributors

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Preface

This book is the second in a series covering best practices in community quality-of-life (QOL) indicators. The first was published in 2004. The editors are M. Joseph Sirgy, Don Rahtz and Dong-Jin Lee. Volume 1 is a compilation of cases of best work in community indicators research. The cases describe communities that have launched their own community indicators programs. Elements that are included in the descriptions are the history of the community indicators work within the target region, the planning of community indicators, the actual indicators that were selected, the data collection process, the reporting of the results and the use of the indicators to guide community development decisions and public policy. The chapters in Volume 1 are: Chapter 1: Vital Signs: Quality-of-Life Indicators for Virginia’s Technology Corridor by Terri Lynn Cornwell Chapter 2: The Sustainable Community Model Approach to the Development and Use of Multi-Dimensional Quality-of-Life Indicators by William T. Grunkemeyer and Myra L. Moss Chapter 3: Taking Indicators to the Next Level: Truckee Meadows Tomorrow Launches Quality-of-Life Compacts by Karen Barsell and Elisa Maser Chapter 4: A Collaborative Approach to Developing and Using Quality-of-Life Indicators in New Zealand’s Largest Cities by Kath Jamieson Chapter 5: 2002 Hennepin County Community Indicators Report: Aligning Community Indicators with Government Mission, Vision and Overarching Goals by Misty Lee Heggeness, Paul Buschmann, and Thomas Walkington Chapter 6: The State of the City Amsterdam Monitor: Measuring Quality of Life in Amsterdam by Peggy Schyns and Jeroen Boelhower Chapter 7: A Three-Decade Comparison of Residents’ Opinions on and Beliefs about etc in Genesee County, Michigan by Robin Widgery Chapter 8: Creating an Index to Evaluate a Region’s Competitiveness by Beth Jarosz and Michael Williams Chapter 9: Toward a Social Development Index for Hong Kong: The Process of Community Engagement by Richard J. Estes Chapter 10: Measuring Sustainability and Quality-of-Life in the City of Zurich by Marco Keiner, Barbara Schultz, and Willy A. Schmid Volume 2 continues to build on the goal of the book series. Eleven chapters are included in Volume 2. Here is a brief description of these chapters. Chapter 1: The Jacksonville, Florida. Experience by Ben Warner (Associate Director of the Jacksonville Community Council Inc. (JCCI), Jacksonville, Florida, USA) describes a community QOL indicators project focusing on Jacksonville, Florida. The sponsoring organization is the JCCI. He explains the origin of the QOL project, the goal of producing a QOL report, the exercise involving the definition of QOL, how JCCI involved the community in the definition and

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PREFACE

specification of QOL indicators, the actual process involved in selecting QOL indicators and the criteria for inclusion and exclusion, finding data related to the selected indicators, presenting the indicators, and using the indicators to develop community programs to enhance community QOL. Chapter 2: The chapter titled Indicators as a Structural Framework for Social Change by Charlotte Kahn (Executive Director of the Boston Foundation, Boston, Massachusetts, USA) depicts a community QOL indicators project focusing on City of Boston, Massachusetts, USA. The sponsoring organization of the indicators project is the Boston Foundation. This chapter starts out with an introduction of the Boston Foundation, its history and the inception of the Boston Indicators Project. Kahn proceeds to describe the conceptual framework guiding the indicators project. She describes ten sectors, and within each sector information is provided in relation to specific population segments (e.g., children and youth). The author then describes the project structure involving two tracks: civic agenda and indicators data and reports. In terms of indicators, she explains the goals behind each indicator, the exact measure and scales, the data source and when the data were collected. She concludes by revisiting some of the core principles of the project and lessons learned. Chapter 3: Indicators in Action: The Use of Sustainability Indicators in the City of Santa Monica by Genevieve Bertone (Executive Director for Sustainable Works, California, USA), Shannon Clements Parry (Founder of Sustainable Places, California, USA), Dean Kubani (Senior Environmental Analyst with the City of Santa Monica’s Sustainable City Program, California, USA), and Jennifer Wolch (College Dean of Graduate Programs and Professor of Geography at the University of Southern California, California, USA) describes a community QOL indicators project focusing on the City of Santa Monica, California, USA, and referred to as the “Santa Monica Sustainable City Program.” The sponsoring organization is Santa Monica City Council. The authors describe the circumstances leading to the inception of the Santa Monica Sustainable City Program, the creation of the Sustainable City Plan, the elements of the plan, the indicators, policies related to the indicators, and performance assessment based on the indicators. Finally, they describe how these indicators are used to mobilize community development. Chapter 4: A Measure and Method to Assess Subjective Community Quality-ofLife by M. Joseph Sirgy (Professor of Marketing at Virginia Polytechnic Institute and State University) and Don Rahtz (Professor of Marketing at the College of William and Mary) introduces the readers to a measure and method to capture subjective indicators of community QOL. The measure and method is based on a conceptual model linking community residents’ ratings of their overall life satisfaction and satisfaction from other life domains. Ratings of overall community satisfaction, in turn, are determined by satisfaction with a variety of services found in the community (business services, government services and nonprofit services) plus evaluations of community conditions (e.g., environment, crime). Chapter 5: Perception and Evaluation of the Quality of Life in Florence, Italy by Filomena Maggino (Researcher and Professor of Social Statistics at the Universita degli Studi di Firenze, University of Florence, Florence, Italy) describes a community QOL indicators project focusing on Florence, Italy. The City of Florence (Italy)

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together with the Department of Statistics of the University of Florence sponsored this project. She starts out by explaining the conceptual model underlying the indicators project, and describes the survey research methods used in carrying out the study: sampling, data collection methods, selection and development of the QOL indicators, the development of composite indicators involving the subjective image of the city, the perception of the city as a tourist destination, the perception of the cultural dimensions of the city, and perception of personal safety. Then she reports trend analyses, and breaks down the data in terms of the various districts and neighborhoods within the city. She identifies several groups of residents: the satisfied group, the critical group, the satisfied-with-little group and the integrated group, and explores the determinants of satisfaction for each group. Chapter 6: City of Winnipeg Quality-of-Life Indicators by Peter Hardi (Senior Fellow at the International Institute for Sustainable Development, Canada) and Laszlo Pinter (Director of the International Institute for Sustainable Development, Canada) is the outcome of a collaboration involving the Strategic Planning Division of the City of Winnipeg and the Measurement and Indicators program of the International Institute for Sustainable Development (IISD). The chapter introduces the reader to the concept of QOL and a little history of the indicators project, and then describes the process involving the development of QOL indicators. The authors have built a foundation for the reader by defining basic concepts such as what is a QOL framework, what are QOL indicators, how a QOL index can be formed from individual indicators, and how indicators are reported. They proceed by describing framework development, stakeholder participation, and indicator development. Following this they report on the resulting QOL framework and provide a sample list of QOL indicators for the City of Winnipeg. They also describe data availability assessment and finally the plan used to implement the framework. Chapter 7: Sustainable Seattle: The Case of the Prototype Sustainability Indicators Project by Meg Holden (Assistant Professor of Urban Studies and Geography at Simon Fraser University, Canada) focuses the indicators project on the City of Seattle, Washington, USA. The sponsoring organization of this indicators project is Sustainable Seattle. The chapter is structured to reflect the organization’s life cycle. The author starts out by describing the inception phase (1990–1991), then proceeds to describe the early phase (1991), the heyday (1991–1998), the changeover and downturn (1996–1999), the near-death experience (1998–2001), and finally the torchbearers and reorganization (2001–2004). Managers of new indicators projects can benefit significantly from the many “lessons” inherent in the Sustainable Seattle story. Chapter 8: Using Community Indicators to Improve the Quality of Life for Children: The Sacramento County (CA) Children’s Report Card by Nancy Findeisen (President and CEO of the Community Services Planning Council Inc., Sacramento, California, USA) starts out by describing how the Community Services Planning Council was formed. The sponsoring organization is the Community Services Planning Council Inc., Sacramento, California, USA. The focus of this indicators project is children residing within Sacramento County. The author turns her attention to the 2000 Children’s Report Card, the primary goal of the Community Services Planning Council. She describes the process involving

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collecting the needed information for inclusion in the report card. Then she devotes considerable energy in describing the content of the report card. The format and presentation of the report card are also described. She discusses the public response to the report card, the resulting summit and the events following the summit, and concludes by highlighting future challenges in this area. Chapter 9: Living in a Post-Apartheid City: A Baseline Survey of Quality of Life in Buffalo City by Robin Richards (Senior Researcher at the Community Agency for Social Enquiry, Johannesburg, South Africa) and Ellen Kamman (Senior Data Manager/Researcher at Development Research Africa CC in Durban, South Africa) focuses this indicators project on Buffalo City, South Africa. The authors describe a major survey (the Buffalo City 2001 QOL Survey) designed to help city planners monitor the QOL of the city residents and conditions that can improve community QOL. They explain the survey in some detail (sampling, data collection, and survey instrument). The results are reports broken down by four geographic regions, and cover demographics, material living conditions (income, employment status, employment blockages, work seeking strategies, dependency ratio, transportation, type of tenure and housing access to basic household services, access to community services), perceptions of QOL (domain satisfactions, perceptions of safety, perceptions of community improvements, and global satisfaction with life). Chapter 10: Making Community Indicators Accessible Through the Census Information Center by Rodney Green (Executive Director of the Howard University Center for Urban Progress, Washington, DC, USA), Maybelle Taylor Bennett (Director of the Howard University Community Association, Washington, DC, USA), Haydar Kurban (Assistant Professor of Economics at Howard University, Washington, DC, USA), Lorenzo Morris (Professor and Chair of the Political Science Department at Howard University, Washington, DC, USA) and Charles Verharen (Graduate Professor in the Philosophy Department at Howard University, Washington, DC, USA) aims to show how universities especially Historically Black Colleges and Universities (HBCUs) are increasingly taking on partnership roles through service learning and community-based research. University students, faculty, and administrators are all involved in that endeavor. It describes a model that other universities can use to set up their own community university partnership programs. Chapter 11: Quality Indicators for Progress: A Guide to Community Quality-ofLife Assessments was originally written by Marian Chambers (who was a civic leader in Jacksonville, Florida, USA from 1975 until her death in 1996). The chapter has a foreword by David Swain (currently a consultant, retired from the Jacksonville Community Council Inc., Jacksonville, Florida, USA). It provides community planners with practical guidelines on how to plan and implement community indicator projects. It introduces the reader to QOL projects (motivation, definitions, components, etc.), and proceeds by taking the reader through a step-by-step approach to planning and implementing a QOL indicators project. Chambers specifically describes how early decisions (e.g., adopting a QOL model) are made. The chapter explains the processes of citizen participation, selecting indicators, compiling indicators, designing and using a telephone survey, establishing priorities, setting targets, preparing the publication, distribution and public education, encouraging citizen action, and the annual review.

The Jacksonville, Florida, Experience J. BENJAMIN WARNER Associate Director, Jacksonville Community Council Inc.

In 1985, the Jacksonville Community Council Inc. (JCCI) and the Jacksonville Chamber of Commerce created a unique tool to measure and promote improvement in the quality of life (QOL) in Jacksonville, Florida. The Quality of Life Progress Report, published annually for the last 20 years, has required a series of community decisions about the process of determining, quantifying, and evaluating community well-being. As such, it has provided significant opportunities for community learning about measuring and improving the QOL in a community.

Background and History About Jacksonville Jacksonville, Florida, is a consolidated city-county government with an estimated population of 850,000 in 2005, anchoring a five-county Northeast Florida region of 1.2 million.1 Jacksonville covers 840 square miles, reaching to the Atlantic Ocean on the east and bisected by the St. Johns River, which supports commercial seaport activities, two U.S. Navy bases, and recreational activities. Jacksonville’s economy is primarily service-based, with financial and health care institutions predominating, with a strong construction industry.2 Jacksonville’s population is younger than most Florida cities, with 26% aged less than 18 years and 10.5% above 65 years. Of the population 65% is White, 28% Black/African American, and 4% identify themselves as Hispanic. The population has been growing by an estimated 1.7% annually for the last 20 years.3

About JCCI JCCI was created in 1975 to serve as an independent citizens’ voice in examining and finding solutions to pressing community issues. The nonprofit, nonpartisan citizens group adapted a consensus-based study model to create recommendations for change, and soon added an implementation process using citizen advocates to ensure that the recommendations received the proper audience and, with optimistic advocacy, action. JCCI’s mission is to engage diverse citizens in open dialogue, research, consensus building and leadership development to improve the QOL and build a better community in Northeast Florida and beyond. For more information, visit the JCCI website at www.jcci.org.

1 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 1–22. © 2006 Springer. Printed in The Netherlands.

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Origins of the Quality-of-Life Project JCCI, from its inception, was charged with identifying community needs and developing solutions across a broad range of issues. The Amelia Island Community Planning Conference, which spawned JCCI, defined ten priority areas for community dialogue and action: downtown development, education excellence, open housing and housing supply, land use, transportation–mass transit, utilities, work opportunities as a basic human and economic need, additional revenue, strong joint civic effort, and cultural enrichment.4 The Community Planning Council, which became JCCI (together with the Commission on Goals and Priorities for Human Services and the Amelia Island Community Planning Conference), issued a report identifying goals for the community in December 1974, which was expanding on the earlier list of priority areas. These included economic opportunity, education, public safety, the natural environment, health care, racial harmony, and sufficient resources to address these issues.5 In JCCI’s first year, it issued a report, Learning About Jacksonville. This 1975 report asked, “Is Jacksonville a good or bad city?” The report directly discusses the QOL in the community, compiling “data briefs” on 11 areas: community (including governance issues and opportunities for citizen involvement), criminal justice, employment/financial assistance, energy, environment/ land use, health, housing, learning, public service, recreation/culture, and social services.6 JCCI next turned to citizen-based studies on priority areas of community need, developing recommendations for action and a citizen implementation advocacy process for these study recommendations.7 A 1981 study, Coordination of Human Services,8 led to the creation of the Human Services Council, a coalition of the primary regional funders (public and private) of health and human services in Northeast Florida, with JCCI providing staff support. In 1983, this effort produced a report, Indicators of Human Needs in Jacksonville,9 using both survey and empirical data to measure and prioritize social indicators. These events provided JCCI with a background in research and citizen involvement and a holistic perspective of the interrelated issues that need to be addressed to achieve the desired community QOL. At the same time, the Jacksonville Chamber of Commerce, which had been involved with JCCI since its beginning, set as a goal to “monitor and help improve those elements of Jacksonville which affect the quality of life.”10 Its specific objectives included an action step to “develop a measurable quality-of-life assessment for Jacksonville for the purpose of influencing strategic and operational planning.”11 This objective was realized in 1985 when the chamber and JCCI came together to measure the QOL in the community, expanding beyond economic indicators to measure the breadth of what was important to the Jacksonville community. The project was informed by the national conversation about the importance of addressing QOL issues as part of an economic development strategy, with the following quote being representative of the material shared at the early planning meetings:

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Money is just one factor in attracting high-tech companies. Unlike smokestack industries that need access to raw materials, energy, and transportation, high-tech plants locate where the quality of life is high enough to draw a skilled work force. (Business Week, March 18, 1983)

The chamber referred to the QOL project as “a source of information for developing its own goals and objectives for each year.”12 JCCI saw the project as a tool to identify problems that required community attention.13 Both organizations anticipated that the project would lead to an improved QOL for Jacksonville. The project built on a series of efforts across the country to measure or rate the QOL. Models for QOL measurement used by JCCI included Midwest Research Institute’s Quality of Life in the U.S. (1970), an attempt to compare metropolitan areas using five QOL components14; a New York Times article comparing New York City in 1975 and 198315; and a 1972 community social-environment audit conducted by the First Bank of Minneapolis. In addition, the indicators developed by the Places Rated Almanac16 and a new “quality-of-life” section in the statistical reports coming from the Bureau of Economic and Business Research at the University of Florida17 informed the project. However, these reports did not meet the community’s needs, as seen by JCCI and the chamber. They looked for an approach that brought citizens together to define their own vision for the community and develop indicators that measured, across some set of elements, how well the community was reaching that vision. From the beginning of the QOL project, the emphasis was on measuring Jacksonville against itself, not in comparing Jacksonville to other communities, and institutionalizing this self-reflection as part of how the community moved forward. The 94 volunteers who joined in the effort to describe, define, and then seek to measure the community’s QOL searched unsuccessfully for a model that accomplished their purposes. Forging a new path, they proclaimed: As far as we can determine, no other city has attempted a task such as this in such a comprehensive manner with the intent of annual review and monitoring. There has been no effort nationally to develop or standardize such data. Jacksonville can be proud of this project for it signifies tangible evidence of a forward looking Chamber of Commerce, with a strong commitment to monitor and improve the livability of our city. The value of this project will increase over the years, as trends become apparent. If used properly, it will become a yardstick for community improvement. It sets forth both the implicit and explicit needs of the community and the resources currently allocated to these needs, providing community decision-makers and leaders with the capability of further improving what is already a highly attractive quality of life.18

Decision Points In creating the report, JCCI encountered a series of decision points that shaped the report and, in so doing, helped shape the efforts to improve the QOL in Jacksonville. The methodology of the report will be described through examining

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these decision points, identifying the course of action JCCI took, and finally discussing some of the observed ramifications of those decisions. A time line of major improvements to the indicators can be found in Appendix B.

Purposes of the Quality-of-Life Report Perhaps the first decision that shaped the QOL project was its purpose—the reasons behind creating the document. The original purpose was stated (in a 1985 memorandum) as follows: The purpose of this project is to develop an annual or bi-annual objective assessment of Jacksonville’s quality of life, to be published in a brief and readable format. This would provide a self-evaluation tool of Jacksonville and its progress over time, but not a comparison of Jacksonville’s quality of life with that of other cities. The uses of the assessment would be many. For the Chamber of Commerce it would supplement the 2005 vision and assist in establishing Chamber priorities and work programs. Those areas which show evidence of improvement in the assessment would be highlighted to continue the high level of civic pride which the Chamber has fostered in recent years. For the Jacksonville Community Council, the assessment would be useful in pointing out areas deserving further research, analysis, and community action. For the city government, the assessment should assist in establishing priorities and budget items. As one indicator of community needs, the assessment should be important to the United Way when those needs are related to human services.19

When JCCI published its Quality Indicators for Progress: A Guide to Community Quality-of-Life Assessments manual in 1994, it had extended the purposes of QOL reports to include all of the following: ● ● ●

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To produce an annual report card on community progress To serve as a planning tool for government and private institutions To educate the residents about their community and the factors they consider important to their QOL To increase awareness of the many components of progress and their interrelatedness, the connections between people and their environment To highlight community success stories and give credit for work well done To identify areas of decline or concern where community action is needed To help focus community resources and efforts in the areas of highest priority To encourage residents to take an active part in addressing community problems To promote accountability of local government To stimulate new and better ways of measuring progress20

Significantly, even though the chamber was a coinitiator of the project and a partner throughout (at first financially, then providing leadership for the citizen review panel annually), the purpose of the QOL document has never been to market the community to incoming businesses, though the document has been used successfully to provide a thorough picture of the community to interested companies. Sometimes jokingly referred to as the “wart report” (because it shows the

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community, warts and all), the QOL document has retained the independence necessary to tell the complete story about the community, without trepidation that some aspects of the report might make the community “look bad.” In addition, the report was never designed to advance a particular agenda or support specific policy recommendations. This has allowed the document to be used by a broad constituency in the community, as the data presented are perceived to be independent of bias or manipulation to further a single position. At a time when many in the local community tend to distrust statistics, this perceived fairness has been critical to the widespread reliance on the report. However, because the report is not designed to further a particular cause, the report lacks the strength of other advocacy tools in making policy change. The readers are compelled to draw their own conclusions about the data and what can be done to improve the QOL.

Defining the Quality of Life The project defines the QOL as “a feeling of well-being, fulfillment, or satisfaction resulting from factors in the external environments.”21 It divides the external environment into nine elements, states a vision or goal for each element, and then provides indicators to measure the progress in meeting that vision. The nine elements developed from the ten priority areas of the Amelia Island Conference, the eleven data briefs of the Learning About Jacksonville report, and the areas of need identified in the Indicators of Human Needs study (see p. 3.) In the initial proposal to the chamber, only seven elements were identified: economic, political/governmental, environmental, health, education, social, and leisure/cultural.22 Public safety and mobility (transportation) were added to the list as the steering committee was assembled. While staff developed these element areas, citizen volunteers fleshed out the elements by identifying the indicators to measure the aspects of the element they thought important for the community. The report was, from its inception, a community definition of the QOL, reflecting the unique perspective of citizens living in the community determining what was important to them. Annual citizen review of the document requires the document to respond to the community viewpoints. Having citizens determine the indicators to be measured (and later, the targets [community goals] for the indicators) has added perceived legitimacy to the project and encouraged its widespread adoption. In 2000, the elements were prioritized in the order of need for community attention. In 2002, the titles of the elements were adapted to reflect an active description of the aspect of the QOL to be measured, and goal statements were provided to further elaborate on what was being measured. The elements now read as follows23: ●

Achieving educational excellence. Educational institutions in the region achieve excellence in the delivery of learning opportunities, and citizens achieve educational attainment sufficient to enjoy a high QOL. Citizens, young and old, have access to a broad range of learning opportunities in pre-K to 12th grade,

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higher education, and life-long learning, based on their educational needs and desire to learn. Growing a vibrant economy. The regional economy supports a vibrant and diversified mix of economic activities, which combine to provide ample opportunities for productive employment, a strong consumer market, the capacity to fund needed public services, and a high standard of living that is shared widely among all citizens. Preserving the natural environment. The resources of the region’s natural environment positively enhance the QOL of citizens, and air, water, and ground pollution is kept below levels harmful to ecosystems, human health, or the QOL. The built environment is developed in ways that preserve natural ecosystems and is maintained in ways that enhance natural beauty and visual aesthetics. Promoting social well-being and harmony. Social-service institutions in the region provide services with excellence to those in need, citizens and institutions support philanthropy and volunteerism to enhance the social environment, and citizens share social interactions characterized by equality of opportunity and racial harmony. Enjoying arts, culture, and recreation. Citizens desire, support, have access to, and actively patronize a great diversity of opportunities in the region for cultural and artistic enrichment and for recreational, leisure, and entertainment activities. Sustaining a healthy community. Health-care institutions in the region provide medical and preventive health-care services with excellence; all citizens have access to these services, regardless of financial means; and citizens generally experience a high level of physical and mental health. Maintaining responsive government. Local governmental bodies in the region are led by competent, representative, and responsive elected and appointed officials; they provide public services effectively and equitably to citizens; and citizens are well informed about public affairs and actively participate in civic activities. Moving around efficiently. Citizens in the region have access to affordable, convenient, and accessible transportation services with the capacity to convey them around the community and around the world to their chosen destinations at their chosen times. Keeping the community safe. Public-safety agencies in the region provide rescue, fire, and law-enforcement services with excellence, and citizens generally experience a low level of crime and a high level of personal safety.

This broad definition of the QOL has proved important to the community’s understanding of the interrelatedness of multiple factors on community well-being and progress. However, the report does not distinguish between the relative importance of these factors—Is going to the symphony as important to one’s QOL as having employment that provides the wherewithal to attend a concert, or having a feeling of personal safety that allows one to leave the house for a night on the town? The report also limits its definition of the QOL to factors within the purview of policymakers. Although few would argue that the QOL in Northeast Florida is significantly enhanced by sunshine, beaches, and ocean breezes, gifts of nature are

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not within the ability of citizen advocates to affect and therefore are not measured. For many, the quality of interpersonal relationships is a significant factor in their QOL, yet the document chooses to focus on a community definition of the QOL, rather than on an individual happiness scale.

Involving the Community Throughout the process of designing the QOL project and determining what “quality of life” meant, community involvement played a central role. Over the last 20 years, citizen involvement has remained a defining characteristic of the Jacksonville model. Deciding who decides was the third major decision point of the project. The QOL project began with a partnership of two institutions, JCCI and the chamber, with local government as a third interested party. JCCI staff sketched the outlines of the proposed project, and the chamber agreed with the design and provided leadership for the undertaking. At that point, 100 community representatives were invited to sit on one of ten committees—one committee for each of the nine elements, plus a steering committee. The project grew from, and was bought into by, the community. Staff roles were concentrated on researching the availability of proposed indicators and documenting the process used to reach the final indicator set. Community volunteers chaired each of the committees and facilitated their progress. Government, rather than direct the project, was in a position to respond to the indicators. This allowed the community to tell government what was important in service delivery, as well as to create indicators of the responsiveness of local government to citizen needs. This bottom-up approach made the project an outside evaluation of government effectiveness, rather than an internal benchmarking of process goals. Nonetheless, in 2001 the City of Jacksonville received the Governor’s Sterling Award for quality practices, using (among other statistics) the quality-of-life indicators as measures of government performance. This commitment to citizen engagement remained throughout the project. Annual reviews, target setting, creating linkages among indicators, setting priorities among the elements and within the elements, and amalgamating the QOL document with the community agenda were all done by citizens. Each process was informed by stakeholders and experts in the community, but the decisions were left to citizens, allowing the document to develop through a learning and adapting process while retaining trend lines whenever possible.

Selecting Indicators Using a shared definition of the QOL and nine elements to provide focus to the project, citizens representing the broad diversity of the community were charged to select the indicators to quantify and measure the QOL. The original charge to the citizens was to select no more than ten indicators per element; after amalgamating the QOL and the Community Agenda, this restriction no longer applies. Determining what makes a good indicator was a necessary step in selecting

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indicators. The following guidelines have been used to define meaningful and useful community indicators: ●

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Purpose. The indicator is both meaningful (it provides information valuable for community members to understand the important aspects of their QOL) and useful (it offers a sense of direction for additional research, planning, advocacy, and action toward positive community changes and a means of assessing progress toward these desired changes). Importance. The indicator measures an aspect of the QOL which a diverse group of people in the community would agree as important in relation to the priorities in the community’s shared vision or goals. Validity and accuracy. If the indicator trend line moves upward or downward, a diverse group of people in the community would agree on whether the QOL is improving or declining. Relevance. The indicator measures an aspect of the community’s QOL concerning which the community can achieve positive change through public decisionmaking and action at the community level. Responsiveness. The indicator trend line responds relatively quickly and noticeably to real changes in the QOL. Anticipation. The indicator anticipates future trends rather than reacting to past trends. A “leading” indicator, e.g., cigarettes sold, is generally more useful than a “lagging” indicator, e.g., lung cancer deaths, because it allows a proactive response. Understandability. The indicator measures an aspect of the community’s QOL in a way that most citizens can easily understand and interpret in relation to their own lives. Availability and timeliness. Data for the indicator are readily available and affordably accessible on an annual basis from a credible public or private source. If data come from multiple sources, staff can readily compile and calculate the indicator. Stability and reliability. Data for the indicator are consistently collected, compiled, and calculated in the same way each year. Outcome orientation. Where possible, the indicator measures the actual condition of the community’s QOL. Alternatively, it measures an outcome of the community’s response to the issue rather than the input of the response itself. Asset orientation. Where possible, the indicator measures a positive aspect of the community’s QOL (to focus on community assets), and a trend line increase clearly denotes an improvement in the QOL. Scale. The indicator is reported for a geographic area that is most meaningful for community understanding and most helpful for improvement. For many indicators, both regional and single-county trend lines are reported; others have subcounty measures. Linkages. The indicator reports important interrelationships among indicators and over time. Some of these linkages may positively reinforce one another; for example, improving the public high school graduation rate may, over time, improve employment rates, as high school graduates are more likely to obtain

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and maintain employment. Others may conflict with one another, possibly reducing the QOL; for example, increased housing starts may result in longer commute times and poorer air quality because of the negative influence of increased traffic. All indicators within an element are assumed to be interrelated to some degree; linkages are created only between indicators in different elements. Clarity. The indicator uses clear measures that filter out extraneous factors. Perperson rates filter out the effect of population growth, and constant dollars eliminate the effect of inflation. Raw numbers are used where total magnitudes are important. Representativeness. Taken together, the indicators measure the major dimensions of the community’s QOL.

Selecting indicators often involved compromise between the ideal (what the community would like to measure) and the practical (what data are available.) For some characteristics of the QOL, community perception was as important as available data; for example, one’s QOL is affected by both actual crime rate and one’s perception of personal safety. To address these issues, JCCI commissioned an annual telephone survey. In 2005, 17 of the 119 indicators were based on survey questions. Part of selecting indicators involved recognizing that each indicator is in itself a value judgment, not just a statistic. Indicators represent the operational definitions of community values, measuring what is important to the community. Indicators not selected may be perceived as value judgments as well, that the data not measured lack community importance or do not represent a community priority for action. These perceptions may in themselves be an unintended consequence of lack of available data for measuring an important community issue. Selecting an indicator requires selecting the geographical scale being measured. Some issues are affected by regional inputs and require regional action to address effectively. For other indicators, a regional measurement may hide significant variances and needs for community action within the broad average. Some indicators may require subcounty or neighborhood-level measurement to get to areas of meaningful impact. The QOL project began by measuring all indicators at the county level. The community agenda measured indicators at a five-county regional level, where possible. In 2000, a citizen committee specifically addressed, indicator by indicator, the question of geographic scale. The 2005 QOL document seeks, whenever possible, to provide regional, county-level, and subcounty information in the graphs and trend lines or on the supplemental data files. In addition to geographical scale, some indicators are time-sensitive. For example, a short-term positive trend for an indicator can sometimes lead to a negative trend in the long run, such as new housing starts (which may meet a community housing need in the short term but lead to unmanaged growth in the long term). This is especially evident in certain indicators relating to economic growth. Other indicators are sensitive to geography, meaning that negative trends of some indicators can “flow” into other areas, even as trends are improving in the initial areas. For instance, reducing crime in one area may simply move it to other areas, rather than eliminating it. In another example, efforts in one area to reduce air pollution may be negated by pollution blowing from other nearby areas.

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Most of the indicators have important linkages with other indicators (see p. 15), either reinforcing the trend of another indicator or undermining its progress. The citizen review committee noted that “understanding and reporting these linkages is important because effective community decision-making to improve the QOL depends on consciously seeking to encourage reinforcing linkages, while minimizing the effects of undermining linkages.”24 One limitation in selecting indicators to measure the QOL is that, in many ways, the QOL cannot be assessed exclusively through quantifiable indicators. Important qualitative measures of progress have not been included among these indicators if they cannot somehow be quantified. While the community’s QOL may be enhanced to the extent that its growing senior population is respected and actively involved in charting the course of the city, solid data measuring the civic engagement of the elderly is difficult to find locally. Annual citizen review and continual citizen involvement in the project raised another concern in indicator selection: the problem of maintaining continuity while adapting to community change. In order to respond to changing community needs, new indicators may be added and obsolete indicators deleted in the review process. However, the effectiveness of indicators often depends on their continuity and the length of trend lines over time. Of the 119 indicators in the 2005 document, 36 original indicators with their original definitions remain (a complete list of the indicators found in the 2005 document is presented in Appendix A.) Not all of the variance is due to citizen preference, however; many of the changes in indicators stem from problems associated with finding data.

Finding Data JCCI decided from the beginning that it would not be a primary data source for the indicators. Instead, with the exception of the survey data provided by a local polling firm, JCCI would collect data from other sources such as government agencies and major community institutions. This has posed significant challenges to JCCI over the years. The effectiveness of an indicator may decline if the institution collecting the data changes its definitions or reporting processes. In some cases, significant movement in trend lines results from institutional policy changes rather than actual shifts in community needs; for example, a change at the state level in defining child abuse or in collecting and reporting cases of suspected child abuse may significantly alter the indicator without a corresponding change in the number of children being abused. Sometimes JCCI has needed to advocate for better data collection and availability from institutions, rather than pushing for progress in addressing an identified community priority. Although JCCI does not do primary research, some indicators require multiple inputs and staff calculations in order to adjust primary data to make it meaningful. Indicators that measure dollar amounts, for example, are adjusted using the Chain-type Price Index from the annual Economic Report of the President,25 and many indicators measure a rate per person in the population. Here citizen input can be extraordinarily helpful in identifying ways to make data meaningful; for

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example, the 2004 indicators review committee suggested measuring the number of available boat ramps in the community not as a rate per total population but as a rate per licensed boats in the community. Sometimes the need for community understandability conflicts with the desire to provide adjusted data. For several health indicators, age-adjusted death rates are the preferred method of statisticians and epidemiologists to factor out differences in relative ages in the populations studied. However, citizen review panels have repeatedly insisted that age-adjusted death rates are too complicated for the layman to understand, and that a simple per-population rate provides a better way for the community to discuss a significant community issue without the level of detail professionals may use. When JCCI began its QOL project, the primary challenge was finding data. Over time, with the growth of the information age, increased availability of data via the World Wide Web, and expanded citizen access to up-to-the-minute information on multiple subjects, the challenge has shifted from finding data to presenting data.

Presenting the Indicators The first decision point in presenting the indicators was defining the audience for the report. As discussed earlier, the multiple purposes of the document required that the data be presented with multiple audiences in mind. Government agencies needed information about their perceived effectiveness in meeting community expectations for services. Human service-funding organizations desired data to define unmat community needs. The chamber and other private institutions needed a comprehensive overview of Jacksonville in order to develop strategies and work plans. Everyday citizens wanted to know about their community and to identify where they could get involved to do the most good. And the media, an important audience that serves as the primary conduit of the report’s findings to the community, needed simple, clear messages of community priorities and improvements. From the beginning, many have asked for an overall score or letter grade for the QOL project, a simple answer to the question “how is the quality of life in Jacksonville this year?” JCCI decided not to create an overall index for the QOL, and instead insist that the indicators stand as independent measures of a range of community activities and needs. From the first, committee members felt that a composite QOL index “would distort, rather than clarify.” “The indicators were not of equal importance, and ranking them involved highly personal judgments.”26 Instead, the message of each report has been to identify the areas of improvement and the priority areas for action, identified respectively with gold stars and red flags. The decision was also made at the beginning to report the indicators annually. This has allowed the report to be institutionalized in the decision-making process of community agencies and organizations. In addition, the data-gathering requirements of the report are often better served by an annual effort, as each year tracking down changes in definitions, data-collection methods, and individuals responsible for providing data is a significant task. Returning to this effort every two years or longer could significantly magnify the data-collection problems.

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As JCCI collected data and built up a reputation in the community as an important source for meaningful information, JCCI needed to decide how much information it would gather and distribute. The QOL project had begun with a limited set of 84 indicators. As information technology grew, the possibility of creating a data warehouse—a single repository of extensive amounts of relevant community information—was discussed. This model, when linked with GIS software and made available via the Internet, provides a user interface where the consumer (citizen, stakeholder, or decision-maker) has the ability to select a personalized indicator set out of an array of possibilities, perhaps identifying not only the desired data but also the geographical scale the data should cover. Another possibility was to create a data clearinghouse, a single Internet location that (instead of physically storing an expanded range of data) could create links for the users to explore information on other websites. Although both the data warehouse model and the data clearinghouse model are potentially highly useful and important community tools, both models share similar drawbacks when compared to the QOL indicator model. The strength of the QOL model is its ability to reflect and reinforce in the community a shared vision of priority areas for action. Through its indicator linkages, it challenges the user to think about community issues in new ways; someone concerned with economic development, for example, is forced to examine the roles that preserving the natural environment or addressing social needs have in the local economy. The benefits of the data warehouse and the data clearinghouse models—expanded community data self-selected by the user—become their limitations. Instead, JCCI elected to maintain a single indicator set as its primary presentation. Its focus was measuring progress and identifying priorities, not presenting data. However, for each indicator an expanded data spreadsheet was created, containing additional information about the indicator and often web links to additional data sites, similar to a data clearinghouse model. These spreadsheets are provided on JCCI’s website and, in the printed version of the indicators, on a CD included with the document. Another decision point about the presentation of the data revolved around the context and explanations provided with the numbers and the graphs. The graph alone, without any explanation or analysis, can be misleading; an indicator measuring local airline travel would be remiss if it did not point out the impact the events of September 11, 2001, had on the industry. At the same time, too much analysis and interpretation can jeopardize the organization’s reputation of providing only the facts. JCCI decided from the beginning that each indicator would be accompanied by a section called “caveats and explanations” that would describe the limitations of the data and any significant events that might impact on the trend line. However, while JCCI provides explanations for each indicator on what it measures and why it has importance in the community, the document does not describe what should be done to address the needs identified by the indicator. The analysis of the data does not extend to the point of making recommendations for action in the community; JCCI has a separate community study process for reaching conclusions and developing action plans for the community. The QOL document is designed to stand

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on its own and be used by individuals and groups in the community who want to take action themselves. One result of the citizen focus of the document has been to attempt to present the indicators in the most accessible manner possible. JCCI does not provide an analysis of statistical significance of the movement of the trend lines. Instead, the information is presented for the layperson’s benefit, an indicator of community trends rather than an extensive study of the subject. The indicators answer the simple question: Are we doing better in this area than we were last year? They are designed to encourage further investigation into the information, rather than provide all possible information. These decisions helped shape the format in which the indicators are presented to the community. JCCI now creates an executive summary of the indicators, discussing in narrative format the movement of the indicators during the past year. Each of the nine sections receives its summary page. The document, in print form, is designed to be a conversation-starter as well as a reference document. For those with greater needs to dive into the information, the raw data are provided in spreadsheets over the Web or on an enclosed CD with the print document. Each year, the document is tweaked with the focus on how the multiple audiences use the book, and looking for ways to make examining data more inviting and accessible.

Using the Indicators Indicators in isolation are simply numbers. While they can indicate areas of community progress or trouble spots, they do not identify the underlying causes of the problem, provide a full understanding of the nature of the problem, describe how the community is currently addressing a particular problem, or prescribe a detailed action plan. Knowing the unemployment rate does not, in itself, create jobs. Six years into the project, JCCI created targets for each indicator (see time line in Appendix B). In addition to revising the indicator set, the volunteers in 1991 set community goals for the indicators. With Community Development Block Grant funding from the City of Jacksonville, JCCI staff researched trend projections, as well as existing standards and goals for the various indicators. Using this information, community task forces established a target for 2000 for each indicator, a goal representing a point between the ideal and the possible, which the community could reach in the time specified if it devoted sufficient time and resources to the question. In 2001, the targets for 2005 were set, after the learning experience that 10-year targets represented too much time for the goals to be both meaningful and attainable. Adding targets to the indicators, as JCCI has done, identifies how much progress the community hopes to achieve by a certain date. However, even with targets, the indicators can only report where the community wants to be, not how to get there. In creating community QOL indicators, JCCI needed to decide how the indicators fit into an overall community change strategy. The resulting model for community improvement demonstrates how the QOL report plays a significant role in community improvement.27 The model begins with a vision for the community,

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built on the values shared by citizens in the community. To assess the community’s relationship to that vision requires knowledge, and here JCCI’s indicator report comes into play. Community improvement depends initially on accurately determining how close or far the community is to its goals. The next stage of the model involves using the indicators to develop strategies and create a plan of action. The indicators help by identifying priorities for action and spurring on the research component. The following step is the action to improve the community. The action should produce results of some sort, and assessing the outcomes of that action requires indicators once again. Based on the outcome assessment, the model calls for revisiting the vision, the indicators used to measure the community’s progress toward the vision, or the plan used to move the community closer to that vision (Figure 1). JCCI uses the model for its internal processes. The QOL indicators identify priorities and inform JCCI’s selection of issues for community study. Its consensusbased citizen study model is the primary means JCCI uses to develop action steps to address the issues identified by the indicators. At the completion of each study, JCCI commits two years to an implementation effort to ensure that the recommendations translate into community action. The results of these efforts can be seen in the indicators, which track progress toward addressing the priorities originally identified. The indicators are also used in many different community organizations. ●

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The City of Jacksonville uses the indicators as internal benchmarks for local government functioning and quality improvement. The Jacksonville Sheriff’s Office looks to the indicators to gauge public perceptions of safety and satisfaction with public-safety services. The Jacksonville City Council has used the document to orient newly elected officials to the needs of their constituents. The Human Services Council, a coalition of the primary public and private funders of health and human services, uses the indicators in their annual planning retreat and as part of their funding decisions. The Jacksonville Regional Chamber of Commerce, in addition to the involvement of the incoming chamber president in the annual indicators review,

Values Vision

Knowledge Indicators

Research/strategies Priorities/plans

Assessment Indicators

Advocacy Actions

Outcomes Results

Fig. 1. JCCI model for community improvement.

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discusses the indicators at their annual Board of Governors meeting where they install their new officers for the year. Leadership Jacksonville presents the QOL report at their opening retreat for each new leadership class, and the indicators inform the learning curriculum for the year. Leadership Jacksonville also provides a “New CEO Orientation” for executives moving to Northeast Florida, and the indicators inform participants about the priority needs of the community. Local media use the report to generate stories about the QOL in Northeast Florida. And many other institutions, including social service providers, private foundations, businesses, and everyday citizens, use the report for strategic planning and directing their efforts to build a better community.

The result has been to institutionalize the indicators across multiple community organizations. Effective use of the indicators often requires embedding them in the complex processes the community uses for its improvement efforts. Publishing the report annually has been an important facet of this strategy. By building the report into the decision-making and strategy-planning activities of multiple community institutions, Jacksonville is more likely to see positive steps taken to address the needs identified by the indicators.

Improving the Community After the indicators are released and the priority areas for community action are identified, the most critical—and most difficult—step is translating the data into sustainable community improvement. For JCCI, this begins with looking for opportunities to make the indicators part of the process of reflection and strategic planning across as many community organizations as possible. Beyond informing planning processes, however, the indicator report needs community partners ready and willing to step forward and accept the charge to make a difference. Along with a broad definition of the factors that make up the QOL, JCCI maintains a broad conception of who is responsible for improving the QOL. Binyamin Applebaum wrote at the release of the 2003 Quality of Life Progress Report: In some ways, the best news for Jacksonville is the report itself. The very premise of the report, and of JCCI, is the belief in Jacksonville as a community where the problems of some are the responsibility of everyone.28

In 1998, an Indicators Steering Committee reflected on the previous 13 years of work and began developing a vision for how the indicators project could best serve the community. After compiling all community visioning efforts completed between 1988 and 1998, the group identified shared values and themes out of the 12 vision statements collected. The elements of these vision statements corresponded to the nine elements of the QOL project, with one exception—thriving neighborhoods and downtown—that was identified as “more a statement of the importance of place than a separate aspect of the quality of life.”29

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These efforts resulted in a vision statement for the QOL project: JCCI’s indicator reports will be the premier local, summary-level information on the quality of life in Jacksonville. Each annual update will be the community’s report card, containing vital, valid, and relevant information, which is actively used to inform the community, guide decisionmakers, ensure public accountability, and promote a continuously improving quality of life for all citizens.30

This vision of engaging the community in a shared, concerted effort of selfimprovement relied on an extensive marketing effort to ensure that the indicator document was used throughout the community. Unfortunately, funding for this marketing effort never materialized. Instead, JCCI has marketed the QOL report to the extent possible, using only in-house resources. While some of the results have been gratifying, JCCI continues to explore new opportunities for addressing this strategic goal. JCCI’s marketing effort has been undertaken in a time when data itself is more freely available than ever before. This begs the question of whether JCCI’s QOL indicator project continues to be relevant, 20 years after its inception. The enduring priority in the report is improving public education, yet enormous amounts of information about our public education system are available online and at the School Board offices, far exceeding the number of indicators in the report. When the public school system needs data to drive internal decision-making about improving the school system, it turns to its internal data sources—the same sources that provide the data for JCCI’s indicators. When the media wants to run a story about the progress of public education reform, it turns to the primary data source for its information. When parents want more information about the school their children are attending, they turn to more comprehensive data sources at the school system. This example holds true for most single-issue advocacy opportunities surrounding the indicators in the report. Outside of the survey questions, none of the indicators are uniquely available through JCCI. (If they were, JCCI would not be able to get them.) What is unique, however, and perhaps the most useful aspect of the report, is the collection of the range of indicators into a central report, painting a more complete picture of the needs and triumphs of the community. The indicators are not just interesting bits of information or conversation starters in the community, prodding the community to take action. The Quality of Life Progress Report serves as a lens through which the reader can view the community, with all its strengths and weaknesses, in a way no other source provides. As JCCI’s indicator processes continue evolving, learning from thousands of communities around the world wrestling with the same questions of measuring progress and creating community improvement, some things remain constant. The indicators come from the community, measuring progress against a broad definition of the QOL. The indicators are reviewed by the community annually, to assign gold stars/red flags and develop priorities for community action. And the indicators are presented to the community as an important tool for understanding how people and organizations across Northeast Florida can work together to improve what is still a highly attractive QOL.31

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Appendix A: Quality-of-Life Indicators Measured in JCCI’s 2004 Quality-of-Life Progress Report Achieving Educational Excellence ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Public high school graduation rate Public high school dropout rate High school dropout education outcomes High school dropout employment outcomes Tenth graders reading at grade level Tenth graders at grade level in math Public school attendance Public school first grade promotions Fourth graders writing at grade level Average public school teacher salary Teachers with advanced degrees Students attending racially balanced schools Magnet school enrollment High school graduates employed or in college High school graduates prepared for college Exceptional students completed high school Satisfaction with public education Higher education degrees and certificates Total participation in continuing education Expanding literacy: early literacy Expanding literacy: school-age literacy Expanding literacy: adult literacy

Growing a Vibrant Economy ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Net employment growth Average annual wage Unemployment rate Unemployment benefit claims Children in poverty (free lunch participation) Income available per person Recipients of public assistance Requests for emergency assistance Affordability of a single-family home Typical monthly household Jacksonville Electric Authority utilities costs New housing starts Total taxable value of real property Gross tonnage handled by marine terminals Tourism (as measured by bed-tax revenues)

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Preserving the Natural Environment ● ● ● ● ● ● ● ● ● ●

Days the air quality index is “good” Gallons of motor fuels sold per person St. Johns River compliance with oxygen standards St. Johns River bacteria standards compliance Average water consumption Water level in Floridan aquifer Tons per person of solid waste recycled New septic-tank permits issued Manatee deaths Conservation land

Promoting Social Well-Being and Harmony ● ● ● ● ● ● ● ● ● ● ● ●

Is racism a local problem? Have you personally experienced racism? Births to teen mothers per 1000 live births Subsequent births to teen mothers Foster children per 10,000 children Median length of stay in foster care Births to mothers with 12 years of education Children of parents becoming divorced Do you volunteer? Do you volunteer more than 7 hours a week? Philanthropy given to federated campaigns Homeless count per 100,000 people

Enjoying Arts, Culture, and Recreation ● ● ● ● ● ● ● ● ● ●

Public performances/events at selected facilities Public and private support per person for the arts Public-park acreage per 1000 people Participants in sports activities at parks and pools Attendance at musical shows per 1000 people Attendance at sports facilities per 1000 people Attendance at selected events per 1000 people Library use (as measured by circulation per person) Recreation expenditures for activities/maintenance Boat ramps per 100,000 people

Sustaining a Healthy Community ● ● ●

Racial disparity in infant deaths Infant death rate Newborns with healthy birth weights

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Early prenatal care Children receiving scheduled immunizations Alcohol use reported by youth People with no health insurance Jacksonville health care rated as high quality Deaths due to heart disease per 100,000 people Cancer deaths per 100,000 people Lung cancer deaths per 100,000 people Packs of cigarettes sold per person Nursing-home patient days per person aged above 65 People receiving home-delivered meals Newly diagnosed AIDS cases per 100,000 people Sexually transmitted disease reports HIV racial disparity HIV/AIDS-related deaths per 100,000 people

Maintaining Responsive Government ● ● ● ● ● ● ● ● ● ● ●

Elected leadership rated as high quality School Board leadership rated as high quality Can you influence local government? Voter registration Percentage of registered voters who vote Satisfaction with public-safety services Keeping up with local government news Diversity of elected officials Satisfaction with basic city services Can you name two city council members? Households watching local early-evening news

Moving Around Efficiently ● ● ●

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Commute times of 25 minutes or less Average seats on airplane flights Destinations served by direct flights from Jacksonville International Airport (JIA) Total passengers flying in or out of JIA Average weekday Jacksonville Transportation Authority (JTA) bus ridership Average weekday miles of JTA bus service JTA bus headways within 30/60 minutes Average weekday skyway ridership

Keeping the Community Safe ● ●

Index crimes per 100,000 people Juvenile delinquents per 1000 youth

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Serious student conduct violations Juvenile alcohol/drug arrests per 1000 youth People feel safe in their neighborhood at night People report being victims of a crime Rescue-call response times under 4 minutes Fire-call response times under 4 minutes Police-call response times under 5 minutes Child abuse reports per 1000 children Domestic-violence-related crime reports Domestic-violence-related homicides Motor-vehicle accidents per 1000 people Violent deaths per 10,000 youth

Appendix B: Time line of JCCI indicator improvements 1974 1975 1985 1991 1991 1995 1998

1999 2000 2000 2001 2002 2002 2002 2005

Amelia Island Conference JCCI created “First Life in Jacksonville: quality indicators for progress” document published Indicator set revised Targets for 2000 created for all indicators “Creating a community agenda: indicators for health and human services” first published Indicators Steering Committee creates subcommittees to address the vision for the indicator project(s), create a process to upgrade the indicator set, and market the indicators to the community Targets for 2005 created for community agenda indicators Indicators upgrade project—review of all QOL indicators and prioritization of elements and indicators within each element Linkages among QOL indicators created Targets for 2005 created for QOL indicators Linkages created among community agenda indicators and QOL indicators Indicators of Civic Health project completed Amalgamation of community agenda and QOL indicators into one indicator set completed Race Relations Report Card (indicators of racial disparity and discrimination) project completed

Notes 1. Bureau of Economic and Business Research, University of Florida (2004). Florida Population Studies, Population Projections by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties, 2003–2030, 37(3). 2. Jacksonville Community Council Inc. (2004). Quality-of-Life Progress Report.

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3. Jacksonville Community Council Inc. (2004). Quality-of-Life Progress Report. 4. Jacksonville Community Planning Conference: A Report (1974). Published by the Jacksonville Area Chamber of Commerce. While the official title referenced Jacksonville, because the conference was held at Amelia Island (a resort area just north of Jacksonville), by 1975 the name had been changed to reflect the location, and subsequent references to the conference have consistently maintained that geographical identification. 5. The Commission on Goals and Priorities of the Community Planning Council (1974, December 15). Goals and priorities for Jacksonville. Times-Union and Journal. 6. Learning about Jacksonville: issues and trends in our community. A summary of citizen team reports submitted to the Jacksonville Council on Citizen Involvement Inc. (1975). 7. For a list of the studies JCCI has conducted, see www.jcci.org. 8. Jacksonville Community Council Inc. (1981). Coordination of human services. 9. Indicators of Human Needs in Jacksonville, A Product of the Jacksonville Human Services Coalition (1983, November). The Human Services Coalition was later renamed the Human Services Council. 10. Jacksonville Chamber of Commerce Community Development Department, 1983. 11. Jacksonville Chamber of Commerce Community Development Department, 1983. 12. Meeting summary, Quality-of-Life Assessment Planning Session, January 14, 1985, p.1. 13. Meeting summary, Quality-of-Life Assessment Planning Session, January 14, 1985, p.1. 14. Lice, Ben-Chich (1970). Quality of Life in the United States, Midwest Research Institute. 15. From 1975 to now: how’s New York City doing? (1983, April 10). New York Times, IV, p. 6. 16. Boyer, R. and Savageau, D. (1981). Places Rated Almanac: Your Guide to Finding the Best Places to Live in America. New York: Rand McNally & Company. 17. A great place to marry ... (1985, March). Florida Trend, p. 27. 18. Hightower, W.A. (1985). Letter to E. William Nash, President, Jacksonville Chamber of Commerce. In Life in Jacksonville: Quality Indicators for Progress, (1985), p. 1. William A. Hightower served as the chair of the original Quality-of-Life indicators project. 19. Jacksonville Community Council Inc. (1985). “Quality of Life Assessment Project,” handout for January 14, 1985, meeting among the Jacksonville Chamber of Commerce, City of Jacksonville, and JCCI. 20. Jacksonville Community Council Inc. (1994). Quality Indicators for Progress: A Guide to Community Quality-of-Life Assessments, p. 90. 21. Jacksonville Community Council Inc. (2004). Quality of Life Progress Report. 22. Meeting summary, Quality of Life Assessment Planning Session, January 14, 1985, p.2. 23. Jacksonville Community Council Inc. (2004). Quality of Life Progress Report. 24. Jacksonville Community Council Inc. (2001, November). Quality of Life in Jacksonville: Indicators for Progress, reference report. 25. Economic Report of the President (2004). Table B-6. Retrieved December 15, 2004. Available at http://www.gpoaccess.gov/eop/ 26. Swain, D. and Chambers, M. (1991, April 18). Quality indicators for progress in Jacksonville: a six-year assessment. Presented at the 21st Annual Meeting of the Urban Affairs Association, Vancouver, Canada, p. 3. 27. Swain, D. (2002, April). Measuring Progress: Community Indicators and the Quality of Life. Retrieved December 1, 2004. Available at http://www.jcci.org/statistics/ documents/measuring_progress.pdf. 28. Applebaum, B. (2004, January 27.) JCCI report finds a growing city with a touch of economic blues. The Florida Times-Union, p. B-1. 29. Jacksonville Community Council Inc. (1998, December.) Compilation and Analysis of Existing Vision Statements for Jacksonville and Northeast Florida, p. 5.

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30. Jacksonville Community Council Inc. (1998, June 15.) Meeting summary of the Indicators for Progress Steering Committee, p. 1. 31. See Hightower, W.A. (1985). Letter to E. William Nash, President, Jacksonville Chamber of Commerce. In Life in Jacksonville: Quality Indicators for Progress, p. 1.

J. BENJAMIN WARNER, Associate Director, Jacksonville Community Council Inc. [email protected]

Indicators as a Structural Framework for Social Change CHARLOTTE KAHN Director, The Boston Indicators Project, The Boston Foundation

Introduction In the Greater Boston citistate, known in the 19th century as the “Athens of America,” it should be easy, in the Information Age, to locate good local data about things that matter. The data do exist, of course, but they are exceedingly difficult to find in a timely and useful format, even for experts. And as difficult as it is to good local data, it is harder still to “connect the dots” to arrive at the shared understanding required for true collaboration. The latter poses a particular hurdle in Metro Boston, where, it is said, we lack “the collaborative gene.” The Boston Indicators Project was conceptualized in 1997 as a “one-stop shop” to address these challenges. Its goals are to: (1) democratize access to data; (2) foster informed public discourse; and (3) track progress on shared civic goals. At its core, the project aims to expand Bostonians’ capacity to make wise choices in order to create a more just, prosperous, and sustainable future for all residents of the city and region. Founded in 1997 as a partnership between the Boston Foundation and the City of Boston’s Environmental Services Department, the project is coordinated and managed today as a freestanding initiative of the Boston Foundation, Greater Boston’s community foundation, in partnership with the City of Boston/Boston Redevelopment Authority and the Metropolitan Area Planning Council, a quasi-public planning agency covering most of the Greater Boston region. The project also collaborates with many community-based organizations, universities and research institutes, public agencies, and civic institutions, providing a well-organized and accessible container for the many sources of excellent research and data produced in and about the city and the region. Its support comes largely from the Boston Foundation, which provides a trusted, neutral ground for deliberation, an excellent communications staff, and its own brand of civic leadership. The foundation is committed to issuing biennial indicators reports through 2030—Boston’s 400th anniversary. The Boston Indicators Project’s theory of change is that broad access to wellorganized data and information in combination with informed, open, and inclusive civic dialogue across the boundaries of sector, geography, race, age, and income will result in more collaborative, strategic, and effective policies and civic action than would otherwise occur. In this sense, the project uses data and information to create the civic common ground on which new relationships can form and new thinking can occur. By the ordinary laws of the world, the project should not exist. Tracking indicators and measures in ten categories, institutionalizing data updates, convening

23 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 23–42. © 2006 Springer. Printed in The Netherlands.

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stakeholders and experts across sectors, issuing a comprehensive online report and a hard-copy summary every 2 years, building a network of engaged stakeholders, and driving a civic agenda is just too broad in scope and too subject to the whims of funding and politics to succeed. Because of this challenge, it is fair to say that the project exists in large part due to the long-term commitment of its partners and participants. For almost a decade, people from multiple neighborhoods, sectors, organizations, agencies, and institutions have volunteered their time and expertise to create and maintain this breakthrough framework of measurement to build a better Boston and a better world. City, state, and federal agency staff, community-based organizations, civic institutions, university-centered research institutes, and independent think tanks have all contributed their research and data. All have participated in convenings and for dialogue, deliberation, and reflection about current trends and effective strategies to attain long-term goals. The Boston Indicators Project is branded as “a project of Boston’s civic community.” Indicators are seen as a means for the Greater Boston community to “measure what we value and value what we measure.” In that spirit, the project seeks to build consensus, or at least broad support, for a set of goals, or agenda, items against which progress can be methodically tracked through 2030. This approach encourages stakeholders to imagine a shared future beyond traditional time constraints such as election cycles, and to venture across traditional boundaries, whether geographic, socioeconomic, racial/ethnic, or generational. In these ways, the project is laying a foundation for collaborative action that may have to be sustained for a generation to fully attain the desired outcomes. In this sense, the Boston Indicators Project is more than a project. It is a tool for civic engagement and collaboration that is being constantly recrafted and enhanced by many minds from many backgrounds and facets of community, academic and civic life. By creating and then using this shared tool, participants are changed by it, and then go to work again to make it better. Within its biennial rhythm and consistent framework of indicators, the project continues to evolve. Following release of a baseline report in 2000 as a hard-copy, 300-page document, the project released its 2002 report in two parts: (1) a comprehensive, multidimensional website www.bostonindicators.org that tracks and reports on indicators and measures in ten sectors across 70 goals and 150 measures, and includes, in addition, a variety of special interactive features; and (2) a summary report that “tells a story” based on systemic analysis and a synthesis of sector convenings, research findings, and indicators data. Both succeeded in garnering media attention as well as action on the issues raised. In its 2004 report, for the first time, the project issued an “emerging civic agenda” drawn from the results of project convenings over many years, a synthesis of local and regional research findings, dialogue among emerging and established leaders, a scenario-planning workshop, and the deliberation of a cross-sectoral leadership group. The launch of this civic agenda reflected a shift in the work of the project from simply tracking change within and across sectors to driving it prospectively by reporting progress on a shorter list of identified long-tem goals.

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In 2006, the project is offering a highly interactive online regional data repository in collaboration with its partner the Metropolitan Area Planning Council, a quasi-public agency that provides planning, technical assistance, and data to Greater Boston’s 101 cities and towns. A virtual data warehouse made possible through shared protocols and new “middleware” designed by the Department of Urban Studies and Planning at the Massachusetts Institute of Technology (MIT), the repository offers online access to large datasets in a GIS format and through a OCG-compliant product, ensuring eventual transition to open-source products. In the works for a decade, this new tool allows participants and visitors access to a vast array of data that can be mapped, charted, or used to develop their own indicators system. The Boston Indicators Project has been recognized for its commitment to civic engagement, for the comprehensiveness of its indicators framework, and for its efforts to provide both fine-grained neighborhood and metropolitan-scale data. Its website received the International Tech Museum/Knight Ridder Equality Award in 2003 as one of 25 projects selected for “using technology to benefit humanity” from among 500 candidates in 70 countries. The project was also acknowledged for its accomplishments as a model local and regional indicators system by the Government Accountability Office (GAO), the research arm of Congress. It was a founding member of the National Neighborhood Indicators Partnership (NNIP) at the Urban Institute and the Community Indicators Consortium (CIC).

A Comprehensive Framework The Boston Indicators Project tracks change and progress in ten sectors through approximately 70 indicator goals and 150 measures that emerged through the deliberation of project participants over several years. This framework includes both conventional categories such as “education” and “public health,” for which administrative data are regularly collected at the local, state, and national levels, and other sectors that are idiosyncratic to the Boston Indicators Project, such as “civic health” and “cultural life and the arts.” The resulting framework is unusually comprehensive and succeeds in organizing and tracking the issues of concern to project participants.

Ten Sectors ● ● ● ● ● ● ● ● ● ●

Civic health Cultural life and the arts Economy Education and lifelong earning Environment Housing Public health Public safety Technology Transportation

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Cross-Cut Filters: A Systemic View The project’s sector-specific framework is augmented by a Web-based “cross-cut filter” feature that pulls measures from each sector to support an additional set of cross-sectoral categories: ● ● ● ● ● ●

Boston neighborhoods Children and youth Race and ethnicity Sustainable development Competitive edge Fiscal health (in development)

This mechanism encourages users to think about data holistically, expressing linkages across sectors and a more systemic approach to key trends and challenges. Each “cross-cut filter” category, like each sector, has its own home page, with appropriate links to data, research, and ways to get involved.

Sector Home Pages Each of the sectors tracked by the project has its own home page on the project’s website focusing on items of special interest and late-breaking news. Each home page also contains the following standard features: ●

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Sectors highlights. An extensive overview essay that includes the results of convenings about what stakeholders and experts across the sector have identified as key trends, recent accomplishments, and remaining challenges. At-a-glance indicator goals and measures. A one-page overview of indicators in the sector, with live links to each goal and measure, and access to the data tables behind charts and graphs for downloading as desired. Research. Sector-specific annotated compilations of recent research and reports by research institutes and local, regional, state, and, if relevant, national agencies, as well as an archive of research to facilitate retrieval. Innovation. A link to this feature of the website offers examples of breakthrough work in the sector at the local, regional, national, and international levels (see detailed description, following: “Hub of Innovation”). Links and resources. A feature that links users to data- and information-rich websites at the local, regional, statewide, national, and international levels by sector, as well as to the websites of local organizations offering opportunities to engage more deeply in the work of each sector.

Special Web-Based Features In addition to the features available by the sector described above, the Boston Indicators Project website contains features that reflect its commitment to broadening participation, simplifying the use of data and information, and stimulating new thinking about Greater Boston’s key challenges and opportunities:

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At-a-glance geography. Statistical profiles of census, housing, health, and other data presented for the Greater Boston region, the region’s inner core communities, the City of Boston, and Boston’s 16 neighborhood planning districts. Boston: Hub of Innovation. A new feature that highlights local, regional, national, and international breakthrough technologies and practices in the ten sectors tracked by the project, with an online survey tool to gather nominations for additional innovations by sector. Greater Boston data portal. A new feature that “opens a door” to comprehensive, data-rich websites and web-based tools offering access to high-quality information about Boston, the region and Massachusetts. The Greater Boston cultural resources survey. A new online survey tool developed in partnership with the Mayor’s Office of New Bostonians to document and share the wealth of cultural resources generated by members of each of more than 100 ethnicities as they make their presence felt in the cultural and civic landscape of Greater Boston. This is a way to gather qualitative data to support the cultural life and the arts indicator goal of “vibrant expressions of cultural diversity.” What’s Next? seminars. A website features that presents the programs, notes, pictures, and other informations about quarterly seminars designed by the project and its advisory committee of emerging leaders to create an active intergenerational network of emerging and established leaders. The seminars are often organized in a “fishbowl” format to encourage dialogue, and increasingly focus on how best to move the needle on the elements of a shared civic agenda. An emerging civic agenda. The 2004 report, for the first time, included an “emerging civic agenda” that reflects the ideas and aspirations of thousands of participants over the life of the project as well as a confluence of recent research findings. The civic agenda is described as having four parts: (1) analysis; (2) agreement; (3) alignment; and (4) action. The indicators project has asserted, based on its own convenings and the remarkable confluence of findings by researchers from all sectors in Greater Boston, that most Greater Bostonians have reached the point of agreement on our greatest challenges and opportunities. The “emerging civic agenda” set forth in the report captures this agreement in four “buckets,” each with measurable goals: ● ● ● ●

A dynamic and open civic culture World class human resources 21st century jobs and economic strategies 21st century infrastructure.

The project is now engaged in moving this agenda forward by seeking to identify and encourage action on high-leverage points of intervention that cut across these major areas. Future indicators reports, in addition to tracking change in ten sectors, will highlight progress in these broad areas by tracking milestones identified by project participants.

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A Two-Pronged Approach: Data and Dialogue The Boston Indicators Project, then, operates on two distinct but related tracks: (1) a data track and (2) a deliberative track. While functionally distinct, they each play a greater or lesser role during various phases and demands within the project’s 2-year cycle leading up to and following the release of a biennial report. Both tracks are expressed in the project’s work on a continual basis, as well as in the design of its website (Figure 1). The Project’s biennial summary reports draw from and express both tracks. On the one hand, data analysis and recent research findings update the indictors report. On the other, a summary report highlights key issues drawn from sector convenings and other forms of civic deliberation to “tell a story” to a broad audience. This thematic “story” uses data from the updated indicators report, reaching across sector silos and highly bounded geographies to connect the statistical dots in ways that the broad public as well as the media can grasp as worthy of their attention. Increasingly, the two “sides” of this process are linked, so that statistical analyses can inform the sector convenings and the convenings can, in turn, inform the interpretation of data and the framing of findings. For example, a series of sector convenings are designed to tap the knowledge of stakeholders and experts within each of the ten sectors tracked. Overlapping the convenings, the project also focuses intensely on data collection, analysis, updates, and interpretation a period of about 6 months prior to the release of the next biennial online and hard-copy summary

Civic agenda civic leadership, deliberation, and action on a high-leverage civic agenda

2002

2004

2006

Benchmarks aligned to vision for 2030

1997

2000

Project launch

First report

Identifying indicators framework

The wisdom of our choices

2002

2004

2006

Indicators data and reports …updated Web site, report every 2 years to measure progress toward a vision for 2030 ...deepening data, creating tools for access to data, training and education

Fig. 1. Project structure: a long time frame, two tracks.

2030

Longterm vision

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indicators report. Likewise, the release of each biennial report at a major civic convening is in turn followed by briefings of key constituencies and smaller civic convenings to allow for deeper deliberation and discourse about key findings.

Deliberation, Dialogue, and a Civic Agenda The project’s regular “menu” of offerings to encourage deliberative dialogue and a dense network of relationships includes: ●

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Sector convenings to frame its key biennial findings. The project taps the knowledge of each sector by convening stakeholders, experts, and leaders in a “diagonal cut” in which participants explore what they see as key trends and short-term changes, recent accomplishments, and remaining challenges. These biennial convenings by sector also foster shared understanding across sectors, and help identify long-term goals and high-leverage strategies as part of a broad civic agenda against which progress can then be tracked What’s Next? Seminars, focusing on aspects of the emerging civic agenda in a “fishbowl” format to encourage real dialogue among an informed and engaged intergenerational network of emerging and established leaders Biennial report release at a major civic event, the venerable Boston College Citizen Seminar, to highlight the findings of the biennial report and reinvigorate participants’ interest and engagement, complemented by a media and communications strategy Leadership group deliberation by 40 cross-sectoral members representing a range of key constituencies to guide the project’s direction and conclusions Related forums and public discourse such as the “Understanding Boston” research series sponsored by the Boston Foundation, with a report and special convening to issue findings on particular topics, as well as links to research conducted and issued by the many excellent public agencies, academic research centers, and independent think tanks in Greater Boston Occasional special events, often in collaboration with partners or key constituencies, such as a series of conversations among civic and business leaders organized in cooperation with the Federal Reserve Bank of Boston.

In all of these ways, the project seeks to tap the tremendous store of knowledge, wisdom, and problem-solving capacity in Greater Boston, while the indicators become a kind of civic common ground.

The Data Track The project draws data from the wealth of high-quality information and research generated by the region’s many academic institutions, public agencies, civic institutions, think tanks, and community-based organizations. In addition to its biennial report, the project’s website includes posting of new research by sector, regular updates, and upgrades to the online version of the report.

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Nested Geography One organizing principle of the Boston Indicators system is geographic, with the goal of organizing data within a “nesting” geographic framework—from the subneighborhood, neighborhood, citywide, metropolitan, regional, statewide, national, and in a few cases, even global levels. For example, each sector’s framework of indicators begins with a goal and measure that reference a regional perspective, such as, in the economy sector, comparative competitiveness measures at the state level. This “nesting” approach to data and measurement will be greatly advanced with the launch of a regional data repository developed as a partnership between the Boston Indicators Project and the Metropolitan Area Planning Council, Greater Boston’s planning agency (Figure 2). The project uses data primarily from city, state, regional, and federal government sources, as well as from nonprofit organizations, universities, and newspapers (see Figure 3). The geographic level of the indicators data varies. About 40% of the indicators are reported for the City of Boston only, and another 10% are reported for the city in combination with a larger jurisdiction (see Figure 4). Another 10% of indicators are reported for neighborhoods within the City of Boston. Nearly a fifth of the indicators are reported at the regional level; this could be either the Boston primary metropolitan statistical area or the slightly smaller region of the eastern Massachusetts council of governments. Another 18% of indicators are reported at the state level only, in some cases because these were the only data available.

• Clarify patterns and put conditions in context • Clarify appropriate geopolitical “ground” for action • Reflect real world thinking and action: people’s multiple communities of interest

l ica ys Ph n latio Popu teristics c a r a ch

s tic ris e t ac ar ch

Subneighborhood Neighborhood Sub-region Regional State(s) New England National Global

Fig. 2. Nesting indicators.

Geog raph y

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Newspaper 3% University 3% Regional 7%

City 21% Federal 13%

State 18%

U.S. census 14% Nonprofit 17%

Fig. 3. Distribution of data sources by type for the Boston Indicators Report.

Indicator Goals and Measures Each sector has between six and eleven indicator goals, each of which has a “home page” describing the reasons for its selection and its importance. Progress on each goal is measured by one to four measures, each with its own page of explanatory text, data, and associated graphics. U.S. 1%

Other 2%

City and State 4% City and region 6%

Neighborhood 10%

City 40%

State 18%

Region 19%

Fig. 4. Geographic level of data reported in the Boston Indicators Report.

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For example, one of the six goals in the transportation sector is “environmentally sustainable transportation,” and one of the three indicator measures within this goal is “car ownership and vehicle miles traveled.” Data for this measure include “motor vehicle registrations,” “distribution of households by car ownership,” and “vehicle miles traveled by roadway type.” For each data item within the indicator measures, there is a table or chart that can be enlarged (an example is shown in Figure 5). Clicking the “view data on screen” button shows the numbers used to create the chart, along with the metadata describing the source and other attributes of the data, and sometimes more data not included in the chart (see Table 1). This information can also be downloaded to a spreadsheet for manipulation as desired. A complete list of all indicator goals, indicator measures, and data items for the transportation sector is shown in Table 2. This table also shows the name of the data source, the type of data source, the scale of the data (city, regional, state, etc.), the display type, the dates reported, and the availability (annual or otherwise). A complete list of all indicator goals, indicator measures, and data items for one of the ten sectors tracked, for example transportation, in Table 2, shows the name of the data source, the type of data source, the geographic scale of the data (city, regional, state, or region), the display type, the dates reported, and the availability (annual or otherwise). In addition to the framework of indicators organized by sector, the project’s data track includes Web-based features and special activities.

Motor vehicle registrations, City of Boston and Boston Region: 1987−2003 Boston Region City of Boston 140

Index (1987=100)

130 120 110 100 90 80 1987

1989

1991

1993

1995

1997

1999

2001

Source: Massacjisetts Registry of Motor Vehicles. Fig. 5. Example of an indicator data item in the transportation sector.

2003

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Table 1. Example of data and metadata behind indicator chart. Measure

10.4.1.a

Title

Motor vehicle registrations, City of Boston and Boston Region: 1987–2003 Division of Local Services

Published by Document Source URL Data source 1 Data source 2 Geography1 Geography2 Start date End date Period By Note 1 Note 2 Keywords Cross reference

http://www.dls.state.ma.us/mdmstuf/socio.htm Registry of Motor Vehicles City of Boston MAPC Region 1987 2003 Annual City Data not available for 1989 (n/a) Motor vehicle, car Index

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Boston

MAPC

City of Boston

Boston region

258,171 265,469 N/a 258,896 249,085 241,702 241,033 247,336 244,405 275,589 287,632 303,326 318,598 332,038 343,518 346,126 336,975

1,891,001 1,916,435 N/a 1,906,248 1,864,022 1,861,607 1,878,500 1,927,985 1,925,259 2,077,820 2,158,444 2,207,747 2,292,119 2,332,632 2,372,546 2,416,851 2,284,888

100 103 N/a 100 96 94 93 96 95 107 111 117 123 129 133 134 131

100 101 N/a 101 99 98 99 102 102 110 114 117 121 123 125 128 121

Geography-at-a-Glance A Geography-at-a-Glance section of the website presents a statistical profile of the metropolitan region, the inner urban core communities surrounding Boston, the City of Boston, and Boston’s 16 neighborhood planning districts. Data are drawn from the project’s partners, the Metropolitan Areas Planning Council and the

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Table 2. Indicator goals, indicator measures, and data items for the transportation sector. Indicator measure

Data item

Source type

Scale

Dates

Display

Transportation that enhances national and global competitiveness

Metro Boston’s global and national transportation capacity Household income spent on transportation: Boston vs. comparable regions

Logan airport annual passengers Average household transportation expenses Ranking of household transportation expenses Trips from Boston

State

Region

1980–2004

Line chart

Federal

Region

1986–2003

Line chart

Federal

Region

2002–2003

Table

Region

City

2000

Region

City and 2000 region Region 1991–2004 City 2000

Map and pie chart Map and pie chart Line chart Map

Region

2000

Map

City

2000

Bar chart

Region

2001

Bar chart

An integrated regional system

Equitable and high-quality transportation access for all

Distribution of daily trips, Boston and Metro Boston

Trends in rapid-transit ridership Residents within a 10-minute walk or short drive from transit nodes by race, income, age group, and transit dependency

Convenience of service to bus riders

Trips to Boston from the region MBTA annual ridership Average commute time

Region U.S. Census

MBTA commuter rail Region and rapid transit stations with a 1/4 mile buffer Percentage of the U.S. Census population estimated within 1/4 mile of rail transit by race/ethnicity MBTA bus shelter locations Region compared to routes

CHARLOTTE KAHN

Indicator goal

Environmentally sustainable transportation

Car ownership and vehicle miles traveled, Boston and Metro Boston

Use of low-emission vehicles Options that enhance civic and community life

Miles of bike and pedestrian ways, people walking and biking to work

Traffic and parking volume in Boston Hours spent stuck in traffic Adequate public funding

Transportation funding by mode

Motor vehicle sales by emission controls Existing and proposed off-road bike paths Share of workers bicycling to work Share of workers walking to work Average weekday highway traffic volume Annual per capita delay hours MBTA expenses by type

Region

State

City and 1987–2003 region

Line chart

U.S. Census

City and 1990 and region 2000

Bar chart

Federal

Region

1982–2002

Line chart

State

State

Bar chart

State

State

State

Region

1990 and 2000 MY1996MY2003 2000

U.S. Census

Federal

City and 1990 and region 2000 City and 1990 and region 2000 City 1977, 1987, 1992, and 1999 Region 1982–2002

Region

Region

Region

Region

State

State

U.S. Census Region

2004

FY1991– 2005 FY1991– 2005 2004

Line chart Map Bar chart Bar chart Bar chart

Line chart Line chart Line chart Pie

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MBTA revenues by source Massachusetts transportation expenditures by agency

Region

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Vehicular greenhouse gas emissions

On-time performance of MBTA bus routes Motor vehicle registrations, City of Boston and Boston region Distribution of households by car ownership Vehicle miles traveled by roadway type CO2 emissions by source

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Boston Redevelopment Authority, with live links as appropriate to other sources of high-quality data at each level.

Data Portal Finally, the Boston Indicators Project and website serves as a portal to relevant research from public agencies, academic institutions, and independent think tanks, as well as linking to other data-rich websites and to organizations that offer ways to get more deeply involved. In other words, the project underscores its role as both a “one-stop shop” and portal.

Online Data and GIS The Boston Indicators Project’s website will be significantly enhanced with the release of an online data system and GIS tool developed in collaboration with its partner the Metropolitan Area Planning Council, a quasi-public agency providing planning, technical assistance, and access to data for the region. It will cover 101 cities and towns in Eastern Massachusetts. A hybrid of a conventional and “virtual” data warehouse made possible through “off-the-shelf ” software, shared protocols, and new “middleware” designed by the Department of Urban Studies and Planning at MIT, the data warehouse will offer online access to large datasets in a GIS format through the partnership. Automated features will allow the public, municipalities, and other government agencies to view searchable data about the metropolitan region, with a deeper view of Boston and its neighborhoods. The data repository will also allow organizations to create tailored websites, adding their own data and information for viewing on the Internet. A fully OCG-compliant approach will ensure eventual transition to open-source solutions.

Training Working with a team from the Emerging Leaders Program at the University of Massachusetts-Boston’s Center for Collaborative Leadership, the project has developed a workshop for use in briefings and training sessions. The project also works with colleagues in the Boston Foundation’s Communications Department to offer an annual curriculum to media professionals. Following launch of the regional data repository, the project will codevelop training workshops with its partner the Metropolitan Area Planning Council.

A Biennial “Data Day” Capacity-Building Conference Since 1997, in partnership with the Metropolitan Area Planning Council and Northeastern University, the project has cosponsored “Data Day: Using Data to Drive Community Change,” at Northeastern University. Organized in both plenary sessions and tracks—novice, intermediate, and advanced—the conference allows

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all participants to move forward in their use of data and information, to share their experience and examples of recent work and accomplishments, and to advance the field. The conference generally attracts about 200 participants from Boston’s nonprofit sector, academia, public agencies, and, increasingly, from out of state.

The Evolution of the Boston Indicators Project: Mostly Intelligent Design The Boston Indicators Project was initiated in 1996 by Catny Douglas Stone, Chief of Environmental Affairs for the City of Boston, Geeta Pradhan, Director of Sustainable Boston for the City of Boston, and Charlotte Kahn of the Boston Foundation as a joint project of the City of Boston and the Boston Foundation. The Boston Foundation had also worked with researchers at Northeastern University, the Metropolitan Area Planning Council, and others since the early 1990s to “democratize access to data” through the development of a data warehouse of administrative data about Boston and its neighborhoods. Refined throughout the 1990s, with the first data release in 1994, the Children and Families Database, as it was dubbed, was a purely statistical data warehouse of administrative data geo-coded to census geography. A breakthrough of collaboration and data integration in its time, it had, however, proven difficult to use for anyone but trained researchers and highly skilled community-based staff and residents. Its often deficit-oriented administrative data had also proven to be insufficient to answer fundamental and often qualitative questions posed by residents and policymakers about how Boston, its neighborhoods, and the region were really doing. The Boston Indicators Project, then, was born of the desire to respond to a set of still-unmet needs: ●

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The diminishing accuracy of census data through an unfolding decade (a limitation somewhat offset today by the Census Bureau’s annual American Community Survey) The lack of consistent access to high-quality data and information on the part of residents and people working at the community level in a comprehensible and easy-to-use format The difficulty in making programmatic and policy linkages across sectors, and in seeing patterns within and across sectors, even though large societal goals such as “justice” and “sustainability” often require analysis and action in the “hybrid” spaces between disciplines, with few tools to promote cross-sectoral analysis, planning, and decision-making The great distance between irrefutable academic research findings and their application in community-based settings The lack, in Boston, of opportunities for informed, sustained civic discourse of the quality that could lead to shifts in shared understanding and to a broadly supported civic agenda

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The first meeting of the Boston Indicators Project included a dozen people, most of whom represented comprehensive community-building initiatives who were being challenged to create new measures to document their work. The project quickly snowballed. This first cohort of participants quickly expanded to include city, state, and federal agency staff eager to share data-driven approaches to public policy, to residents seeking to measure the quality of neighborhood life, to environmentalists challenged to introduce the concept of sustainability into economic and social indicator systems, and to parents and educators seeking a better handle on school and student performance. Within 6 months, the number of participants had grown to 75, and included people from diverse sectors, neighborhoods, community-based organizations, racial/ethnic groups, and levels of government, from the City of Boston to the regional offices of federal agencies such as the US Department of Housing and Urban Development and the US Environmental Protection Agency (EPA). To break the group down into manageable working groups, participants were asked to count off and reassemble by number, forcing everyone to become a Bostonian first and an expert, advocate, or resident of a particular neighborhood second. Later, small working groups were reassembled by the topic of interest and expertise. In all, it took 2 years of large and small meetings to arrive at the ten sectors and “asset-oriented” framework of broad goals tracked by measures of progress that form the basic architecture of the Boston Indicators Project, to reach agreement (more or less) on specific goals and measures, and to assess the availability of data to support most of the desired measures. At one point, participants generated a “wish list” of more than 1500 desirable indicators through whole-group brainstorming and small-group deliberation. Project staff, in consultation with experts and “data crunchers,” then worked over a period of months to narrow the list based on actual data availability, with expert opinion driving many of the final choices. However, some “wish list” entries, deemed highly desirable by many, remained in the final framework even though reliable data—even today—are “not yet available.” By the end of the 2-year process, in 1999, the framework had been reduced to about broad 75 goals, with one to three measures of progress on those goals in ten sectors. By then, more than 300 Greater Bostonians had participated. The Boston Indicators Project released a draft report at a major civic event, a Boston College Citizen Seminar, with about 250 participants, and gradually the draft to an additional 750 residents, agency staff, academics, and civic and community leaders. This kicked off a year of review of comment on the indicators framework, with its proposed goals and measures, during which time the staff made changes in response to comments, completed the cultural life and the arts sector (the only one that had not been ready for inclusion in the first draft), and gathered additional data. Suggestions were incorporated, charts and maps reworked, and data gathered and updated as feasible. Finally, in the fall of 2000, the project released the first complete Boston Indicators Report. Since then, many more participants have helped refine the original set of goals and measures, and to find and format relevant data.

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The 2000 report, The Wisdom Our Choices: Indicators of Progress, Change, and Sustainability, was released as a 300-page report in ten sectors at a Boston College Citizens Seminar, with a keynote address by Boston’s Mayor Thomas M. Menino. This report stands as the baseline for future reports, yet it was an unusual time in Boston, with a booming high-tech economy that had spawned very low unemployment and office vacancy rates as well as Greater Boston’s rising importance in the national and global economies. The report also highlights a widening income gap between the well-educated beneficiaries of the high-tech boom and less well–educated Bostonians, who are shown to be falling behind. The 2002 report, Creativity and Innovation: A Bridge to the Future, was released as both a summary report and an interactive website at a wellattended Boston College Citizen Seminar at which Tim Berners-Lee, inventor of the World Wide Web, delivered the keynote address. The summary report documents a period of economic contraction following the high-tech bust. It describes the city’s competitive advantage as a three-legged stool: a strong institutional and physical infrastructure; a culture and practice of innovation; and a well-educated, skilled, and diverse workforce. While the first two legs are seen to be holding firm, the third had weakened in comparison to competitor regions, with a decline in the number of 20–34-year-olds in Boston, Metro Boston, and Massachusetts relative to other regions. The report concludes with statistical factors drawn from the comprehensive indicators report influencing the stay/go decisions of young people in the city and the region. The 2004 report, Thinking Globally/Acting Locally: A Regional Wake-Up Call, released as both a summary report and a website, highlights a remarkable 2-year period of city building and civic accomplishment. It then moves to a discussion of the effects on the city and the region of the fast-changing, post-high-tech-boom global economy. The summary report documents increasing external competition from other regions of the U.S. and abroad as well as internal challenges, drawing on such indicators as continuing income inequality, educational disparities, and a high cost of living driven largely by housing costs. Released at a major civic event celebrating the 50th anniversary of the Boston College Citizens Seminar attended by a cross-section of business, government, community and civic leaders, the report includes an “emerging civic agenda” to address these challenges.

The project continues to convene stakeholders and experts by sector every 2 years to refine the original indicators framework, to identify the “overview and highlights” sections in each of the ten sectors, and to develop a constituency, including emerging and established leaders, to refine and track progress a shared civic agenda.

Core Principles and Lessons Learned An Asset Orientation Early on, participants agreed to use an asset-oriented framework to encourage users of the system to work toward progress on attaining explicit high-leverage goals and increasing assets (such as “third graders reading at the third grade

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level”; “swimmable days in Boston Harbor”; “a diverse economy”). This was a reaction to the measurement frameworks then in use to describe most urban communities, most of which included measures of unemployment, school dropouts, teen pregnancy, substance abuse, and crime. Worse, there was no apparent way in these deficit-oriented frameworks to acknowledge a community’s unique strengths or assets. Even a community doing fairly well would be painted in negative tones (“juvenile crime was reduced from x to y”), and the impetus to community improvement would be described as a reduction in deficits, which for individuals and communities is not an inspiring or empowering goal, as is made abundantly clear in the work of John McKnight of Northwestern University. The Boston Indicators Project framework is designed to express and stimulate action on attaining valued community goals. For example, in public health, one stated broad goal is “healthy children,” in contrast to a goal-neutral category such as “child heath”. However, progress on this broad goal is measured by standard metrics such as: “adequate prenatal care”; “infant mortality rates” and “birth weight by race”; “chronic preventable disease rates”; and so on. Likewise, in the civic health sector, the goal of “healthy race relations” is measured by progress on “the degree of residential segregation,” “hate crimes,” and “demographic representation of leadership by sector.” In other words, placing standard metrics within a framework of goals serves to remind a community of its own expressed values and about where it is trying to go—making indicators doubly useful.

The Value of Systemic Analysis Even as the first indicators report went off to the printer, project staff realized that they had not been able to “handle”—in the linear format of ten sectors—the important goal of expressing linkages across sectors. They turned to systems thinking for help, working with two graduate students from MIT to better understand systems dynamics, and then to create a series of workshops for participants. They later also worked with a national foundation to cosponsor a scenario-planning workshop for participants, and were able by the next report to use data more effectively to “tell a story” with data. The systemic nature of the Boston Indicators Project is also captured on the project’s website through its “cross-cut filter” feature. In using systems thinking to inform the framework and allow for deeper analysis, staff and participants also learned basic principles that have continued to inform the work of the project: ● ● ● ● ●

Today’s problems come from yesterday’s solutions. The harder you push, the harder the system pushes back. The cure can make the situation worse before it gets better. Cause and effect are not necessarily close together in space or time. There are very few effective, high-leverage policies.

The lessons of systems thinking were put to the test at a Boston College Citizen Seminar, “Metro Boston in the New Global Era” following the events of September 11, with Malcolm Gladwell, author of The Tipping Point, the keynote speaker followed by a panel of “visionaries.” At 35 tables, participants focused on a topic

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selected at prior convenings as being of interest to the event’s 350 participants, and a systems-thinking approach developed by the project was successfully used to generate key trends, identify trend drivers, and develop strategies to affect the trend drivers. These ideas were incorporated into the civic agenda released several years later.

The Power of Both/And Indicators development processes can get mired in trying to decide between two approaches to key issues: Should the system be neighborhood-based, citywide, or regional? Should it be organized by sector-specific categories or cross-cutting fields like “children and families”? Should it be expert-driven or the result of a broadly participatory process? The Boston Indicators Project reflects a strong “both/and” orientation. In addition to ten sectors, its framework includes a set of broad categories (the “crosscut filters” described earlier) such as “sustainable development” that, by their nature, cannot “live” within a particular sector but rather draw from a number of sectors and help to highlight the importance of cross-sectoral thinking, policies, and action. Along with the project’s concept of “nesting indicators” that posits that one cannot understand what is happening on one block without understanding the wider community, the citywide context as well as the regional and national economic contexts, and perhaps the global environmental context as well, this both/and approach highlight linkages, also furthering systemic analysis.

A Commitment to Broad, Diverse, Cross-Cultural Participation Each stage of the Boston Indicators Project, has involved large numbers of participants. To frame and follow up on its biennial findings, the project engages residents, civic, business, and community leaders, government officials, and academics in dialogue about the city and the region’s key challenges and opportunities. Opportunities for dialogue and deliberation are created within and across sectors through small working sessions as well as major civic events. The project works specifically to attract a diverse constituency, and to build an intergenerational network of emerging and established leaders. The working sessions of the Boston Indicators Project are often the only time that a sector comes together across its own myriad fractures and levels to explore long-term trends, recent accomplishments, and key challenges going forward, or to issues across sectors. Yet this is where the most powerful, high-leverage solutions are most often located.

Staffing, Governance, and Funding The Boston Indicators Project is a special initiative of the Boston Foundation as well as a partnership among the Boston Foundation, the Metropolitan Area Planning Council, and the City of Boston. The project director reports to the

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Boston Foundation’s vice president for communications, community relations and public affairs. The staff includes a full-time project director and a research director and a project coordinator for a total three Project staff are responsible for most meeting design, facilitation, and documentation, for coordinating and drawing themes and findings from sector convenings and research, and for writing the summary indicators report, as well upgrading the project’s website through a content management system. Additional capacity includes occasional consultants for website development and design, the design of publications, volunteer facilitators for large or special meetings, and paid and pro bono student interns. The project also benefits significantly from the assistance of researchers and staff at partner organizations such as the Metropolitan Area Planning Council, Boston Redevelopment Authority, Boston Department of Neighborhood Development, Boston Public Health Commission, Massachusetts Public Health Department, Boston School Department, Boston Police Department, and many academic researchers and researchers from community-based organizations. The project is largely funded by the Boston Foundation, with occasional additional grants by local foundations and contracts, and is administratively accountable to the Boston Foundation’s President and Board of Trustees. The project’s budget fluctuates between $300,000 and $450,000 annually, depending on project activities and funding. For example, the year in which a major report is released as an updated website with an accompanying summary report in hard copy is much more expensive than the off year in the project’s biennial cycle. While the project director is directly accountable to the leadership and board of the Boston Foundation, ongoing work is also guided by the cochairs and members of a diverse, cross-sectoral leadership group of about 30 active participants. In addition to the leadership group, core project participants include more than 300 people who developed the initial indicators framework, about 250 stakeholders and experts convened biennially by sector, with cochairs who facilitate the session and review results and findings, and scores of data providers. Approximately 3000 residents, labor, faith-based and business and civic and community leaders have participated in major public forums and release events since the project’s inception, and about 750 people—primarily emerging and established leaders—are invited to quarterly “What’s Next?” seminars to develop and engage an intergenerational network. The project also works with key constituencies such as business, civic, and nonprofit leadership, funders, policymakers, and others to develop indicators and measures in their own work. A growing list of people attend the project’s training workshops and its jointly sponsored biennial Data Day Conference.

CHARLOTTE KAHN, Director, The Boston Indicators Project, The Boston Foundation. [email protected]

Indicators in Action: The Use of Sustainability Indicators in the City of Santa Monica GENEVIEVE BERTONE,1 SHANNON C. PARRY,2 DEAN KUBANI,3 AND JENNIFER WOLCH4 1

Executive Director for Sustainable Works, City of Santa Monica 2 Founder of Sustainable Places 3 Environmental Programs Division, City of Santa Monica 4 Director of the Center for Sustainable Cities, University of Southern California

The City of Santa Monica is a unique coastal community, surrounded by the natural beauty of the Santa Monica Mountains and the intense urban landscape of Los Angeles. Its 85,000 residents are tightly packed into an 8.3 square mile city boundary. The view from its thriving downtown and quiet neighborhoods looks onto coastal beaches that stretch for miles along the scenic Santa Monica Bay. The city has historically maintained a strong relationship to the beach and the ocean. Tourists come from all over the world to visit this eclectic community, relax in the temperate climate, and enjoy the unique venues that the city has to offer. One such venue is the historical Santa Monica Pier. As the oldest pleasure pier on the West coast, it is a Santa Monica icon and defines the city’s western view. The fact that this pier is also home to both the world’s first solar-powered Ferris wheel and the world’s first urban runoff-recycling facility might hint to the observant tourist about one of Santa Monica’s other defining attributes: its deep-seated commitment to sustainability. Since the 1970s, Santa Monica’s residents and political leaders have strongly supported progressive social and environmental initiatives. For decades the community has proactively addressed issues such as affordable housing, has been providing strong support for public arts, cultural programs, and education, and in 1982 developed one of the nation’s first curbside recycling programs. Santa Monica’s commitment to sustainability and the development of the Santa Monica Sustainable City Plan (SCP) grew out of this social and environmental consciousness. In an effort to track the progress of an eclectic and diverse community toward sustainability, the city developed a comprehensive set of indicators. The indicators are not a stand-alone system, but an essential component of the SCP. This chapter traces the history of the SCP, from its inception in the early 1990s to today. By focusing on the SCP’s comprehensive indicator system, this chapter demonstrates how the SCP is performing in practice as a guide to policy and citizen action. This chapter concludes with lessons learned from the Santa Monica experience.

43 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 43–60. © 2006 Springer. Printed in The Netherlands.

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Developing the Sustainable City Program (1994–2000) The city’s Task Force on the Environment (ETF), established in 1991 to advise the city council on environmental programs and policy issues, initially recommended the development of a Sustainable City Program for the city. In order to measure the success of the program and guide city policy, the ETF recommended that the program include a set of sustainability indicators and targets. The ETF first presented the indicators as part of the initial Sustainable City Program proposed in 1992. Recognizing the need to ensure that Santa Monica could continue to meet its current needs—environmental, economic, and social— without compromising the ability of future generations to do the same, the Sustainable City Program was designed to help the community begin to think, plan, and act more sustainably. It was initially developed to provide criteria for evaluating the long-term rather than the short-term impacts of municipal decisions (City of Santa Monica, 2003). In 1994, the Santa Monica city council showed their commitment to addressing sustainability issues in the community by adopting the Santa Monica Sustainable City Program. The 1994 program included goals and strategies for the city government and all sectors of the community to conserve and enhance local resources, safeguard human health and the environment, maintain a healthy and diverse economy, and improve the livability and quality of life (QOL) for all community members in Santa Monica. In order to monitor the city’s progress toward meeting these goals, 16 indicators were developed (later expanded to 18 in 1996) and specific targets were set for the city to achieve by the year 2000 in four goal areas. The four goal areas were: 1. 2. 3. 4.

Resource conservation Transportation Pollution prevention and public health protection Community and economic development

Although the Sustainable City Program addresses environmental, economic, and social sustainability, the program and the indicators primarily focused on the environmental area. In addition, the program was mainly focused on municipal operations and areas that the city government could influence. This was done for two reasons. The ETF recommended that environmental issues be a priority because at that time they were not being addressed in a systematic and comprehensive manner. Furthermore, the city was committed to developing and implementing a successful program. Initially, the city wanted to focus on environmental goals knowing that they would be more likely to succeed in making sufficient changes. For this reason, the scope of the program was kept small and manageable. This would create a culture of success and would inspire decision-makers, city employees, and the community as a whole to support a broader sustainability initiative.

Creating the Sustainable City Plan (2000–2003) After 7 years of implementation, the Santa Monica Sustainable City Program had achieved much success in relation to the original goal areas. Many of the initial

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targets had been met or exceeded, and Santa Monica had become recognized as a worldwide model for sustainability. In reviewing the progress made since the 1994 adoption of the program, the city not only recognized its successes but also identified the need to update and expand the program. The update process began in 2001 with the formation of the Sustainable City Working Group. This group comprised community stakeholders including elected and appointed officials, city staff, and representatives of neighborhood organizations, schools, the business community and other community groups. The working group met numerous times over the course of 15 months to discuss the long-term sustainability of Santa Monica. Based on their findings, the group proposed significant changes to the initial Sustainable City goals and indicators and assisted with the creation of new targets. Early drafts of the proposed update were revised based on the large amounts of public input received during the summer of 2002. The result of the process is the updated Santa Monica SCP that was adopted by the city council in 2003. The updated plan represents the community’s vision of Santa Monica as a sustainable city. The SCP is a much more comprehensive plan than the 1994 Sustainable City Program, giving equal attention and weight to environmental, economic, and social components of sustainability, and focusing on the community as a whole rather than on the municipal operations. The change in name from Sustainable City Program to Sustainable City Plan was made to better reflect the long-term, comprehensive nature of Santa Monica’s vision and the community’s efforts to become a sustainable city.

Elements of the Sustainable City Plan The SCP is a focused, results-oriented strategy designed to achieve measurable improvements in the city’s sustainable practices (Brugmann, 2001). The indicator system is a key component of this comprehensive sustainability initiative. There are five essential elements to the SCP: 1. 2. 3. 4. 5.

Guiding principles Goal areas Goals Indicators Targets

Guiding Principles Nine guiding principles are the foundation of the plan. During the update process, these guiding principles were revised from those initially adopted in 1994 to more accurately reflect the expanded scope of the plan. The 2003 updated guiding principles are: 1. The concept of sustainability guides city policy. 2. Protection, preservation, and restoration of the natural environment is a high priority of the city. 3. Environmental quality, economic health and social equity are mutually dependent.

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4. All decisions have implications on the long-term sustainability of Santa Monica. 5. Community awareness, responsibility, participation, and education are key elements of a sustainable community. 6. Santa Monica recognizes its linkage with the regional, national, and global community. 7. Those sustainability issues most important to the community will be addressed first, and the most cost-effective programs and policies will be selected. 8. The city is committed to procurement decisions, which minimize negative environmental and social impacts. 9. Cross-sector partnerships are necessary to achieve sustainable goals. The guiding principles provide the basis from which effective decisions can be made, and they are the context under which the goal areas and indicators are organized.

Goal Areas The original four goal areas were expanded in the 2003 update to include four additional goal areas. The eight goal areas are: 1. 2. 3. 4. 5. 6. 7. 8.

Resource conservation Environmental and public health Transportation Economic development Open space and land use Housing Community education and civic participation Human dignity

The additional goal areas reflect the city’s commitment to all three aspects of sustainability—environment, economics, and equity. Building off the success of the original program, the city grew the goal areas to include economic development, open space and land use, housing, community education and civic participation, and human dignity. These goal areas acknowledge the need for a broad and comprehensive strategy that goes beyond environmental initiatives to create a truly sustainable city. They reflect complex and interrelated issues and the city is committed to addressing them individually and in relationship to one another.

Goals Within each goal area are specific goals. The goals comprise the core of the community vision and represent what Santa Monica must achieve in order to become a sustainable city. For example, the resource conservation goal area has two stated goals. The goals are: Across all segments of the community: 1. Significantly decrease overall community consumption, specifically the consumption of nonlocal, nonrenewable, nonrecyclable and nonrecycled materials,

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water, and energy and fuels. The city should take a leadership role in encouraging sustainable procurement, extended producer responsibility, and should explore innovative strategies to become a zero-waste city. 2. Within renewable limits, encourage the use of local, nonpolluting, renewable, and recycled resources (water, energy—wind, solar, and geothermal—and material resources).

Indicators For each of the goals, specific indicators have been developed to measure progress toward meeting the goals. The expansion of the SCP goal areas from four to eight and the focus on measuring community sustainability, as well as progress on the municipal front, led to the expansion in the number of indicators from 16 in the original Sustainable City Program to more than 120 in the current plan. Two types of indicators are tracked as part of the SCP. System-level indicators measure the state, condition, or pressures on a community-wide basis for each respective goal area. Program-level indicators measure the performance or effectiveness of specific programs, policies, or actions taken by the city government or other stakeholders in the community.

Targets Specific targets have been created for many of the indicators. The targets represent aggressive yet achievable milestones for the community. Most targets are for the year 2010, using 2000 as a baseline. Numerical targets have not been developed for all the indicators. This was done where development of a numerical target was determined to be infeasible or where limits on data type and/or availability made it difficult to set a numerical target. In many of these cases a trend direction was identified. Examples of a system-level indicator and a program-level indicator in the resource conservation goal area are presented in the following table. The top row identifies the goal area. The left column represents the indicator and the right column represents the target.

System-level indicator Solid-waste generation Indicator

Target

Solid-waste generation

Generation: do not exceed year 2000 levels by 2010 Diversion: increase amount diverted to 70% of total by 2010

●

● ●

Total citywide generation (also report per capita and by sector) Amount landfilled Amount diverted (recycled, composted, etc.) from landfill

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Program-level indicator “Green” construction Indicator

Target

“Green” construction Total number of LEED™-certified buildings in Santa Monica as a percentage of new construction

100% of all buildingsa greater than 10,000 square feet eligible for LEED certification constructed in Santa Monica in the year 2010 shall achieve LEED certification or its equivalent. Of these, 20% should attain LEED Silver, 10% LEED Gold and 2% LEED Platinum certification or equivalent. In addition, 50% of all new, eligible buildingsa less than 10,000 square feet constructed in 2010 shall achieve LEED certification or its equivalent

a

Including all municipal construction.

Indicators, Policy, and Performance Sustainability is a broad concept that resists easy measurement and therefore it is difficult to know when we have accomplished it (Bell and Morse, 1999). SCP includes a comprehensive indicator system that assists in measuring progress, or lack thereof, toward the city’s stated sustainability goals. Unlike other urban indicator systems that arise as independent initiatives without stated targets, links to government or policy objectives, and that are used strictly to raise awareness among the community, the SCP utilizes clearly defined indicators with performance-based targets to measure progress and create a clearer definition of sustainability itself. A general assessment of indicator systems illustrates that the indicators that are tied to performance-based targets are more likely to influence policy, raise public awareness, and communicate the message of sustainability in a responsible way. Additionally, target-based indicators are more likely to direct municipal and citizen behavior towards sustainability. Several factors have been essential in creating and utilizing SCP indicators to guide policy decisions. First, the indicators are goal specific with clear targets that are easy to understand. The indicators were developed to influence and evaluate performance, and therefore are more likely to direct municipal policies and activities. Second, the indicators were developed with input from community stakeholders and maintain strong support from the city council. In addition to creating indicators that are target based and goal oriented, a primary reason for the success of the indicators influencing policy decisions has been their role in a more holistic plan. This enables the city council to see the indicators as part of a larger community vision. The SCP is a planning tool for the future, and the indicators are an essential component. The combination of a supportive city council, good leadership among city staff, and pressure from leaders in the community has made sustainability a priority for the entire city. Examples of how indicators have been utilized to affect city policy can be seen throughout the city. One example of this can be seen in the indicator measuring Big Blue Bus ridership in the transportation goal area. The target for this indicator

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is a 10% annual increase in ridership on local buses by 2000. When the transportation division measured the indicator in 1995, they found that ridership had actually dropped by 7%. When these findings were reported to the city council, they directed the transportation department to develop a plan for improvement. The transportation department solicited feedback from more than 3000 bus riders. They made a variety of changes based on the rider responses. By 1998, Santa Monica had increased bus ridership by 9.5% above the baseline, and by 2000, the ridership target had been exceeded by 7%. This is just one of many examples of indicators and targets influencing policy in Santa Monica. A sample of the SCP’s indicators, targets, and current progress for each goal area illustrates the measurable progress the city is making toward its definition of sustainability. Examples highlighted in the tables below reflect the wide range of indicators that have been created in order to measure progress. Some indicators have successfully met the stated target, some indicators are progressing toward the stated target but have not yet met the target, and some indicators cannot be reported on due to unreliable or unreported data.

Resource conservation Goal: Decrease consumption of non-local, non-renewable, and non-recyclable energy, water, materials and fuels. Reduce waste going to landfills, and promote renewable resource use and sustainable purchasing.

Indicator

Target

Solid-waste generation

Generation: do not exceed year 2000 levels by 2010 Diversion: increase amount diverted to 70% of total by 2010

●

● ●

Total citywide generation (also report per capita and by sector) Amount landfilled Amount diverted (recycled, composted, etc.) from landfill

Current Progress Community-wide waste diversion from landfills in the city increased from 14% in 1990 to 65% in 2002. In the last 10 years, Santa Monica has kept over 1,000,000 tons of solid waste out of the landfill. Unfortunately, community-wide waste generation continues to increase. The city is generating more waste, but a higher percentage of the waste is being diverted. Nationally, waste-diversion rates are approximately 22%. In Santa Monica this number has steadily grown from 15% in 1995 to 60% in 2001. With the steady increases in diversion achieved over the last 10 years, it looks as though Santa Monica is on track to meet the target to divert 70% of the waste stream from the landfills by 2010. This indicator has been successful in monitoring the amount of waste diverted from landfill, but it has also been useful in highlighting information that might have otherwise been ignored. The increase in waste generation is a problem that is not addressed in the SCP. Consumption patterns and consumer choices are perennial problems that are more difficult to influence with local policy.

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Environmental and public health Goal: Minimize/eliminate the use of hazardous and toxic materials and the levels of pollutants entering the air, soil, and water.

Indicator

Target

Wastewater Total citywide generation (also report per capita and by sector)

Reduce wastewater flows 15% below 2000 levels by 2010

Current Progress Wastewater generation decreased by almost 15% in the period between 1990 and 2000. Wastewater levels since 2000 have remained relatively constant. Implementation of aggressive water-conservation programs has been largely responsible for the reductions. Regional drought combined with the need for wastewater-treatment facilities has resulted in programs that link pollution prevention and water conservation throughout the city. However, meeting the wastewater-reduction target for 2010 will require identifying new opportunities for water conservation in the community and innovative ways to reduce wastewater generation in new developments.

Transportation Goal: Reduce traffic and pollution associated with transportation and ensure safe, efficient mobility and access for all.

Indicator Modal Split ● Number of trips by type citywide ●

Average vehicle ridership (AVR) of Santa Monica businesses with more than 50 employees

Target An upward trend in the use of sustainable modes of transportation AVR of 1.5 by 2010 for Santa Monica businesses with more than 50 employees

Current Progress The City of Santa Monica is working to increase the use of sustainable modes of transportation. This includes travel by bus, bike, foot, and rail. Sustainable modes of transportation are important because they can reduce congestion on city streets and contribute to the reduction of vehicle emissions. Data are currently not available to determine the number of trips by type throughout the city, which creates a challenge for attaining the target. However, Santa Monica businesses with 50 employees or more are required to annually file an Employee Trip Reduction Plan. This allows the city to get important data regarding how employees in Santa Monica are getting to work. According to this data, AVR rates for business with more than 50 employees have risen from 1.13 to 1.39 between 1993 and 2003. The city is working steadily toward the AVR target of 1.5.

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The City of Santa Monica is doing well in comparison to the Southern California region. The city’s current AVR is 1.39 compared to the Southern California regional AVR of 1.27.

Economic development Goal: Nurture a diverse, stable local economy that meets the basic needs of all segments of the community.

Indicator

Target

Economic Diversity ● Percentage of total economic activity/output by business sector (expressed as a percentage of total wages)

No single sector shall be greater than 25% of total economic activity/output, and the top three sectors shall not be greater then 50% of the total economic activity/output

Current Progress The economy in Santa Monica is very diverse. In 2002, no single sector of the economy represented more than 25% of the total. The top three economic sectors were professional, science, and technology (19% of total), information (14%), and health care and social assistance (11%). In 2002, the top three sectors of the economy represented only 44% of the total economic activity. This is within the target cap of 50% or less. Sustainable economic development is a challenge. It is difficult to promote economic growth without experiencing increases in waste production and resource usage. In addition to the sectors above, tourism is a strong economic contributor. Currently, the city is researching methods of “greening” the hospitality industry, including market-based, incentive-based, and regulatory methodologies. In an effort to meet the economic development targets, a sustainable economic development strategy for the city is currently being developed.

Open space and land use Goal: Develop and maintain a diverse open-space system and urban environment that supports the community and the natural environment.

Indicator

Target

Park accessibility Percentage of households and population within 1/2 mile and 1/4 mile of park by neighborhood

Upward trend

Current Progress As a measure of the city’s sustainability, access to these parks is essential. Parks provide a variety of resources to the community including rest, recreation, and aesthetic value. There are more than 420 acres of public open space in the City of Santa Monica. Of the total open space, 112 acres are public parks. In 2000, 55% of households were within a quarter mile of a park or open space and 88% were within half a mile of a park or open space.

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Open-space development is a challenge in a built out, compact city like Santa Monica. The city purchased a major lumberyard site in 2004 and is working to acquire more existing properties to be developed into parks and open spaces. In addition, the city is undertaking substantial remodels of open space to make them more accessible and sustainable. The recently remodeled Virginia Avenue Park community center is LEED certified.

Housing Goal: Provide a mix of affordable, livable, and green housing types for people of all socioeconomic, cultural, and household groups.

Indicator

Target

Availability of affordable housing Percentage of new and existing homes in Santa Monica affordable to very low, low, moderate, and upper income families

Target to be developed by city staff in 2005 with the best update of the Housing Element of the General plan

Current Progress In a truly sustainable city, affordable housing is available to households of varying income levels. This requires variety in the housing stock to meet the variety of household income levels in the community. The percentage of new and existing rental housing available to low and very low–income families in Santa Monica fell dramatically in recent years. In 1998, 86% was affordable, and in 2003, only 54% was affordable. In addition to skyrocketing property values in the area, providing affordable housing has become harder since the late 1990s when changes to state rent-control laws resulted in the loss of a significant percentage of the affordable units in the city. Although Santa Monica continues to actively fund and encourage the development of affordable housing, its efforts are increasingly affected by the forces beyond its control. The city has recently completed a 44-unit affordable housing complex in the heart of the city that received a LEED Gold rating. Although this facility addresses only a small fraction of the affordable housing need, it reflects the city’s commitment to integrated solutions to finding and funding affordable housing in the community.

Community education and civic participation Goal: Community members participate actively and effectively in civic affairs and community improvement efforts.

Indicator

Target

Community involvement Percentage of residents who have attended a community event in the last year

Upward trend

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Current Progress A sustainable community is an active and vibrant community. Its residents are engaged and involved, not just in community decision-making and volunteer efforts but also in regular interactions with each other. Most people who are familiar with Santa Monica would surmise that it has a very engaged populace. The community education and civic participation indicators will allow us for the first time to measure this and focus resources to maintain and improve opportunities for engagement. The indicator above measures residential participation in community events. In 2002, 35% of residents reported having participated in a community event in the past year. These events include the Santa Monica Festival, farmers market, pier concert, a Virginia Avenue Park event or other community gatherings. This was the first year of the study, so no trend has been determined, but additional data is expected in late 2005.

Human dignity Goal: All community members are able to meet their needs, have adequate access to housing, health care, education, employment, and are empowered to enhance the quality of their lives.

Indicator

Target

Basic needs—shelter Homeless transition to permanent shelter ● Number of homeless living in Santa Monica ● Percentage of Santa Monica homeless population served by city shelters that transition to permanent housing

No target Upward trend

Current Progress Recognizing that homelessness is a regional problem, the city has joined forces with neighboring governments to find collaborative solutions. Additionally, the city has developed a local, coordinated plan for the delivery of homeless services. Homeless services provided by city-funded organizations focus on long-term stabilization plans that are designed to assist the homeless in transitioning to permanent housing and consistent employment. These services are based on a continuum of care model. The continuum of care model includes outreach, emergency services, intake and assessment, emergency shelter, case management and support services, transitional housing, permanent housing, and aftercare. In 2002, cityfunded shelters served 2566 homeless people. Of those, 244 individuals were transitioned to permanent residences. This represents about 9.5% of those served by city shelters. A complete list of the indicators and additional information about the SCP are available at www.smepd.org.

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How Are Santa Monica’s Indicators Used? After reviewing a sampling of the city’s indicators, one realizes that an indicator is simply a set of rules for gathering and organizing data, so that they can be assigned meaning (Innes, 1990). The core of any indictor is the data, but the presentation of the data is what turns the information into a usable and meaningful indicator that can affect municipal operations, inform public policy, and educate the community. Santa Monica’s SCP indicators were developed with the primary intention of informing the decision-making process of the city’s elected officials, city staff, and key community leaders. A secondary role for the indicators is to inform the public about the myriad issues relating to the sustainability of the community and to inspire personal actions to promote sustainability. These primary and secondary roles have shaped the way the indicators have been reported on so far. Since the Sustainable City Program was initially adopted in 1994, city staff and the ETF have prepared three detailed progress reports—in 1996, 1999, and 2002—which were presented to the city council and released to the public. These reports included indicator data along with detailed analyses of current program and policy activities, obstacles affecting progress toward meeting the various sustainability goals, and recommendations for the future (copies of these reports can be viewed and downloaded at www.smepd.org). As noted above, the reports proved very effective at guiding city policy toward sustainable outcomes. However, preparation of the reports also highlighted one of the drawbacks of the early indicator system. Because the 1994 Sustainable City Program included only 16 (and later 18) indicators, that data taken alone did not provide a very comprehensive picture of progress toward sustainability in the community. Preparation of the progress reports thus became a laborious and time-consuming undertaking, because extensive additional information was needed to complete the picture. Although filled with very useful information, these reports were not very reader friendly. For this reason, very few people other than policymakers ever reviewed the report. With the update of the SCP, a more comprehensive indicator system was developed. The new indicator system is more closely linked to the SCP goals and, taken as a whole, the data from more than 120 indicators present a fuller picture of progress toward sustainability in the community. In order to capitalize on this new indicator system and maximize the usefulness of the data it conveys, the city is working on a new reporting system, using “spider diagrams” to concisely present this data to decision-makers and interested residents alike. The spider diagram allows the city to assess its progress in terms of individual indicators, goal areas, and the system as a whole. This visual depiction allows the complex data and indicator relationships to be presented in a simple and easyto-understand manner. Spider diagrams provide clear representations of complex data and have been developed for each goal area. Additionally, the spider diagram quickly displays where the city is meeting the indicator target and where more work needs to be done. This can be helpful to policymakers when deciding how to best distribute limited resources to address problems.

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Each indicator has been indexed on a scale of 0–100, with 100 meaning the indicator target has been reached and zero meaning no progress has been made toward the target. The outside ring of the diagram represents the target (100) for each indicator. The inner core of the diagram represents the baseline or zero movement. The areas of color on the diagram are areas where the city is progressing toward its stated target. The white areas are the areas where the city is not meeting its target and identifies areas that need to be addressed. In the following example, we can see a portrait of the city’s environmental indicators presented in one spider diagram. The environmental indicators are a subset of the entire indicator set; the spider diagram is capable of displaying the entire indicator set in one graph. In the example diagram, we can quickly see that the waste generation is approaching the target, but that green construction has a long way to go (Figure 1). As seen in the spider diagram, the city has been able to promote sustainable practices in the community and meet many of SCP indicator targets. In 1999, Santa Monica was the first city in the country to purchase 100% green power for all municipal facilities. In addition, the city was able to reduce its greenhouse gas emissions by 6% between 1990 and 2000. As if energy savings are not enough, the city is also a leader in municipal water operations. In 2000, the city completed construction on the Santa Monica urban runoff-recycling facility. This facility reclaims 95% of dry-weather runoff that previously dumped into the Santa Monica Bay, polluting the ocean and causing beach closures and public health risks. Through these efforts and more like them, the city has reduced the size of its ecological footprint by 5.7% since the adoption of the original sustainability plan in 1994. Implementation of the SCP has also lead to the expansion of the city’s community forest as well as increases in the amount of parks and public open space available to the community. There are also challenges to creating a sustainable city and as the spider diagram illustrates, there are many areas of necessary improvement. However, it is important to differentiate the challenges facing a sustainable city in utilizing and maintaining an indicator system from those that arise when implementing a comprehensive sustainability plan.

Indicator challenges The city’s sustainability initiative has relevant and accessible indicators tied to targets that measure progress toward the goals set forth in the plan. The indicators reflect the community’s long-term priorities, are easy to understand, have successfully impacted on policy decisions, and are measurable. However, there are two primary challenges that are specific to the indicator system. One of the biggest challenges for any indicator system is finding reliable and consistent data sources and collection methods. This challenge is especially difficult for a complex and comprehensive indicator system as utilized in the SCP. While some data are derived from reliable city resources such as utility billing or open-space

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Citywide Solid-waste generation Parks accessibility 100.0 Open space

60.0

Water use: total citywide use per day Water use: percentage local vs. imported

40.0 Organic and low-chemical produce sales

Energy use

20.0 0.0

Organic produce: sales at farmers markets Urban runoff reduction: permeable land area in the city Percentage of households using the HHW collection facility Residential household hazardous waste Vehicle miles traveled

Greenhouse gas emission

Ecological footprint for Santa Monica “Green” construction—2004 Santa Monica Bay beach health Wastewater (sewage) generation

Fig. 1. Santa Monica environmental sustainability indicators.

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Food choices: vegetarian meals

80.0

Solid waste diverted from landfill

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databases, much more of it comes from outside sources such as phone surveys or other self-reporting methods which may be less reliable, valid, and consistently available than internal sources. For some indicators, data have yet to be identified. The presence of indicators without data highlights the community’s ability to identify critical areas that cannot yet be accurately measured. Identifying the types of toxic air contaminants released in Santa Monica provides an example of indicators without data. The city is beginning to meet this challenge by conducting a study to identify the sources of toxic air contaminants. It should be noted that the inclusion of this indicator, even without data, has identified an area of necessary improvement. In this way, indicator systems are essential tools in assisting communities and municipalities in identifying their priorities, strengths, and weaknesses. The addition of the new goal areas and respective indicators has created new challenges for the SCP indicator system. As mentioned earlier, the number of indicators increased from approximately 16 indicators in 1994 to over 120 indicators currently. Clearly, this increase in the number of indicators has added a new dimension to the plan and increased the complexity of the system. Developing, identifying, collecting, managing, and reporting on data for this extraordinary number of indicators is proving to be quite a challenge. In order to find the most efficient and effective ways to provide information to the community, new data sources and methods of collecting that data are being sought out on a regular basis. In an effort to address this challenge, the city is developing a coordinated website and report to present the most current indicator data to the community. This information will be available to all community stakeholders and will educate individuals about sustainability in the community. It will also be available to policymakers and community stakeholders who can use it to promote sustainable practices at all levels of decision-making. Thus, indicators are key tools for helping the community make the connection between everyday life and the goals of a sustainable Santa Monica.

Sustainable City Plan Challenges The city’s sustainability initiative is founded on progressive guiding principles, a relevant indicator system, and is representative of community priorities. It is a comprehensive statement of the city’s commitment to sustainability. This commitment has been successfully expressed in a variety of ways. However, execution of the SCP objectives has and continues to face many challenges. Presently, the primary challenges are: (1) increasing community awareness and involvement; (2) better integrating the SCP into the city’s other long-range planning processes; and (3) enlisting key community institutions in working together to achieve the SCP goals. Originally, the SCP primarily targeted municipal operations. Indeed, much of the success of the city’s sustainability initiative could be linked to strong municipal participation. This signified leadership and commitment on the part of the city government and allowed the city to pilot projects and programs on a municipal level that could then be expanded into the greater community. The municipal approach has facilitated great progress in meeting stated targets for a number of

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indicators, but this approach has also created challenges in educating and engaging the community. The Sustainable City Program was essentially developed in a “top-down” process with limited public input. This resulted in the plan having very limited buy-in from the public and key community stakeholders, when it was adopted in 1994. In contrast, community indicator initiatives, such as sustainable Seattle, involve hundreds of volunteers and participants. These participants are not just getting involved, they are becoming educated on what sustainability really means, how it is measured, and how it affects their every-day lives. They take this experience and knowledge into their homes, their schools, and their workplaces and educate others (AtKisson, 1999). Recognizing the limitation of a plan based primarily on municipal operations, the update process that resulted in the adoption of the SCP in 2003 was specifically designed to include greater community input and expand the SCP beyond its original municipal focus. This acknowledged the fact that in order for the plan to be successful, the community needed to be more involved in defining and working to meet the goals. Community awareness and active involvement in addressing the SCP goals remains a challenging area for the implementation of the plan. The city’s environmental programs division has the primary responsibility for community education as it relates to sustainability. The division’s outreach and education strategies include a thorough and educational website, print, and e-news articles, and a strong presence at community festivals and events. The recent SCP 10-year anniversary celebration was a weeklong educational celebration that included walking tours, lectures, free events, and awards ceremonies. At their annual community festival, the city included the Ecological Footprint Campaign that allowed community members to calculate the environmental impacts of their everyday lives. These and other activities have helped the plan gain prominence in the community. A phone survey conducted in January 2005 indicates that 25% of the city’s residents are aware of the SCP (Goodwin Simon Strategic Research, 2005). A previous poll, conducted in 1998, showed that only 12% were aware of the plan at that time. While this is a positive trend, the fact that only one in four residents are aware of the plan highlights that challenges in raising community awareness still exist. In other cities, sustainability advocacy groups have helped educate residents as well as pressure local governments to adopt stronger sustainability programs. Existing advocacy groups in the city are being identified as possible partners to raise community awareness. Another challenge facing the SCP is incorporating the plan objectives into long-range city policy and planning processes. Although the SCP has met with success in implementing programs within municipal operations, it has not been directly linked to city planning processes until recently. According to the 1996 Santa Monica Sustainable City Progress Report, “Despite progress made towards the meeting the various indicator targets, sustainable policies, and programs are still being undertaken in a piecemeal basis within the city (City of Santa Monica, 1996). Coordinated implementation of the sustainability program within the city has not yet been achieved.” A new task force and staff advisory group were recently established to create an implementation plan. This provides unique opportunities for addressing implementation issues.

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The primary challenge, however, which must be overcome if the city is to meet its sustainability goals, is engagement of the community’s institutions and businesses. Although the SCP has resulted in many sustainability gains within municipal operations in Santa Monica, meeting the broader goals for the community will require similar participation and commitment by other key institutions and businesses within the city, including the school district, community college, hospitals, hotels, and other industries.

Looking to the Future Following the update and expansion of the SCP, Santa Monica’s city council appointed an 11-member sustainable city task force (SCTF) to provide community oversight and guide future implementation. The SCTF members were appointed based on their expertise in the various SCP goal areas and their connections in the community. At the same time, a sustainability advisory team (SAT) was created to oversee implementation of the city government’s sustainability efforts. The SAT is a city staff group chaired by a representative from the city manager’s office. The SCTF and SAT are together responsible for developing a comprehensive implementation plan for meeting the sustainable city goals and targets and for coordinating implementation, both interdepartmentally and within community. The development of a Sustainable City Implementation Plan (SCIP) is a new frontier for sustainability initiatives. This illustrates Santa Monica’s commitment to achieving the goals of the SCP, eagerness to involve a variety of stakeholders, and willingness to utilize a variety of innovative strategies. The creation of the SCTF and SAT coincides with the city’s general plan update. Both groups are working to keep the goals of the SCP at the forefront of the general plan update process. This provides a unique opportunity to use the SCP as a tool to further guide policy decisions. Using the SCP indicators and targets as a foundation for the general plan update provides an opportunity for the city to maximize its ability to meet its sustainable city goals. Additionally, it provides a venue to educate the public, not only about the plan but also about the indicators and guiding principles that are the foundation of the plan. Using the indicators, city staff and the SCTF created a preliminary gap analysis of SCP. This provided a general assessment of progress made toward the SCP goals. Based on the findings reported in the gap analysis, the SCTF has identified economic development, environment and public health and resource conservation as priority areas and is now focused on developing tools for making progress toward the respective goals and targets. The SCTF is currently considering a variety of approaches, including market-based, incentive-based, and regulatory methods. Before developing alternative mechanisms to achieve the goals, the SCTF will identify current city efforts and the goal area/indicator to which they are directed. Interestingly, the prioritized goal areas themselves present conflicting interests within the city. For example, the need for economic development can present new issues for the goals set forth in the resource conservation. The city is attempting to create integrated solutions that can address both goal areas

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simultaneously. The indicators will help identify conflicts and ensure that progress in one goal area does come at the cost of another.

Conclusions The Santa Monica SCP maintains a high-functioning indicator set that serves multiple purposes. It represents a community and municipal commitment to sustainable practices. Santa Monica has led the charge to find innovative ways to incorporate sustainability into the community. In a best-case scenario, indicator sets can educate residents, assess existing conditions, guide planning decisions, and focus and evaluate programs (Brugmann, 2001). As evident here, the Santa Monica SCP does each of these. By identifying and facing the challenges, Santa Monica is perpetually seeking ways to advance their understanding of what a sustainable city really looks and acts like.

References AtKisson, A. (1999). Developing indicators of sustainable community: lessons from sustainable Seattle. In Satterhwaite, D. (ed.), The Earthscan Reader in Sustainable Cities. London: Earthscan Publications, Chapter 16, pp. 353–363. Brugmann, J. (2001). Is there method in our measurement? The use of indicators in local sustainable development planning. In Satterhwaite, D. (ed.), The Earthscan Reader in Sustainable Cities. London: Earthscan Publications, Chapter 18, pp. 394–407. City of Santa Monica, Environmental Programs Division. (1996). Santa Monica Sustainable City Progress Report. Santa Monica, CA. Available at http://santa-monica.org/epd/scp/ pdf/SCP_1996_Progress_Report.pdf City of Santa Monica, Environmental Programs Division. (2003). Santa Monica Sustainable City Plan. Santa Monica, CA. Available at http://santa-monica.org/epd/scp/pdf/SCP_ 2003_Adopted_Plan.pdf Innes, J.E. (1990). Knowledge and Public Policy: The Search for Meaningful Indicators, 2nd expanded edition. New Brunswick, NJ: Transaction Publishers. Goodwin Simon Strategic Research. (2005). 2005 Santa Monica Resident Survey. Los Angeles, CA.

GENEVIEVE BERTONE, Executive Director for Sustainable Works, City of Santa Monica, [email protected] SHANNON C. PARRY, Founder of Sustainable Places, [email protected]

DEAN KUBANI, Environmental Programs Division, City of Santa Monica; [email protected]

JENNIFER WOLCH, Director of the Center for Sustainable Cities, University of Southern California; [email protected]

A Measure and Method to Assess Subjective Community Quality of Life M. JOSEPH SIRGY1 AND DON RAHTZ2 1

Professor of Marketing, Virginia Real Estate Research Fellow, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 2 Professor of Marketing, College of William and Mary, Williamsburg, Virginia

Introduction In today’s community, members are influenced by a variety of domains that make up the total community in which they live. Organizations from a variety of cities are trying to monitor the community’s well-being for a variety of domains. In Baltimore, The Enterprise Foundation Initiative uses 40 outcome indicators as “vital signs” of community well-being. These indicators are drawn from a variety of domains such as housing and community development, family health, safety, sanitation, education, and even sense of community (Anonymous, 2005). These factors go far beyond the traditional use of basic economic indicators often touted by community officials when they talk about community quality of life (QOL). Disciplines and businesses alike that have not traditionally examined these more subjective measures in their decisions are now beginning to recognize the importance of such community assessment in decisions regarding development. For example, Poorman (2005) examines a community domain, traffic and transportation, which has grown in importance over recent years. In that piece he calls for a planning strategy built taking into account public expectations that include things beyond simple economic concerns. He notes that planners need to consider such things as community structure, public health, and a variety of QOL domains. Difficulties arise, however, when there is not a theoretically sound framework that can guide public policy decisions regarding the integration, application, and monitoring of these domains. To address such problems in an increasingly complex community environment, Sirgy et al. (2000) have developed a subjective measure of community QOL based on a theoretical model shown in Figure 1. The model makes the distinction between “community” and “other” life domains, both contributing to perceived QOL (global life satisfaction). The community life domain pertains to one’s perception of one’s overall community. In contrast, “other” life domains are those that pertain to noncommunity domains, such as health, work, marriage and family, physical fitness, income, standard of living, neighborhood, among others (e.g., Andrews and Withey, 1976; Campbell et al., 1976). The model treats global satisfaction with community as determinants of global life satisfaction above and beyond the effects of global satisfaction with job, family, leisure, finance, health, education, friends, culture, social status, spiritual life, and home.

61 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 61–74. © 2006 Springer. Printed in The Netherlands.

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Global community satisfaction Global life satisfaction

Global satisfaction with other life domains (e.g., job, family, leisure)

Global business services satisfaction

Sum of individual business service satisfaction (weighted by importance)

Global government services satisfaction

Sum of individual government service satisfaction (weighted by importance)

Global nonprofit services satisfaction

Sum of individual nonprofit service satisfaction (weighted by importance)

Fig. 1. Sirgy et al.’s original model on how satisfaction with individual business, government, and nonprofit services in a community impacts the quality of life (2000).

Global satisfaction with community was hypothesized to be a function of global satisfaction with government, business, and nonprofit services. In turn, global satisfaction with government services was hypothesized to be a function of satisfaction with specific government services perceived to be important. Similarly, global satisfaction with business and nonprofit services were hypothesized to be a function of satisfaction with specific (business and nonprofit) services perceived to be important. The relationship between satisfaction with individual government, business, and nonprofit services and global life satisfaction was explained using the bottomup spillover theory (e.g., Andrews and Withey, 1976; Campbell et al., 1976; Diener, 1984). The basic premise of bottom-up theory is that life satisfaction is functionally related to satisfaction with all of life’s domains and subdomains. Life satisfaction is thought to be on top of an attitude (or satisfaction) hierarchy. Thus, life satisfaction is influenced by satisfaction with life domains (e.g., satisfaction with community, family, work, social life, health, and so on). Satisfaction with a particular life domain (e.g., community satisfaction), in turn, is influenced by lower levels of

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life concerns within that domain (e.g., satisfaction with government, business, and nonprofit services). That is, life satisfaction is mostly determined by the evaluations of individual life concerns. Thus, the greater the life satisfaction with such life domains as community, personal health, work, family, neighborhood, and leisure, the greater is the satisfaction with life in general. Specifically, bottom-up theory of life satisfaction postulates that global life satisfaction is determined by global satisfaction with major life domains, such as community satisfaction, job satisfaction, family satisfaction, personal health satisfaction, neighborhood satisfaction, etc. The effect within a life domain spills over vertically to the most superordinate domain (life in general), thus determining life satisfaction. Similarly, this theory postulates that global satisfaction with a given life domain (community life) is determined by satisfaction with the life conditions/concerns (i.e., government, business, and nonprofit services) making up that domain. In keeping with this perspective, Sirgy et al. argued that the relationship between life satisfaction and satisfaction with specific government, business, and nonprofit services within a given community is a type of bottom-up spillover effect. For example, they hypothesized that there is an indirect relationship between life satisfaction and satisfaction with a specific government service (e.g., police) mediated by global satisfaction with overall government services and overall community as shown in Figure 1. The authors used the logic of multiattribute attitude models (e.g., Fishbein and Ajzen, 1975) in predicting and explaining satisfaction. That is, a resident’s satisfaction with government services in the community, for example, is a direct function of the sum (or average) of the resident’s evaluations of the various and specific government services, moderated by the perceived importance of each service. The same logic was applied to the determinants of global satisfaction with business services and global satisfaction with nonprofit services. Consequently, global satisfaction with community was postulated to be a function of global satisfaction with government services, business services, and nonprofit services. Global satisfaction with government services was hypothesized to be a function of the sum (or average) of satisfaction with individual government services (e.g., police, fire protection, transportation, utilities, recreation facilities, schools), weighted by the perceived importance of each. Similarly, global satisfaction with nonprofit services was hypothesized to be a function of the sum (or average) of satisfaction with individual nonprofit services (e.g., adoption/foster care services, counseling/support services, cultural/recreation services, educational services, legal services, senior citizen services), weighted by the perceived importance of each. Furthermore, global satisfaction with business services was hypothesized to be a function of the sum (or average) of satisfaction with individual business services (e.g., retailers, restaurants, hotels/motels, hospitals and medical care centers, automobile dealerships and repair services, media services), weighted by the perceived importance of each. These hypotheses were empirically tested in a study involving four samples from four communities. The study results supported the hypotheses and thus lent support to the nomological (predictive) validity of the community QOL measures. Although supporting the hypotheses, the

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results of Sirgy et al.’s study suggested that the model may better fit the data if it is modified taking into account the following four insights gleaned from the previous analysis: 1. There is high multicollinearity among other life domain satisfaction constructs (e.g., job, family, leisure). Hence, regressing global life satisfaction against satisfaction with individual life domains produces results indicating that satisfaction with only certain life domains account for significant variability in global life satisfaction scores. A solution around the multicollinearity problem would be to compute a composite index of satisfaction with all other life domains by summing or averaging the satisfaction scores across all other life domains (other than community). 2. Global community satisfaction is predicted not only by satisfaction with business, government, and nonprofit services but also by satisfaction with other life domains. 3. There is high multicollinearity among the three services satisfaction constructs (global business services satisfaction, global government services satisfaction, and global nonprofit services satisfaction), suggesting the possibility of combining these three services satisfaction into one construct, which can be referred to as the “sum of global services satisfaction.” 4. Global community satisfaction predicts the sum of global services satisfaction. That is, there is a reciprocal link between these two constructs. Figure 2 shows the suggested model based on the results of Sirgy et al.’s study. Consistent with the original model (shown in Figure 1), the suggested model (shown in Figure 2) posits that global life satisfaction is a direct function of global community satisfaction and a composite of the sum of satisfaction scores from other life domains. The model also suggests that global community satisfaction is a direct function of the sum of global services satisfaction as well as satisfaction with other life domains. Finally, the sum of global services satisfaction is influenced by composite business services satisfaction, composite government services satisfaction, and composite nonprofit services satisfaction, as well as global community satisfaction. Sirgy and Cornwell (2001) proposed still other improvements to the model based on the theoretical considerations (see Figure 3). These are: 1. Theoretically speaking, they argued that the weighted domain satisfaction scores (as well as the sum of the weighted scores) are likely to add significantly to the predictive variance of global life satisfaction than raw satisfaction scores. In other words, if one obtains measures of residents’ perceived importance of these life domains, then one can adjust the satisfaction score of a given life domain by the perceived importance of that domain. Thus, the weighted satisfaction scores of the various life domains should predict global life satisfaction better than satisfaction scores alone. The logic here is borrowed from the multiattribute attitude models (e.g., Fishbein and Ajzen, 1975). Hence, Sirgy and Cornwell hypothesized that global life satisfaction would be better predicted by global community satisfaction and the sum of

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Sum of individual business service satisfaction (weighted by importance)

Global community satisfaction Global life satisfaction

Sum of global satisfaction with other life domains (e.g., job, family, leisure)

Sum of global services satisfaction

Sum of individual government service satisfaction (weighted by importance)

Sum of individual nonprofit service satisfaction (weighted by importance)

Fig. 2. Sirgy et al.’s suggested model (based on data) on how satisfaction with individual business, government, and nonprofit services in a community impacts the quality of life (2000).

global satisfaction with other life domains (weighted by the perceived importance of each life domain). 2. Global satisfaction with community was also hypothesized to be better predicted by a composite of services satisfaction (sum of the weighted global satisfaction with business, government, and nonprofit services—weighted by the perceived importance of business, government, and nonprofit services in general). Again, the theoretical logic here is borrowed from the multiattribute attitude models (e.g., Fishbein and Ajzen, 1975). 3. It was further hypothesized that global community satisfaction is affected by other factors besides global satisfaction with business, government, and nonprofit services. These other factors are: (1) quality of the environment in the community (air, water, land, etc.); (2) rate of change to the natural landscape (deforestation, housing/commercial development, loss of agricultural land, ridgeline development, etc.); (3) race relations in the community; (4) cost of living in the community; (5) crime in the community; (6) ties with people in

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Sum of individual business service satisfaction (weighted by importance)

Global community satisfaction

Sum of global services satisfaction (weighted by importance)

Global life satisfaction

Sum of global satisfaction with other life domains (weighted by importance)

Sum of global satisfaction with other aspects of the community (weighted by importance)

Sum of individual government service satisfaction (weighted by importance)

Sum of individual nonprofit service satisfaction (weighted by importance)

Fig. 3. Sirgy and Cornwell’s theoretically improved model (2001).

the community; (7) one’s neighborhood; and (8) one’s housing situation. Sirgy and Cornwell suggested these factors from the literature in community psychology (e.g., Bruin and Cook, 1997; Campbell et al., 1976; Dahmann, 1981, 1983; Galster, 1987; Galster and Hesser, 1981; Lansing et al., 1970; Lee and Guest, 1983; Vrbka and Combs, 1993; Yockey, 1976). Hence, they proposed to capture satisfaction with these other aspects of the community by a construct involving the sum of global satisfaction with other aspects of the community (weighted by perceived importance of each aspect). Based on the aforementioned modifications to the model, Sirgy and Cornwell’s new and improved model is shown in its entirety in Figure 3. From this refined model, they tested the following hypotheses: ●

●

Hypothesis 1. Global life satisfaction is a direct function of two factors: (1) global community satisfaction and (2) the sum of global satisfaction with other life domains—weighted by the perceived importance of each life domain. Hypothesis 2. Global community satisfaction is a direct function of three factors: (1) the sum of global satisfaction with government services, business services, and nonprofit services—weighted by the perceived importance of

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these services in relation to other community aspects; (2) the sum of global satisfaction with quality of the environment in the community (air, water, land, etc.), rate of change to the natural landscape (deforestation, housing/commercial development, loss of agricultural land, ridgeline development, etc.), race relations in the community, cost of living in the community, crime in the community, ties with people in the community, one’s neighborhood, and one’s housing situation–weighted by the perceived importance of those community aspects; and (c) the sum of global satisfaction with other life domains–weighted by the perceived importance of each life domain. Hypothesis 3. The sum of global satisfaction with government services, business services, and nonprofit services weighted by the perceived importance of these services in relation to other community aspects is a direct function of four factors: (1) the sum of satisfaction with individual business services (e.g., banking/savings, insurance, restaurants)—weighted by the perceived importance of those business services; (2) the sum of satisfaction with individual government services (e.g., fire, rescue, library)—weighted by the perceived importance of those government services; (3) the sum of satisfaction with individual nonprofit services (e.g., alcohol/drug abuse, crisis intervention, adoption/foster care)—weighted by the perceived importance of those nonprofit services; (4) the sum of global satisfaction with quality of the environment in the community (air, water, land, etc.), rate of change to the natural landscape (deforestation, housing/commercial development, loss of agricultural land, ridgeline development, etc.), race relations in the community, cost of living in the community, crime in the community, ties with people in the community, one’s neighborhood, and one’s housing situation—weighted by the perceived importance of those community aspects; and (5) the sum of global satisfaction with other life domains—weighted by the perceived importance of each life domain.

Using a mail survey sent to households, this new set of hypotheses was tested in a large-scale study involving a number of communities located in western Virginia. The results of the study provided empirical support for additional nomological (predictive) validation of Sirgy et al.’s measures of community QOL. The results showed that community variable did not have a significant predictive effect on services. Therefore, Sirgy and Cornwell (2001) revised the model by eliminating this relationship from the overall model (see Figure 4). The data provided the best good-of-fit with the revised model. A description of the measures is provided in Appendix A.

Policy Implications The system of measures shown here have the advantage of measuring resident satisfaction with their community in a way in which that satisfaction can be examined in the context of its contribution to both community and overall QOL. From a public policy perspective, an annual (or biennial) survey based on our system of measures should be able to provide community leaders with measurement of the level of

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Sum of individual business service satisfaction (weighted by importance)

Global community satisfaction

Sum of global service satisfaction (weighted by importance)

Global life satisfaction

Sum of global satisfaction with other life domains (weighted by importance)

Sum of global satisfaction with other aspects of the community (weighted by importance)

Sum of individual government service satisfaction (weighted by importance)

Sum of individual nonprofit service satisfaction (weighted by importance)

Fig. 4. Sirgy and Cornwell’s final-modified model (2001).

resident satisfaction/dissatisfaction with community-based services (government, nonprofit, and business services). Additionally, a real value exists in being able to assess the impact of this satisfaction/dissatisfaction on the resident’s global community satisfaction (community well-being) and overall life satisfaction (subjective QOL) (see Table 1). As shown in the table, community-based organizations can employ one of the four marketing strategies given in the results of the annual survey. If the results were to point to the fact that their residents are satisfied with a particular service and that this satisfaction is found to produce high impact on their community well-being and subjective QOL, then the marketing strategy should be to reinforce resident satisfaction with that service. This ability to pinpoint areas of value and direct strategies based on that assessment should be highly desirable for all community-based organizations—government, nonprofit, and business organizations. Achieving high levels of resident satisfaction with a particular communitybased service is not only very desirable but also ideal when this satisfaction is found to play a significant role in the residents’ community well-being and subjective QOL (this is the satisfaction/high-impact cell in the table). Community-based organizations or any public agency can use such evidence in the development of various marketing and promotional campaigns. An example is offered below.

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Table 1. Marketing strategies to enhance community and overall QOL.

Satisfaction with a community-based service Dissatisfaction with a community-based service

High Impact on Community Well-Being and Subjective QOL

Low Impact on Community Well-Being and Subjective QOL

Recommended strategy: maintain resident satisfaction and involvement Recommended strategies: (1) decrease resident dissatisfaction while maintaining involvement or (2) convert resident dissatisfaction into satisfaction

Recommended strategy: maintain resident satisfaction but increase involvement Recommended strategies: (1) decrease resident dissatisfaction or (2) convert resident dissatisfaction into satisfaction while increasing involvement

Consider the Santa Monica Mountains Conservancy. This organization has recently won an award for contributing to the well-being of the Southern California community. The organization develops and maintains a Southern California network of urban parks that protect wildlife habitats and “green spaces” that coexist with an ever-expanding suburban/urban sprawl and highway network (Kris, 2005). What does the existence of this green space contribute to the QOL for the community and the community members? In a straight economic assessment of the “value” of the organization, there is little that a public policy official can point to in trying to measure the impact of such urban parks on the community QOL. What is clearly needed is a way in which to “strategically” think about evaluating the impacts of such entities and domains on the community, not only in straight economic terms but also in community QOL. Perhaps, using the example of a particular amusement park and recreation center will shed light on the value of such a strategic tool in both measuring impact and directing strategies to address various situations. Suppose the park finds out that the majority of the residents who visited the park are highly satisfied with the park, and that the park made a significant and positive impact on their lives by enhancing their community well-being and their perception of their QOL. In this case, the management of the park and recreation center selects to maintain its course, i.e., maintains the same level of service. The most problematic is the dissatisfaction/high-impact condition (see Table 1). Here the evidence would suggest that customers are dissatisfied with the community-based service and that dissatisfaction is creating a significant adverse impact on the overall community well-being and subjective QOL. This is most troublesome from a social responsibility point of view. Two alternative strategies are recommended: (1) decrease resident dissatisfaction with that service while maintaining the high level of resident involvement; or (2) convert resident dissatisfaction into satisfaction. The first strategy is probably the most straightforward course of action that can be recommended. Here the community-based organization reconfigures its services and programs in ways to lessen the dissatisfaction.

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Additional research is needed to uncover the various sources of dissatisfaction. Once these sources of dissatisfaction are uncovered, marketing strategy can be formulated to decrease possible future dissatisfaction. For example, the park and recreation center finds out that the majority of their visitors are dissatisfied with the visit, and that the visit created a negative and lasting impression in their leisure life. This negative impression also has caused the visitors to experience a decrease in their overall QOL. The center would engage in research to identify why visitors felt dissatisfied with their visit. Perhaps visitors were dissatisfied because the park was too crowded, the lines were too long, the amenities were too expensive, there was not enough shade to escape the blazing sun, and there were not enough benches to relax. In this case, the park and recreation center would develop strategies designed to address the sources of dissatisfaction. Examples would include building more benches in the park, planting more trees to provide more shade, reducing the price of amenities, etc. The second strategy entails going beyond finding out what the sources of dissatisfaction and addressing those. The strategy would also involve identifying the various sources of satisfaction and implement services and programs that can generate a high level of satisfaction. For example, the park and recreation center would have to go beyond planting more trees to provide shade (therefore reduce customer dissatisfaction). The center has to find out what are the satisfiers, and specifically what are the satisfiers that can create a lasting impact in enhancing one’s community well-being and subjective QOL. Perhaps the satisfiers may be the kind of programs and services that are highly personal. For example, visitors to the park experience a very personal encounter with an expert on wildlife. Adult visitors and their children are allowed to interact with a variety of animals and have an interactive session with the expert. One in which they can gain a wealth of firsthand knowledge about their natural world. This type of program is likely to be both highly satisfying and emotionally involving. With respect to the satisfaction/low-impact condition, here residents do feel somewhat satisfied; but this satisfaction does not seem to spill over to influence their global perceptions of community life and QOL at large. The recommended strategy in this instance is to increase customer involvement with the travel/tourism experience. For example, park and recreation center may find that the majority of its visitors are satisfied with their visit to the park; however, the visit did not seem to have made a significant impact on enhancing the visitors’ community well-being and their overall subjective well-being. What to do in this situation? The park and recreation center may attempt to increase visitor involvement by making many of their programs “personable.” As previously discussed, imagine the following example. Park visitors can have a very personal encounter with the wildlife and the experts in the field. Imagine children being able to act as an assistant to one of the experts in demonstrating animal behavior and the parents of those children being able to shoot video of that activity. This type of program is likely to generate a great deal of emotional involvement with respect to both the kids and their parents. With respect to the dissatisfaction/low-impact condition, here residents feel dissatisfied; and fortunately, this dissatisfaction has not influenced their community life (and overall QOL) in any significant way. Two recommended strategies

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may fit here. The first strategy may involve decreasing resident dissatisfaction while the second is more challenging. The second strategy entails converting resident dissatisfaction into satisfaction while increasing the resident’s involvement with the community-based service in question. For example, a park and recreation center may find out that its visitors may have felt dissatisfied with their visit at large, and fortunately that dissatisfaction has not colored theperception of their community life and overall QOL. To remedy this situation, the center should engage in research to identify the various sources of satisfaction as well as dissatisfaction. The center should also uncover which programs and services tend to produce high levels of emotional involvement. The goal is to implement strategies designed to reduce visitor dissatisfaction, increase satisfaction, and heighten involvement with the park’s programs and services.

Conclusion This chapter reports on the development of a measure and a method to assess community QOL. The method is based on the theoretical notion that community resident satisfaction with individual government services (e.g., police, fire/rescue, and library), business services (e.g., banking/savings, insurance, and department stores), and nonprofit services (e.g., alcohol/drug-abuse services, crisis intervention, and religious services) affects satisfaction with the community at large (global community satisfaction). Ultimately, this global community satisfaction, together with satisfaction with other relevant life domains (work, family, leisure, etc.), affects global life satisfaction. The theoretical notions are explained using bottom-up spillover theory—a theory highly established in QOL research. The predictive validity of these measures was tested in two major studies (Sirgy and Cornwell, 2001; Sirgy et al., 2000) and the data were supportive of the theoretical relationships. From a managerial perspective, it was shown how both community leaders and public policy officials could assess not only the satisfaction with a given government, business, and nonprofit service in the community but also the impact of that satisfaction on the QOL of community residents.

Appendix A: The Measures The refined model (as shown in Figure 3 and articulated through Sirgy and Cornwell’s hypotheses 1 through 3) contained the following satisfaction constructs: ●

●

●

●

Satisfaction with individual government services such as fire, rescue, library, police, and sanitation services Satisfaction with individual business services such as banking/savings, insurance, restaurants/night clubs, and day care services Satisfaction with individual nonprofit services such as alcohol/drug abuse, crisis intervention, adoption/foster care, and family-planning services Satisfaction with community aspects such as government, business, and nonprofit services in general; quality of the environment in the community (air,

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water, land, etc.); the rate of change to the natural landscape (deforestation, housing/commercial development, loss of agricultural land, ridgeline development, etc.); race relations in the community; cost of living in the community; crime in the community; ties with people in the community; one’s neighborhood; and one’s housing situation Satisfaction with life domains such as community, job, family, financial, health, education, friends/associates, leisure, cultural life, social status, spiritual life, and home Satisfaction with life in general

All satisfaction measures were single indicators in which responses were tapped using the Delighted–Terrible Scale: +3 (delighted), +2 (pleased), +1 (mostly satisfied), 0 (mixed feelings), −1 (mostly dissatisfied), −2 (unhappy), and −3 (terrible). Also, respondents were instructed to “circle ‘X’ if ‘you never thought about it,’ or ‘you don’t have an opinion.’ “ For example, global life satisfaction was measured by asking the respondent to answer the following question: “How do you feel about your life as a whole?” The survey questionnaire also contained measures of perceived importance corresponding to all satisfaction constructs (see list above). All perceived importance measures were single indicators in which responses were captured using the following rating scale: 7 (of utmost importance), 6 (very important), 5 (somewhat important), 4 (so/so), 3 (somewhat unimportant), 2 (very unimportant), and 1 (of no importance whatsoever). For example, importance of police services was measured through the following question: “How important or unimportant are police services in your community?”

References Andrews, F.M. and Withey, S.B. (1976). Social Indicators of Well-Being: America’s Perception of Life Quality. New York: Plenum Press. Anonymous (2005). Baltimore-rebuilding neighborhoods locally. Journal of Housing and Community Development, 62(3)(May):26–27. ABI/INFORM Global database (Document ID: 855586201). Bruin, M.J. and Cook, C.C. (1997). Understanding constraints and residential satisfaction among low-income single-parent families. Environment and Behavior, 29(4):532–553. Campbell, A., Converse, P.E., and Rodgers, W.L. (1976). The Quality of American Life: Perspectives, Evaluations, and Satisfactions. New York: Russell Sage Foundation. Dahmann, D.C. (1981). Subjective indicators of neighborhood quality. In Johnston, D.F. (ed.), Measurement of Subjective Phenomena. Washington, DC: U.S. Government Printing Office, pp. 97–118. Dahmann, D.C. (1983). Subjective assessment of neighborhood quality by size of place. Urban Studies, (20):31–45. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95(3):542–575. Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior. Reading, MA: Addison-Wesley. Galster, G. (1987). Homeowners and Neighborhood Reinvestment. Durham, NC: Duke University Press.

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Galster, G. and Hesser, G. (1981). Residential satisfaction: contextual and compositional correlates. Environment and Behavior, 16(November):737–758. Kris, J. (2005). Saving spaces. Planning: APA 2005 Planning Awards, 71(3)(March):14–15. ABI/INFORM Global database (Document ID: 809775001). Lansing, J., Marans, R., and Zehner, R. (1970). Planned Residential Environments. Ann Arbor, MI: Institute for Survey Research, University of Michigan. Lee, B. and Guest, A. (1983). Determinants of neighborhood satisfaction: a metropolitanlevel analysis. Sociological Quarterly, 24(Spring):287–303. Poorman, J.P. (2005). A holistic transportation planning framework for management and operations. Institute of Transportation Engineers. ITE Journal, 75(5):28–32. ABI/INFORM Global database (Document ID: 841849721). Sirgy, M.J. and Cornwell, T. (2001). Further validation of the Sirgy et al.’s measure of community quality of life. Social Indicators Research, 56:125–143. Sirgy, M.J., Rahtz, D., Cicic, M., and Underwood, R. (2000). A method for assessing residents’ satisfaction with community-based services: a quality-of-life perspective. Social Indicators Research, 49:279–316. Vrbka, S.J. and Combs, E.R. (1993). Predictors of neighborhood and community satisfactions in rural communities. Housing and Society, 20(1):41–49. Yockey, K.M. (1976). Residential alterations and additions and housing-neighborhood satisfaction. M.S. thesis. Ames, Iowa: Iowa State University.

M. JOSEPH SIRGY, Professor of Marketing, Virginia Real Estate Research Fellow, Virginia Polytechnic Institute and State University, Blacksburg, Virginia

[email protected] DON RAHTZ, Professor of Marketing, College of William and Mary, Williamsburg, Virginia

[email protected]

Perception and Evaluation of the Quality of Life in Florence, Italy FILOMENA MAGGINO Researcher and Professor of Social Statistics, Università degli Studi di Firenze, Italy

Introduction In 2003, the City of Florence (Italy) in conjunction with the Department of Statistics at the University of Florence conducted research regarding the citizens’ perception and evaluation of the quality of life (QOL) in the city of Florence. The focus of the study was to identify residents’ needs and develop programs and policies to enhance their QOL. The study also attempted to develop specific indicators of QOL aimed at measuring and assessing the levels of suitability of the living conditions that the city of Florence offers to its inhabitants.

The Conceptual Model It was important that the conceptual model for the QOL in Florence described some important aspects directly related to the subjective perception of the QOL in an urban context. That is, such a model had to take into account the specificity and peculiarity of the urban reality. Additionally, the model needed to recognize the uniqueness of Florence, that is, account for the various aspects regarding QOL that make the city of Florence atypical in the context of the Italian city and town environment. The development of the conceptual model that guided this examination of QOL in Florence was, itself, guided with an eye on two different priorities. These were: (1) the individual and (2) the territory. 1. The individual. Following this perspective, the individual objective (sex, age, education, profession, family, house, income) and subjective (attitudes, opinions, evaluations) characteristics represent the really central dimensions of QOL. It is focused on cultural aspects, lifestyles, values, social relations, etc. of the citizens. In this perspective, information concerning individual characteristics is collected with great detail. The physical and social environments are considered as the conditions that are external to the individual, but an environment in which the individual is immersed. This external environment acts as a frame for the study. 2. The territory. In this perspective, the urban territory is considered in terms of space as well as in terms of its efficiency and security. It is where individuals operate, act, interact, move, and organize their life. Following this perspective, information concerning the individual characteristics is collected as a function of the understanding of the territory. The objective (for example,

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time for movements, use of public transportation) and subjective (evaluations for the public services, expectations, and so on) information are collected for each individual regarding connections to the urban reality. The individual is in constant exchange with the urban environment as a dynamic entity. The city transformations involve, and have consequences on, social, cultural, organizational aspects as well as on individual (affective, relationship, ethical, etc.) dimensions. These kinds of transformation are elaborated and assimilated by the individuals as a function of their personal, objective, and subjective characteristics (Bramston et al., 2002; Christakopoulou et al., 2001; Sirgy and Cornwell, 2001; Sirgy et al., 2000). The conceptual model here focused on the urban reality. Specifically, the focus was on investigating the interaction between each individual and the urban environment. This was considered at three different levels: the citizen living in Florence (not living in Florence) is placed in a well-defined spatial and temporal reality, defined in terms of housing space, neighborhood space, and the whole city. Defining, measuring, and interpreting the different citizens’ levels of satisfaction, it was important to take into account that the three realities are successively inclusive. These play a concentric role (in this perspective, the presented approach deals with both community dimensions and subjective dimensions of QOL (Sirgy et al., 2000)). The individual components (objective and subjective) leaving out of consideration the relationship between citizen and urban reality were not investigated.

Measuring the Model’s Components: The Questionnaire Consistent with the conceptual model, the questionnaire was built around two ambits—the relation of the citizen with the city and the citizen’s individual life aspects. The first ambit consists of two aspects that explore the relationship of the individual with the neighborhood area (the first one) and with the whole city (the second one). For each aspect, different areas, variables, and subsequent items were defined. Some variables aimed at the investigation of the satisfaction levels of particular aspects related to the city reality (like the use of public transportation). The definitions of particular variables were built around the exploration of the subjective attitude toward the tourist dimension of the city and the subjective priority related to some environmental problems that cause troubles in urban context. The second ambit was person-centered and is oriented to explore the individual life aspects defined in terms of individual conditions (profession, educational qualification, house, social network supports, and free-time activities), subjective life values, happiness, and financial situation. The individual data (sex, civil status, age, year of registration in the General Register, and number of family components and their relationship with the head of the family) were collected from the City General Register and then connected to the individual questionnaire data. The individual data together with the information related to the profession constitute the basic variables.1 The areas and the variables identified for each ambit are presented respectively in Figures 1 and 2.

1 Citizen and the city (relation with the city)

The neighborhood area

The city (the life in Florence)

Perceptions

Moving

Evaluations (15 aspects) General perception as regards

Definition of urban deterioration At the present

5 years ago

Presence of enviromental problems

The past

The present

Level of agreement for enviromental politics

Perception of social-cultural dimensions

Level of acceptance of the great amount of road works

Image of the city

Presence of relevant social problem

Level of satisfaction

Which mean to go to

The future

Work/school Other places

Level of satisfaction

At the present

Employed time

5 years ago Level of acceptance of tourism At the present

1 year ago

PERCEPTION AND EVALUATION OF THE QUALITY

Opinions and attitudes

The choice

City security

Fig. 1. The relation of the citizen with the city: the first ambit defined in the conceptual model.

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In grey, the variables measured by the composite indicators presented in this chapter.

78

2 Individual life aspects

Individual life conditions

Values

Importance of individual life aspects

Individual data (*)

Educational qualification

Happiness at the present

Adequacy of individual and family income

Level of satisfaction for social relations

Comparison with the past

Satisfaction level

Level

Condition

Financial situation

At the present

The house

Occupation

Satisfaction

External comfort

Distance from 12 important places Social network: support

Received

Offered Free-time activities

(*) Collected from the City General Register

Fig. 2. The individual life aspects: the second ambit defined in the conceptual model.

1 year ago

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Profession

Subjective perceptions

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Sampling Design and the Data Collection The sample was selected by applying a probabilistic stratified design according to the following drawing procedure. The reference population—composed by the Florentine resident citizens that have reached the full age—was stratified according to three characteristics: area of residence (in 1995 the territory of the City of Florence was subdivided in 20 areas exclusively for survey purposes), sex, and age (the defined age-categories were: 18–24, 25–34, 35–44, 45–54, 55–64, 65–74, 75 and above). The total dimension of the sample was set to 1200 units. Initially, organizational reasons suggested to equally arrange/distribute the total sample according to the 20 areas. Subsequently, in order to define the sample numerousness for each of the 280 strata, the sample was proportionally distributed in the 14 strata (2 sexes × 7 age classes). Consequently, the weight for each unit belonging to the hth stratum (h = 1, . . ., 280) was defined, according to the sampling design, as the ratio between the number of the population units of the h stratum and the number of the sample units of the same stratum. In order to manage the nonresponses, a reserve list was identified by drawing, for each unit of the base sample, two units belonging to the same stratum. In some cases, a farther drawing was made necessary to obtain the expected number of units.2 The project was centered around two survey executions. The first execution was run from the end of October to the end of November 2003. Using a structured questionnaire, 1185 individuals were interviewed by a group of trained interviewers, generally at the house of the respondents. An English translation of the Italian submitted instrument can be seen in Appendix A.3 The average length of each interview was 33 minutes (with a range of 15–120 minutes). The validity of the questionnaire was tested in a preceding pilot survey conducted on a small sample. Respondents who, at the end of the first interview, consented to be reinterviewed were involved in the second survey, conducted in October 2004. Among the 1185 involved in the first survey, 694 subjects consented and were reinterviewed after 1 year by a telephone survey (not presented here) managed by the CATI system. The goal of the second survey was to update basic individual information concerning possible change in residence, house, and profession, and to measure possible change in some subjective dimensions concerning city life. As a consequence, a telephone survey was chosen over the more extended and complex personal interview method that was used in the first survey. Average length for this interview was 15 minutes.4 In general, during data collection of both surveys there was a good collaborative attitude shown by all the interviewed citizens. While the selection procedure of the 2004 group did not adhere to a true probabilistic sampling process, the data generated in the collection still offered valuable insights regarding important aspects for comparative analyses (not presented here). 1. Group comparison. Consistency across the entire 2003 sample (n = 1185) and the entire 2004 reinterviewed group (694) was examined in the ex-post analysis. Demographic compositions of both groups statistically demonstrated the comparability of their structures with regard to the sampling variables (age, sex, and residence district).

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2. Individual comparison. This comparison examined data obtained by each individual that has took part in both surveys (n = 694). This kind of comparison, comparable to a panel technique, allowed particular approaches in the analyses of individual change.5

Developing and Using Subjective Indicators of Quality of Life in Florence A number of variables identified and defined in the questionnaire structure and presented in the first questionnaire (2003 survey) were investigated using singleitem measures. Some complex variables, however (marked in grey in Figures 1 and 2), required the definition of a composite model and the collection of several items. These variables are presented below:

• The subjective image of the city. The image that each citizen has for one’s

•

•

•

•

•

•

city is considered related to the level of satisfaction of one’s life in the city (30 items presented in question no. 25 of the questionnaire). The perception of the tourist dimension of the city. The tourism is an important dimension of the city that deeply conditions, positively or negatively, the citizens’ life; in this sense, the level of perception may be related to the level of satisfaction of one’s life in the city (ten items presented in question no. 20 of the questionnaire). The perception of the cultural dimension of the city. The consciousness of the opportunities that the city can give may represent a chance to live the urban life in a satisfying way (four items of question no. 22 of the questionnaire) (Michalos, 2005). The personal safety perception. Feeling secured while walking alone along the roads of the city represents one of the conditions to perceive and live a better quality of city life (six items presented in question no. 18 of the questionnaire). The evaluation of the district. The subjective evaluation of some different aspects of the life in one’s district may represent an efficacious indicator of the perceived conditions, aside from the objective situation of the district (20 items presented in question no. 6 of the questionnaire) (Michalos, 2003; Michalos and Zumbo, 1999). The territorial distribution of the public services. This indicator try to measure the subjective accessibility to some services, defined in terms of time required to go; the perceived time is more important, and not necessarily connected to, the objective distance (12 items presented in question no. 8 of the questionnaire); this subjective indicator may also be useful in planning the territorial organization of services. The irregularity of the time required to cover the daily-route distances. This indicator is connected to the idea that one of the factors that may increase the QOL in a city is the possibility to plan one’s daily movements in a confident and reliable way; the possibility is measured in terms of regularity of time required to cover the daily-route distances (time referred in question no. 10 of the questionnaire).

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The definition of the indicators, as well as of the corresponding items, is the result of extended discussions among city officials and the university research team involved in the project. In some cases, the outcomes represent a real compromise between the positions of the researchers on one side and that of the officials on the other. At the same time, the definition, having taken into account the peculiar characteristics of this city, may make it difficult to compare with other cities. A review of existing literature in the area, however, did not support such a contention. The university researchers and public policy officials who constituted the research group shared the common aim to obtain a group of complex, yet informative, indicators that, when taken together with the other simple indicators, provided a clear picture of the measured aspects. Additionally, these indicators needed to allow for the observation and the interpretation of each analyzed ambit through different kind of comparisons (Del Vecchio, 1995; Horn, 1993; Schifini, 1996):

• Transversal (comparisons between individuals in terms of age, gender, professional position, educational level, family, and so on)

• Spatial (comparisons between individuals living in different urban areas) • Longitudinal/dynamic (comparisons between data of the same respondent in different moments or comparisons between groups in different periods as a result of plausible repeated surveys)6 The following sections of this chapter offer a presentation of the analysis, the aggregation, and the combination of the composite indicators. The processes that were undertaken regarding these are briefly summarized below. An extended discussion of each of these follows in the subsequent major sections of this chapter. The analysis of the composite indicators. The goal of this work was to show the results of the statistical procedure, applied and finalized to the analysis, and the description of the composite indicators.7 In particular, the section on “the analysis of the composite indicators” in this chapter deals with the presentation of the explorative statistical process that was conducted in order to construct the indicators according to the data collected in the 2003 survey. This process proceeded through subsequent phases, designed to: 1. Verify the dimensionality of the group of selected items (dimensional analysis) 2. Construct the synthesis of the indicators (synthesis analysis) 3. Verify the informative characteristic of the indicators as well as of the items defining them (descriptive analysis) 4. Verify the discriminant capacity of the indicators between different groups defined with regard to the basic variables (comparative analysis). The existence of a significant statistical difference between the defined groups was tested applying the appropriate statistical tests (ANOVA), parametric or nonparametric depending on item distributions, at a significance level of 0.01. 5. Verify the validity of the indicators, in terms of QOL, by correlating them with single-item indicators of satisfaction (see questionnaire structure) (validity analysis)

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For each of the composite indicators, the analysis sought to reestablish the unity of the corresponding ambit and to synthesize the single-measured elements (items) in terms of conceptual and methodological homogeneity. The aggregation of the composite indicators. The composite indicators were submitted to an aggregation analysis to provide more interpretable and functional dimensions (section under “the aggregation of the composite indicators”). The aggregation analysis considered the dimensionality of the group of composite indicators, both in the theoretical and in the statistical sense. The combination of the composite and simple indicators. In order to identify the presence of typical profiles of citizens, a grouping analysis was performed using identification of the most frequent combination of values (section under “exploring the existence of some typical citizens’ profiles”).

The Analysis of the Composite Indicators The Subjective Image of the City To investigate the image of the city held by the respondents, a group of differential semantic scales was defined (question no. 25 of the questionnaire). The dimensional analysis (principal component analysis)8 of the data confirmed the presence of the five hypothesized “images.” Accordingly, five different indicators of the “images of Florence” were defined. These were: organization (DF1), uniqueness (DF2), dynamicity (DF3), hospitality (DF4), and livability (DF5). The individual scores (mean of the responses scores for the considered pairs of adjectives)9 range from 0 (extremely negative image) to 7 (extremely positive image).10 The results of the descriptive analysis and comparative analysis, for each composite indicator, and the validity analysis for all composite indicators, are presented below. Organization.11 The pairs of adjectives that define this indicator are (in parentheses component loadings are indicated): conservative–innovator (0.63), disorganized–organized (0.66), improvisator–planner (0.56), and chaotic–tidy (0.54). Figure 3 shows the distributions of each pair of adjectives and of the composite indicator. Significant differences were observed between groups defined in terms of age (lower scores registered by individuals from 30 to 50 years old), of standard of education (scores tend to be lower with reference to high education levels), of professional position (scores tend to be lower with reference to the higher positions), of residence area (scores tend to be lower as the citizens live closer to the center) and of proportion of life lived in Florence (scores tend to be higher among citizens with a high proportion). No significant difference was observed between groups defined in terms of household, even if a tendency to lower scores for singles and young couples were observed.

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8

160

6

120

0.14

Count

4

0.10 0.08

80

0.06

2

40

0

0

0.04

Proportion per bar

Measure

0.12

0.02 V147 V148 V155 V160 Organization: single-items distributions V147 conservative−innovator V155 V148 disorganized−organized V160

0

1

2 3 4 5 6 7 Organization (DF1)

8

0.00

improvisator−planner chaotic−tidy

Fig. 3. Image of Florence: distribution of the pairs of adjectives and of the corresponding defined indicator (organization).

Uniqueness.12 The pairs of adjectives that define this indicator are (in parentheses component loadings are indicated): ugly–beautiful (0.69), unknown–well known (0.75), despised–appreciated (0.68), unpleasant–pleasant (0.53), and common–unique (0.57). In Figure 4 the distributions of each pair of adjectives and of the composite indicator are shown. The high scores observed for this indicator point out the strong awareness of Florentine citizens regarding the inimitability of their city. This awareness is generally independent of age, gender, standard of education, professional condition, residence area, household, and proportion of life lived in Florence. This characteristic let the citizens come to a total agreement apart from any other evaluation. This homogeneity transformed the indicator in a real constant, suggesting its exclusion from any subsequent analysis.

300

8

Count

Measure

200 4

0.1

100 2

0

0 V146 V150 V154 V158 V174 Uniqueness: single-items distributions V158 V146 ugly−beautiful V150 unknown−well known V174 despised−appreciated V154

0

1

2 3 4 5 6 Uniqueness (DF2)

7

8

Proportion per bar

0.2

6

0.0

unpleasant−pleasant common−unique

Fig. 4. Image of Florence: distribution of the pairs of adjectives and of the corresponding defined indicator (uniqueness).

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Dynamicity.13 The pairs of adjectives that defined this indicator are (in parentheses component loadings are indicated): passive–active (0.42), slow–fast (0.48), boring–amusing (0.76), placid–lively (0.78), depressing–stimulating (0.57), and static–dynamic (0.58). Figure 5 shows the distributions of each pair of adjectives and of the composite indicator. Significant differences were observed between groups defined in terms of age (elderly and young people reported higher scores), of standard of education (low scores are associated with high education levels), of professional condition (lower scores are observed among managers, autonomous professionals, and workers), of residence area (higher scores observed among citizens living distant from the center). No significant difference was registered between groups defined in terms of proportion of life lived in Florence. A tendency to lower scores for singles and young couples was observed. Hospitality.14 The pairs of adjectives that define this indicator are (in parentheses component loadings are indicated): intolerant–tolerant (0.68), quarrelsome–easygoing (0.52), close–open (0.68), rude–courteous (0.69), inhospitable–hospitable (0.71), and uncaring–caring (0.46). In Figure 6 the distributions of each pair of adjectives and of the composite indicator are shown. Significant differences were observed between groups defined in terms of age (elderly and young people reported higher scores), of standard of education (low scores are associated with high education levels), of professional condition (lower scores are observed among managers and autonomous professionals), of residence area (higher scores observed among respondent living distant from the center), of household (higher scores observed among elderly people living in family and lower scores among singles and young couples), of proportion of life lived in Florence (lower scores observed among people living in Florence for a low proportion).

8

200

6

150 Count

0.12

4

0.10 100

0.08 0.06

50

2

Proportion per bar

Measure

0.16 0.14

0.04 0.02

0

51 63 6 6 6 7 7 0 7 1 V1 V1 V1 V1 V1 V1

0 0

1

2

3 4 5 6 Dynamicity (DF3)

7

8

0.00

Dynamicity: single-items distributions V151 V163 V166

inactive−active V167 slow−fast V170 boring−amusing V171

placid−lively depressing−stimulating static−dynamic

Fig. 5. Image of Florence: distribution of the pairs of adjectives and of the corresponding defined indicator (dynamicity).

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PERCEPTION AND EVALUATION OF THE QUALITY

150

8

0.12

0.08

Count

Measure

100 4

0.06 50

0.04

2

Proportion per bar

0.10

6

0.02 0

45 49 53 1 6 1 1 6 5 1 6 9 V1 V1 V1 V V Hospitality: single-items distributions

V145 V149 V153

intolerant−tolerant V161 quarrelsome−easygoing V165 V169 close−open

0 0

1

2 3 4 5 6 Hospitality (DF4)

7

0.00 8

rude−courteous inhospitable−hospitable uncaring−caring

Fig. 6. Image of Florence: distribution of the pairs of adjectives and of the corresponding defined indicator (hospitality).

Livability.15 The pairs of adjectives that define this indicator are (in parentheses component loadings are indicated): insecure–secure (0.55), noisy–silent (0.56), chaotic–tidy (0.51), disappointing–gratifying (0.57), unlivable–livable (0.74), stressful–relaxing (0.67), uncomfortable–comfortable (0.63), and uncivil–civil (0.51). Figure 7 shows the distributions of each pair of adjectives and of the composite indicator. Significant differences were observed between groups defined in terms of professional position (higher scores observed among retired people, students, and workers), of standard of education (lower scores are observed among higher education level), and residence area (higher scores among respondents living distant from the center). No significant differences were observed between groups defined in terms of proportion of life lived in Florence, age (even if a tendency to higher scores among elderly respondents was observed), and household (even if a tendency to lower scores among singles and young couples was observed). The comparison between the distributions of the “image” indicators (Figure 8) reveals a clear tendency of the respondents to have a strong positive image regarding the uniqueness (mean = 6.3, standard deviation (SD) = 0.7, negative asymmetry). The majority of the individuals registered mid-high scores for the indicators of dynamicity (mean = 4.5), hospitality (mean = 4.1), and livability (mean = 4.1). Tendentially lower scores can be observed for the organization indicator (mean = 3.6). While conducting validity analysis, interesting levels of correlation16 were observed between these indicators and the life in Florence indicator (question no. 25 of the questionnaire) and the level of satisfaction for one’s life in Florence (question no. 26 from the questionnaire) (Table 1). This is particularly true for the livability indicator and as regards to the present-day dimension. Such levels raise interesting questions regarding the capacity of the created image indicators in measuring the citizens’ perception of their city, particularly in terms of livability dimension.

86

FILOMENA MAGGINO

8

160

6

120

0.14

Count

4

0.10 0.08

80 0.06 0.04

40

2

Proportion per bar

Measure

0.12

0.02 0

52 56 59 60 62 64 68 72 73 V1 V1 V1 V1 V1 V1 V1 V1 V1

0 0

1

2

3 4 5 6 Livability (DF5)

7

8

0.00

Livability: single-items distributions V152 V156 V159 V160 V162

insecure−secure noisy−silent indolent−industrious chaotic−tidy disappointing−gratifying

V164 V168 V172 V173

unlivable−livable stressful−relaxing uncomfortable−comfortable uncivil−civil

Fig. 7. Image of Florence: distribution of the pairs of adjectives and of the corresponding defined indicator (livability).

There is, in general, a high level of criticism directed toward the city among the Florentine citizens. This was especially true regarding the organization, the dynamicity, the hospitality, and the livability of the city. Among citizens that appear to have more “interaction occasions” with the city life (these are people living in a particular city area, such as the city center), as they are engaged in particular professional activities (autonomous or commercial), and/or they have particular family typology producing particular needs (singles and young couples), this effect is particularly noticeable.

The Perception of the Tourist Dimension of the City Each individual involved in the study expressed his/her agreement regarding ten assertions concerning the presence of tourism in Florence (question no. 20 of the questionnaire). The individual aggregate scores were calculated by averaging the number of positive attitudes reflected by the responses to the ten items. This reported the response scales of the negatively oriented items appropriately. Thus, the obtained scores have a positive polarity and range from 0 (maximum negative perception) to 1 (maximum positive perception). The frequency distribution (Figure 9) shows a general tendency to mid and high scores (mean = 0.6 and SD = 0.2). In terms of comparative analysis, no differences were observed between groups defined in terms of age, professional condition, and proportion of time lived in Florence. Significant differences were, however, observed between groups defined in terms of standards of education (individuals with high standards seem to be more critical) and in terms of residence area (the level of positive perception increases with the distance from the center of the city). These results seem to confirm the comments made regarding the “image” indicators: the more critical attitudes are related to high standards of education and to deep individual interaction with the urban reality.

PERCEPTION AND EVALUATION OF THE QUALITY

87

8

Measure

6

4

2

0 DF1 DF2 DF3 DF4 DF5 Comparing indicators distributions

Fig. 8. Image of Florence: comparison between the distributions of the five indicators.

Table 1. Correlations between the subjective images of the city and other single-item indicators. The indicators of subjective image of Florence Organization Uniqueness Dynamicity Hospitality Livability Life in Florence

in the past at the present in the future Satisfaction for at the present one’s life 1 year ago in Florence

−0.04 0.31 0.30 0.31 0.28

0.10 0.25 0.19 0.34 0.35

0.00 0.28 0.24 0.35 0.35

0.04 0.27 0.27 0.35 0.33

0.05 0.42 0.40 0.48 0.41

In terms of validity analysis, no significant level of correlation was observed between this indicator and the life in Florence and the level of satisfaction for one’s life in Florence. The results seem to suggest that the city tourist dimension, even if it creates some practical livability problems, seems to be distinguished from the level of satisfaction. This is supported by the relatively low levels of correlation (ranging between 0.19 and 0.26) observed between this indicator and the image indicators.

The Perception of the Cultural Dimension of the City Respondents expressed their agreement (on a 0–10 rating scale) regarding four assertions about the city (question no. 22 of the questionnaire). Figure 10 shows

88

FILOMENA MAGGINO 400 0.3

Count

0.2 200

100

0.1

Proportion per bar

300

0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 Perception of the tourist dimension of the city

Fig. 9. Perception of the tourist dimension: frequency distribution.

the corresponding four distributions. The artistic aspect of the city rated a higher level compared to the other aspects. The frequency distribution of the corresponding combined indicator,17 defined as the average number of agreements (scores ranging from 0—no esteem—to 10—maximum esteem), as seen in Figure 10 shows a general tendency to mid-high scores (mean = 6.8, SD = 1.6). The comparative analysis shows significant differences between groups defined in terms of age (the level of consideration is higher among elderly people and lower among people with age ranging from 30 to 50 years), standards of education (the level of consideration decreases as the level of education increases), professional condition (higher scores among retired people, workers, and unemployed), residence area (higher score among people living very far from the center of the city), and proportion of life lived in Florence (higher scores among people living in Florence for a long time). The perception of the cultural dimension seems to be related to the level of satisfaction for one’s life in Florence (Table 2). In particular, these results seem to suggest, on one hand, that the level of perception could be related to an affective dimension (may be stereotyped and fixed). On the other hand, they may suggest that the satisfaction for the city life is not extraneous to the sociocultural and artistic dimensions. This issue may well need to receive significant attention when developing strategies and policies finalized to the betterment of city life.

The Perception of the Personal Safety Perceptions of personal safety were measured in three different urban contexts and two different moments of the day (question no. 18). The observation of the frequency distributions of the six items revealed the respondents’ tendency to have different perception between daytime and nighttime (Figure 11).

89

PERCEPTION AND EVALUATION OF THE QUALITY 500

10

0.4 400

Count

Measure

0.3 6 4

0.2

200

0.1

100

2

0

0 V135 V136 V137 V138 Single-items distributions

V135 V136 V137 V138

300

Proportion per bar

8

0.0 −1 3 7 11 Perception of the cultural dimension of the city

Florence facilitates communication among people Florence facilitates cultural activities Florence increases aesthetic sensibility and artistic sensitivity Florence offers same opportunities of other great cities

Fig. 10. Perception of the cultural dimension: frequency distribution of the scores for each item and for the composite indicator. Table 2. Correlations between the perception of the cultural dimension of the city and other single-item indicators. Perception of the cultural dimension of the city Life in Florence

Satisfaction for one’s life in Florence

in the past at the present in the future at the present 1 year ago

0.06 0.30 0.26 0.41 0.40

A cluster analysis was performed on the six items pointed out (Figure 12)18 the “moment of the day” as the prevailing dimension in this kind of perception. In other words, the subjective perception changes as a function of the moment of day and not of the area. Consequently, two different indicators of the personal safety perception were defined. These were: (1) the daytime safety perception and (2) the nighttime safety perception. The scores range from 1 (high security perception) to 4 (high insecurity perception). The observation of the obtained individual scores clearly shows, as expected, a more positive daytime perception (Figure 13). Both indicators showed significant differences between groups defined in terms of residence area (high positive perception among citizens living in the center, high negative perception among citizens living in the suburban area), in terms of age (the level of insecurity increases with the age), in terms of gender (high positive perception among men), in terms of standard of education (high positive perception among people with high standard). The significant difference observed between groups

90

FILOMENA MAGGINO 750

500

500

500

250

0

Count

Count

750

Count

750

250

250

0

1 2 3 4 District of residence

0

5

0

1

2 3 Center

4

0

5

0

1

2 3 4 Other districts

5

0

1

2 3 4 Other districts

5

Daytime safety perception 750

500

500

500

250

0

Count

Count

750

Count

750

250

1 2 3 4 District of residence

0

5

0

250

0

1

2 3 Center

4

5

0

Nighttime safety perception

Fig. 11. Perception of the cultural dimension: frequency distribution of the scores for each item.

Cluster tree Daytime safety perception V106 in the district of residence V110 in the center V114 in any other district

V112 V116 V108 V106 V110 V114

0.0

0.1

0.2 0.3 Distances

0.4

0.5

Nighttime safety perception V108 in the district of residence V112 in the center V116 in any other district

Fig. 12. Cluster tree obtained by the single-item indicators concerning the security perception.

91

PERCEPTION AND EVALUATION OF THE QUALITY 350

350

140

0.1

70 0

0.0 1 2 3 4 0 5 Personal safety perception: daytime

Count

Count

210

280 210

0.2

140 0.1 70

Proportion per bar

0.2

Proportionper bar

280

0.3

0.0 0 1 2 3 4 5 Personal safety perception: nighttime

0

Fig. 13. Indicators of safety perception (daytime and the nighttime): frequency distributions.

defined in terms of professional condition seems to be related with the age (students feel more secure, retired people more insecure). The relevance of the age factor is confirmed by both the comparison accomplished between groups defined in terms of household (elderly persons feel more insecure, apart from the typology of household) and the lack of any significant level of correlation between these indicators and the life in Florence and the level of satisfaction for one’s life in Florence.

Dynamic Evaluations: Time-related Comparisons For each single-item indicator, respondents reported a time-related comparison (today vs. 3 years ago). The grouping analysis19 on these perceptions produced the same ambits aggregations observed for the previous analysis, having pointing out the presence of the same two dimensions with the same single-item profiles. The new two indicators (ISP_GS, ISP_NS, respectively) can support and enrich the interpretation of the previous ones in terms of dynamic evaluation. The scores of the two new indicators range from 1 (clear betterment of the security perception) to −1 (clear worsening of the security perception). The analysis allowed verifying a relative stability of the perception with a tendency for both to the worsening (Figure 14). The comparison perception also revealed a discriminant capacity in terms of age (the worsening perception increases with age). The worsening perception is related also to the residence area, central and suburban. Moreover, each dynamic score registered an interesting level of relation (r values ranging from −0.35 to −0.40) with the corresponding perception indicator.

The Evaluation of the District Respondents were asked to give their evaluations regarding 20 single-item indicators that concerned their district of residence (question no. 6 of the questionnaire). Dimensional analysis (principal component analysis)20 of the 20 single-item indicators was used to confirm the presence of the five hypothesized areas of evaluation. Consistently, five indicators of evaluation were defined: traffic condition (ZONA1), presence of services (ZONA2), road network condition (ZONA3),

92

FILOMENA MAGGINO 700

0.2

200

Count

0.3

300

0.1

100

0.5

500

0.4

400

0.3

300 200

0.2

100

0.1

Proportion per bar

0.4 400

0.6 600 Proportion per bar

0.5

500 Count

700

0.6

600

0 0.0 −0.5 0.0 0.5 −1.0 1.0 Dynamic personal safety perception: nighttime

0 0.0 −1.0 −0.5 0.0 0.5 1.0 Dynamic personal safety perception: daytime

Fig. 14. The dynamic perception of the day- and night safety: frequency distributions.

urban environment (ZONA4), and urban green (ZONA5). The individual scores (mean score of the responses for the considered single-item indicators) range from 0 (extremely negative evaluation) to 10 (extremely positive evaluation).21 The results of the descriptive analysis and comparative analysis for each composite indicator and the validity analysis for all composite indicators are presented below. Traffic conditions.22 The single items that define this indicator are (in parenthesis component loadings): roads cleaning (0.54), traffic (0.78), availability of parking areas (0.67), quietness (0.78). Figure 15 shows the distribution of these items and of the related indicator. Significant differences were observed between groups defined in terms of age (more positive evaluations among young people) and of residence area (more positive evaluations among citizens living far from the center of the city). No significant differences were observed between groups defined in terms of standard of education (even if the scores decrease with high standard), of professional condition (even if the scores are higher among students), of household (even if singles registered the lowest scores), and proportion of one’s life lived in Florence. 11

200

0.16 0.14

Count

Measure

0.12

7

0.10 100

0.08 0.06

3 50

0.04

Proportion per bar

150

0.02 −1

0

V014 V016 V044 V046 Traffic condition: single-items distributions V014 V016

Roads cleaning Traffic

V044 V046

−1

3 7 Traffic condition

0.00 11

Availability of parking areas Quietness

Fig. 15. Evaluation of the district: distribution of the items and of corresponding indicator (traffic condition).

93

PERCEPTION AND EVALUATION OF THE QUALITY

Presence of services.23 The single items that define this indicator are (in parenthesis component loadings): chemist’s shops and ambulatories (0.72), post offices and banks (0.77), supermarkets or hypermarkets (0.54), stores (0.74), schools (0.61). In Figure 16 the distribution of these items and of the related indicator are shown. Significant differences were observed between groups defined in terms of residence area (low scores among citizens living in the center of the city). No differences were observed between groups defined in terms of age, of standard of education, of professional condition, of household (even if singles registered low scores), of proportion of life lived in Florence. Road network condition.24 The single items that define this indicator are (in parenthesis component loadings): bikeways (0.68), state of the roads network (0.46), street islands (0.76), removal of the architectonic barriers (0.57). Figure 17 shows the distribution of these items and of the related indicator. Significant differences were observed between groups defined in terms of age (high scores among young people), of standard of education (high scores among citizens with high standards), of residence area (high scores among citizens living far from the center). No significant differences were observed between groups defined in terms of professional condition (even if students registered a tendency to high scores), of household (even if singles and elderly people living alone registered low scores), of proportion of one’s life lived in Florence (even if with a tendency to lower scores among citizens born in Florence). Urban environment.25 The single items that define this indicator are (in parenthesis component loadings): road conditions (0.50), traffic signals (0.58), public transports (0.61), differentiated waste collection (0.56), removal of waste from garbage cans (0.61), streetlights (0.49). Figure 18 displays the distribution of these items and of the related indicator. Significant differences were observed among groups defined in terms of age (better evaluations among elderly people), of standard of education

11

200

0.16

Count

Measure

0.12

7

0.10 100

0.08 0.06

3 50

0.04

Proportion per bar

0.14 150

0.02 −1

V032 V036 V038 V040 V042

Presence of services: single-items distributions V032 V036 V038

Chemist’s shops and ambulatories Post offices and banks Supermarkets or hypermarkets

0

−1

V040 V042

3 7 Presence of services

0.00 11

Stores Schools

Fig. 16. Evaluation of the district: distribution of the items and of corresponding indicator (presence of services).

94

FILOMENA MAGGINO 11

200

0.16 0.12

Count

Measure

0.10 100

0.08 0.06

3 50

0.04

Proportion per bar

0.14 150 7

0.02 −1

0

V018 V020 V024 V028 Road network condition: single-items distributions V018 V020

Bikeways State of the roads network

−1

0.00 11 3 7 Road network condition

Street islands Removal of the architectonic barriers

V024 V028

Fig. 17. Evaluation of the district: distribution of the items and of corresponding indicator (road network condition).

11

200

0.16

Count

Measure

0.12

7

0.10 100

0.08 0.06

3 50

0.04

Proportion per bar

0.14 150

0.02 −1

0

20 22 2 6 3 0 3 4 4 8 V0 V0 V0 V0 V0 V0 Urban environment: single-items distributions

V020 V022 V026

Road conditions Traffic signals Public transports

V030 V034 V048

−1

3 7 Urban environment

0.00 11

Differentiated waste collection Removal of waste from garbage cans Streetlights

Fig. 18. Evaluation of the district: distribution of the items and of corresponding indicator (urban environment).

(scores tend to be low among citizens with high standards), of professional condition (low scores among managers and autonomous workers), of residence area (low scores among citizens living in the center), of household (low scores among singles and young couples). No significant differences were observed between groups defined in terms of proportion of one’s life lived in Florence. Urban green.26 The single items that define this indicator are (in parenthesis component loadings): differentiated waste collection (0.59), public gardens (0.63), sporting installations and facilities (0.71). In Figure 19 the distribution of these items and of the related indicator are shown. Significant differences were observed between groups defined in terms of age (better evaluations in the extreme groups),

95

PERCEPTION AND EVALUATION OF THE QUALITY 200

11

0.16 0.14 0.12

Count

Measure

7

0.10 100

0.08 0.06

3 50

0.04

Proportion per bar

150

0.02 −1

0

V030 V050 V052 Urban green: single-items distributions

V030 V050

V052

Differentiated waste collection Public gardens

−1

3 7 Urban green

0.00 11

Sporting installations and facilities

Fig. 19. Evaluation of the district: distribution of the items and of corresponding indicator (urban green).

of standard of education (scores tend to be low among citizens with high standards), of professional condition (low scores among managers and autonomous workers), of residence area (low scores among citizens living in the center), of household (lower scores among singles and young couples), of proportion of one’s life lived in Florence (the scores tend to decrease with the proportion). The comparison of the five indicators’ distributions allows one to point out a tendentially positive level of satisfaction, especially in the case of the presence of services (mean = 6.9) and the urban environment (mean = 6.2) indicators. The evaluation concerning the traffic condition (mean = 4.8) and road network condition (mean = 4) appears to be less positive (Figure 20). No significant relationships between these and the indicators of subjective image of the city were observed. These outcomes provide some interesting considerations. The positive evaluations reported by the group of young citizens

Measure

11

7

3

−1

1

NA

ZO

2

NA

ZO

3

NA

ZO

4

NA

ZO

A5

N ZO

Indicators distributions

Fig. 20. The indicators of evaluation of the district: frequency distributions.

96

FILOMENA MAGGINO

seem to suggest that they live the urban dimension by a different kind of involvement. Again the standard of education turned out to be a characteristic that can produce a more critical attitude, may be produced by a different kind of expectation toward the surrounding environment. The critical evaluations produced by singles and young couples may allow one to identify a particular subpopulation that seems to have some difficulty in managing the urban reality. In performing the validity analysis, significant levels of correlation were observed between the indicators, especially the traffic condition indicator that reveals to be a strategic dimension of the district life, and the level of satisfaction for the district (Table 3). This result represents evidence of the connection between the level of satisfaction concerning the district of residence and the urban environment in which one lives. It is not possible to underestimate the role that the age and the level of education play in the way the citizens live and, consequently, evaluate the city.

Dynamic Evaluations: Time-related Comparisons For each single-item indicator of evaluation, respondents had to report a time-related comparison (today vs. 5 years ago). The grouping analysis,27 conducted on these evaluations, confirmed the presence of the same five ambits of aggregations observed for the previous analysis (each ambit produced the same single-item profiles). The new five indicators can support and enrich the interpretation of the previous ones in terms of dynamic evaluation.28 The same score can be related to an improvement evaluation for a citizen or to a worsening evaluation for another citizen or to stability judgment for another one. The analysis of the dynamic scores (Figure 21), ranging from 1 (clear improvement in the evaluated ambit) to −1 (clear worsening in the evaluated ambit), allowed to point out (1) a relative stability in the evaluation of the presence of services (mean = −0.1), the road network condition (mean = 0.1) and the urban environment (mean = 0.1); (2) an improvement in the evaluation of the urban green; (3) a worsening in the evaluation of the traffic (mean = −0.4). Each dynamic

Table 3. Correlations between the evaluation of the district and other single-item indicators. The indicator of approval of tourism Traffic Presence of Road network Urban Urban condition services condition environment green Life in Florence

in the past at the present in the future Satisfaction at the present for one’s life 1 year ago in Florence Satisfaction for the district

0.04 0.29 0.23 0.27 0.24

0.06 0.17 0.18 0.21 0.19

0.06 0.25 0.23 0.19 0.17

0.07 0.24 0.24 0.23 0.19

0.12 0.25 0.20 0.20 0.18

0.50

0.28

0.30

0.37

0.36

97

PERCEPTION AND EVALUATION OF THE QUALITY 400

200

0.2

100

0.1

Count

0.3

0 0.0 −1.0 −0.5 0.0 0.5 1.0 Dynamic evaluation: traffic condition

300

0.3

200

0.2

100

0.1

0 0.0 −0.5 0.0 0.5 1.0 −1.0 Dynamic evaluation: presence of services

400

200

0.2

100

0.1

Count

0.3

0 0.0 −1.0 −0.5 0.0 0.5 1.0 Dynamic evaluation: road network condition

0.3

200

0.2

100

0.1

0 0.0 −0.5 0.0 0.5 1.0 −1.0 Dynamic evaluation: urban environment 1.0

400

0.3

200

0.2

100

0.1

0.0 1.0 0.0 0.5 Dynamic evaluation: urban green

0.5

Measure

300

Proportion per bar

Count

300

Proportion per bar

300

Proportion per bar

Count

400

0

Proportion per bar

300

Proportion per bar

Count

400

0.0

1S

NA

ZO

2S

NA

ZO

4S 5S 3S NA ONA ONA Z Z ZO

Comparison between indicators distributions

Fig. 21. The five dynamic indicators of the evaluation of the district: frequency distributions.

score registered an interesting level of relation (r values ranging from 0.4 to 0.5) with the corresponding evaluation indicator. The traffic dynamic indicator showed clear discriminate capacity. Significant differences were observed between groups defined in terms of standard of education (the worsening is observed among subjects with high standards), of age and professional condition (young people and students do not perceived any worsening). While

98

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the former outcome confirms previous comments, the latter can be explained by possibly different methods of urban mobility that young people and students have by using different means of transit that are not heavily involved in the city traffic. The role that the residence area plays in this kind of evaluation also deserves a brief note. It seems that the citizens that live in suburban areas do not perceive any worsening situation regarding these dimensions. There are noticeable deteriorations, though perceived by the citizens living round-the-center areas (with regard to the traffic) and in the town center (with regard to the urban green). Finally, the previously described critical attitude observed among singles is confirmed here: the persons living alone feel a worsening with regard to the presence of services, confirming the great difficulty in their everyday-life managing.

The Territorial Distribution of the Public Services Those in the study responded to items related to the amount of time required by them to walk to a variety of sites considered important and notable in everyday life (question no. 8 of the questionnaire). The reported times to these sites were varied for each individual and also between individuals, depending not only on the particular objective site but also by the subjective situation and perception (Figure 22). The aim here was to construct a perceptual map—concerning the territorial distribution of the defined “sites”—that allows describing in realistic way the territorial distribution by an individual sight. In order to obtain a stable result, the minutes reported by each respondent were analyzed by three different statistical approaches have produced coinciding outcomes. Figure 23 compares the results 250

Measure

200 V054 V055 V056 V057 V058 V059 V060 V061 V062 V063 V064 V065

150

100

50

Family doctor Chemist’s shop District center District office register The supermarket Grocer’s shop Local market Bus stop Police office/station Bank Post office School

0 54 55 56 57 58 59 60 61 62 63 64 65 V0 V0 V0 V0 V0 V0 V0 V0 V0 V0 V0 V0

How long it usually takes to walk to :

Fig. 22. Minutes (referred by respondents) required to walk to some sites considered important in everyday life.

Factor loadings plot

Cluster tree

Configuration

1.0 3 V054 V063

0.5

Dimension-3

V057 V060

00

V058 V062

−0.5

1

V064 V065

1.0

0.5

1.0

)

(2

R

TO

C

FA

0.0

V054 V055 V056 V057

0.5 (1)

Family doctor Chemist’s shop District center District office register

0

V055

Di

m

V061 0

0.0 OR T AC

.5

−0

V059

20

10

3

1 sio n

en

1

FACTOR(3)

V056

-2

30

Distances

F

V058 V059 V060 V061

The supermarket Grocer’s shop Local market Bus stop

V062 V063 V064 V065

1

on-

nsi

e Dim

Police office/station Bank Post office School

Fig. 23. Representations, obtained through three different statistical approaches, concerning the relations between the different times required to get to some sites considered important in everyday life.

100

FILOMENA MAGGINO

obtained through the three approaches (the principal component analysis,29 the cluster analysis,30 and the multidimensional scaling,31 respectively) and is used in identifying three “sites” typologies. These outcomes allowed the defining of three levels of territorial distribution of the identified services. These were: 1. Extensive distribution (SERV_1M). Services that can be reached in a short time (chemist’s shop, shops, post office, school, bus stop) 2. Zonal distribution (SERV_2M). Services that can be reached in a mid-long time (district center, district register office, supermarket, local market, police office/station) 3. Variable distribution (SERV_3M). Services that can be reached in variable time depending not on geographical factors but on individual preferences and conveniences (family doctor, bank). Three individual scores were calculated in terms of the mean of the original scores for each level. The observation of the frequency distributions of the three scores (Figure 24) has to consider the different length of the scales (the peak values are inevitably very different). The three distributions turned out to be significantly different between groups in terms of age only with regard to the extensive and zonal scores. The outcomes revealed that the perceived times required to reach the “sites” were not homogeneous among respondents, especially with regard to the age and to the residence area; in particular, the highest scores were observed among respondents living in the peripheral area with regard to the extensive and zonal distributions, and among respondents living in round-the-center areas. The outcomes concerning the third indicator (variable distribution of the services) clearly revealed that the individual perception of the times was connected, not to the real distance but to the individual preference. In other words, the “sites” that define the indicator are chosen not according to the practical conveniences but according to the individual faith; it seems that each individual is inclined to cover even longer distances to reach “his/her” family doctor and “his/her” bank. No significant level of correlation between these indicators regarding life in Florence and the level of satisfaction for one’s life in Florence was observed, suggesting that this is an overtaken dimension in terms of QOL in Florence.

The Irregularity of the Time Required to Cover the Daily-Route Distances It is generally agreed among individuals that the QOL in Florence is influenced by the amount of time that each citizen must usually spend in the daily commute of going to work or to school. The actual distances that the citizens of Florence have to cover are not objectively very long; on the other hand, the heavy presence of commuters and tourists coming every day in the city, in an unforeseable way, makes it difficult to predict the duration of the citizens’ daily commute time and route. This degree of commute variability, the minimum and the maximum time (expressed in minutes) that each respondent reported with regards to the daily route to go to work or to school (question no. 10 of the questionnaire), allows the addition of another element in describing and interpreting the subjective level of QOL.

0.1

100

0

10 20 30 40 Extensive distribution

0.0 50

300 0.2 200 0.1

100 0

0

100 50 Zonal distribution

0.0 150

400 0.3 Count

0.3 Count

Count

0.2 200

400

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300 0.2 200 0.1

100 0

0

100 200 Variable distribution

Fig. 24. Territorial distribution of the services: frequency distributions of the scores of the three indicators.

0.0 300

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This commute variability indicator was calculated as the ratio between the maximum–minimum values difference and the maximum value, which produced scores ranging from 0 (no irregularity) to 1 (maximum irregularity).32 In explanatory terms, a 0.5 score of irregularity points out that the subject can double the daily-route time. The indicator does not take into account the weekly frequency of the reported time limits (minimum and maximum); in fact, the two limits could have different frequency, for example, the maximum just once a week and the minimum many times. The lack of the weekly frequency does not allow a properly and consistently weighting of the indicator. The frequency distribution of the scores for the overall sample is shown in Figure 25. In the terms of validity analysis, significant differences were observed between groups defined in terms of residence area, with the greatest irregularities observed among citizens living in round-the-center and peripheral areas. Significant differences were also observed between groups defined in terms of the mean that the citizens usually use for the daily routes (question no. 9 of the questionnaire). In particular, it was observed that the greatest irregularities were among people moving by car. The greatest regularities were among people moving by bicycle. No significant difference was observed between groups defined in terms of age and professional condition. Contrary to expectations, no significant relationships were observed between this indicator and the five indicators of evaluation of the district. Additionally, no significant relationships were seen between this indicator and the five indicators concerning the subjective image of the city and the life in Florence and the level of satisfaction for one’s life in Florence.

The Aggregation of the Composite Indicators In order to make the composite indicators more interpretable and functional, the composite indicators previously described were submitted to further analysis to explore and identify possible and meaningful aggregations. A preliminary analysis, carried out 400 0.4

Count

0.3 200

100

0.2

Proportion per bar

300

0.1

0 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Irregularity of the daily route

Fig. 25. Irregularity of the daily route: frequency distribution.

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by the principal component analysis approach, identified five significant aggregations,33 as reported below (the recorded loading value is reported for each indicator): Component 1: the image of the city

• • • • • •

Organization (0.76) Dynamicity (0.76) Hospitality (0.81) Livability (0.79) Perception of the cultural dimension (0.39) Perception of the tourist dimension (0.60)

Component 2: the services

• • • •

Services with extensive distribution (0.81) Services with zonal distribution (0.86) Services with variable distribution (0.70) Evaluation of the presence of services in the district (−0.49)

Component 3: evaluation of the district

• • • • •

Evaluation of the traffic condition (0.68) Evaluation of the presence of services (0.57) Evaluation of the road network condition (0.75) Evaluation of the urban environment (0.83) Evaluation of the urban green (0.79)

Component 4: security

• Personal safety perception: daytime (0.87) • Personal safety perception: nighttime (0.88) Component 5

• Irregularity of the daily-route distances (0.87) • Perception of the tourist dimension (0.50) All the indicators, with the exception of two, recorded significant component loadings only on one of the five dimensions. The interpretation of the first four components is fairly straight forward, the fifth component, however, seems to represent a residual aggregation. In order to test the obtained aggregation, further analysis was carried out using cluster analysis34 to help judge the aggregation process. The cluster tree (Figure 26) seems to partially confirm the previous result, allowing identification of the four clear and interpretable aggregations. The irregularity of the daily-route distances (IRR_MOB) and the perception of the tourist dimension (TURIS) indicators appear to be “far” from the other identified aggregations, revealing contents and meanings not related to the other elements. A similar result can be observed with regard to the indicator of the evaluation of the presence of services (ZONA2). The four aggregations model is supported by the result obtained by the additive tree approach (Figure 27).35 This further result revealed a clear presence of four aggregations and the correspondent “separation” of the other two indicators (TURIS and IRR_MOB).

104

Cluster tree Aggregation 1: the services Services with extensive distribution SERV_1M Services with zonal distribution SERV_2M Services with variable distribution SERV_3M Aggregation 2: the image of the city DF1 Organization DF3 Dynamicity Hospitality DF4 Livability DF5 Perception of the cultural dimension CULTUR of the city Aggregation 3: the evaluation of the district ZONA1 Evaluation of the traffic condition Evaluation of the presence of services ZONA2 Evaluation of the road network ZONA3 condition ZONA4 Evaluation of the urban environment Evaluation of the urban green ZONA5

0.0

0.5

1.0

1.5

Aggregation 4: the security ISP_G Personal safety perception: daytime Personal safety perception: nighttime ISP_N

Distances

Fig. 26. Cluster tree describing the aggregation process of the indicators.

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SERV_3M SERV_2M SERV_1M ISP_G ISP_N IRR_MOB TURIS CULTUR DF3 DF4 DF5 DF1 ZONA1 ZONA5 ZONA4 ZONA3 ZONA2

PERCEPTION AND EVALUATION OF THE QUALITY

Aggregation 1: the services Services with extensive distribution SERV_1M Services with zonal distribution SERV_2M SERV_3M Services with variable distribution

Additive tree

DF4 DF5 DF1 DF3 CULTUR ZONA5 ZONA4 ZONA3 ZONA1 ZONA2

Aggregation 2: the image of the city Organization DF1 Dynamicity DF3 Hospitality DF4 Livability DF5 Perception of the cultural dimension CULTUR of the city

SERV_3M SERV_2M SERV_1M ISP_N ISP_G IRR_MOB TURIS

105

Aggregation 3: the evaluation of the district ZONA1 Evaluation of the traffic condition Evaluation of the presence of services ZONA2 Evaluation of the road network ZONA3 condition ZONA4 Evaluation of the urban environment Evaluation of the urban green ZONA5 Aggregation 4: the security ISP_G Personal safety perception: daytime Personal safety perception: nighttime ISP_N

Fig. 27. Aggregation tree describing the aggregation process of the indicators.

Factor analysis was used to confirm the presence of the four aggregations dimensions, explaining the 65% of the total variance. According to the four aggregations form, four individual scores were calculated, employing the factor scores recorded by each indicator (weighted scores). Overall the distributions of the sample scores (Figure 28) show a general normal shape, with the exception of the “evaluation of the district” composite indicator that shows a marked asymmetry, caused by the presence of extremely high positive scores.

Exploring the Existence of Some Typical Citizens’ Profiles In order to explore the presence of meaningful and typical profiles among the interviewed citizens, the following analysis aims to identify the most frequent combination of values in the observed group. A hierarchical cluster analysis36 was performed by taking into consideration the aggregated indicators (image of the city, evaluation of the district, services, personal safety), the composite indicators (irregularity of the daily-route distances and perception of the tourist dimension), and some single-item indicators (happiness, satisfaction for one’s life in Florence at the present, the life in Florence at the present, satisfaction for the district). The initial interpretation required the comparison of the profiles through the observation of the basic statistical indexes (minimum, maximum, mean, and SD) registered by the standardized indicators for each group. This interpretation had to take into consideration the different polarizations of the indicators. These were positive when the highest scores indicate positive evaluations (satisfaction for the district, life in Florence at the present, satisfaction for one’s life in Florence, perception of tourist dimension, image of the city, evaluation of the district), and negative when the highest scores indicate negative evaluations (happiness, irregularity of the daily-route, services, personal safety). Four typical profiles were individuated.

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0.1

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• • • • •

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−3

−2 −1 0 1 Image of the city

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Organization, DF1 (0.78) Dynamicity, DF3 (0.77) Hospitality, DF4 (0.81) Livability, DF5 (0.78) Perception of the cultural dimension, CULTUR (0.58)

• • • • •

0.1

0

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−5 −4 −3 −2 −1 0 1 2 3 Evaluation of the district

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Services • • • •

100

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Traffic condition, ZONA1 (0.67) Presence of services, ZONA2 (0.57) Road network condition, ZONA3 (0.72) Urban environment, ZONA4 (0.83) Urban green, ZONA5 (0.78)

300

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Extensive distribution, SERV_1M (0.82) • Personal safety perception: daytime, ISP_G (0.86) Zonal distribution, SERV_2M (0.84) • Personal safety perception: nighttime, ISP_N (0.88) Variable distribution, SERV_3M (0.67) Evaluation of the presence of services, ZONA2 (−0.48)

Fig. 28. The four aggregated indicators: frequency distributions of the individual scores and the defining indicators (with their individual component loadings).

1. The satisfied group. This group, formed by 442 respondents, is characterized by a high level of happiness and satisfaction for one’s life in Florence, by a positive representation of the life in the city. Further, they have a high level of satisfaction for their district, refer a good evaluation for the district, and perceive a high level of perception of personal safety (Table 4). 2. The critical group. This group, formed by 303 respondents, is characterized by mid-low level of image of the city and evaluation of their district. Their critical tendency is confirmed by the mid-low level of satisfaction for their district, for their life in Florence, for the life in the city, and of happiness (Table 5). 3. The satisfied-with-little group. This group, formed by 364 respondents, is characterized by mid-low scores for all the considered indicators with the exception of the low level of perceived personal safety (Table 6). 4. The integrated group. This group, comprising 76 respondents, is characterized by mid-high level of satisfaction for their life in Florence. They have a positive level of representation of the city life and express a high appreciation for the presence of the tourism and for the territorial distribution of the services. They are regular in the time required to cover their daily-route distances (Table 7).

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Table 4. The satisfied group (n = 442): indicators profiles.

Indicators polarity Negative Positive

Indicator Satisfaction for the district Life in Florence at the present Satisfaction for one’s life in Florence at the present Perception of the tourist dimension Image of the city Evaluation of the district Happiness Irregularity in the daily route Services Personal safety

Minimum

Mean

Maximum

SD

−2.11 −1.93 −1.91

0.52 0.62 0.54

1.59 1.63 1.72

0.65 0.64 0.71

−2.54

0.22

1.81

0.91

−2.05 −2.44 −1.50 −2.61 −1.56 −2.26

0.31 0.43 −0.50 0.06 −0.22 −0.60

2.78 3.18 2.16 2.38 1.95 1.39

0.88 0.87 0.74 0.96 0.60 0.73

Table 5. The critical group (n = 303): indicators profiles.

Indicators polarity Negative Positive

Indicator Satisfaction for the district Life in Florence at the present Satisfaction for one’s life in Florence at the present Favor for the perception of the tourist dimension Image of the city Evaluation of the district Happiness Irregularity in the daily route Services Personal safety

Minimum

Mean

Maximum

SD

−3.70 −2.64 −4.33

−0.80 −0.89 −1.05

1.59 1.63 0.51

1.09 0.95 0.97

−2.54

−0.59

1.81

1.01

−3.60 −4.06 −1.50 −2.61 −1.78 −2.33

−0.82 −0.54 0.76 −0.09 −0.06 −0.07

1.82 2.14 2.89 2.86 2.88 2.94

0.89 1.05 1.06 1.04 0.81 0.96

Table 6. The satisfied-with-little group (n = 364): indicators profiles.

Indicators polarity Negative Positive

Indicator Satisfaction for the district Life in Florence at the present Satisfaction for one’s life in Florence at the present Perception of the tourist dimension Image of the city Evaluation of the district Happiness Irregularity in the daily route Services Personal safety

Minimum

Mean

Maximum

SD

−3.70 −2.64 −1.91

−0.04 −0.09 0.18

1.59 1.63 1.72

0.86 0.86 0.67

−2.54 −1.63 −2.92 −1.50 −2.61 −1.95 −0.73

0.09 0.27 −0.06 −0.06 0.07 −0.05 0.77

1.81 2.85 2.46 2.89 2.76 2.59 3.34

0.86 0.84 0.85 0.83 1.00 0.75 0.78

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Table 7. The integrated group (n = 76): indicators profiles.

Indicators polarity Negative Positive

Indicator Satisfaction for the district Life in Florence at the present Satisfaction for one’s life in Florence at the present Perception of the tourist dimension Image of the city Evaluation of the district Happiness Irregularity in the daily route Services Personal safety

Minimum

Mean

Maximum

SD

−2.11 −1.93 −1.31

0.35 0.38 0.07

1.59 1.63 1.72

0.78 0.73 0.77

−2.06 −1.50 −3.02 −1.50 −2.61 1.51 −2.02

0.59 0.05 −0.16 0.17 −0.40 3.73 −0.21

1.81 2.70 2.01 2.89 1.81 7.56 2.00

1.07 1.03 1.25 0.97 1.01 1.49 0.98

Figures 29A and 29B show, respectively, the individuals’ and indicators’ profiles for each group; these graphic representations allow a better appreciation of the differences between the previously described groups. A multiple correspondence factor analysis was applied in order to point out the basic characteristics that better describe the four identified groups.37 The results help clarify the groups’ profiles (Figure 30). In particular, the satisfied group is characterized by the prevailing presence of men, being part of enlarged family context, carrying on a white-collar activity. The critical group mainly constitutes singles or young couples, by citizens with a high standard of education (degree) and with managerial or autonomous activities (manager), and by people living in central or round-the-center city areas (I-cint). The satisfied-with-little group mainly comprises women and people living far from the center. The integrated group is characterized by a prevailing presence of elderly people (especially couples).

Conclusions The initial results of the Florentine study presented here raise a number of questions regarding QOL in Florence and suggest the need for further examination. Nevertheless, the presented results suggest a general positive relation of the Florentine citizens with their city, in terms of both perception and evaluation. In this general framework, two particular individual profiles deserve to be noted. These are: (1) the positive relation that elderly people, living as couples, have with the city; and (2) the difficult relations that an emerging citizen typology has with the city. This particular typology seems to be composed mostly by singles, with a high standard of education, an exacting work schedule, and a high level of involvement in the city and urban environment. This seems to suggest the important role that familiar and social relationships and the standard of education play in individual life. In other words, these relationships and cultural levels are important and basic factors. These are connected, directly and indirectly, to the level of QOL in urban context and to its subjective perception by the city’s populace.

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From a methodological perspective, it is worthwhile pointing out that the study revealed that the “atypicity” concerns mainly are related to the operational definition of the indicators, but not necessarily to the conceptual definitions. For the most part, these can be applied, in our opinion, in other urban contexts. The proposed approach has significant potential since it allows not only the ability to measure a particular ambit but also the ability to explore the connection of the different levels of the indicators with other important individual characteristics. From a policy point of view, the current study provides a cue for a variety of considerations. The approach here used well-synthesized information, which makes it possible to depict the composite descriptions necessary to develop strategies and policies aimed to specific urban areas, segment of population, or particular urban urgent situation. Nevertheless, public policy officials need to be aware of some concerns regarding such data synthesis and analysis. The analysis, which aggregated the Cluster parallel coordinate plots 2

SERVIZI

SERVIZI

V176

V176

V143

V143

SICUREZZA

SICUREZZA

Index of case

Index of case

1

V071 V187 IMMAGINE VAL_ZONA

V071 V187 IMMAGINE VAL_ZONA

TURIS

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IRR_MOB

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V071 V187 IMMAGINE VAL_ZONA

V071 V187 IMMAGINE VAL_ZONA

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IRR_MOB

IRR_MOB

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Indicato rs with positive polarity V071: satisfaction for the district V143: life in Florence at the present V176: satisfaction for one’s life in Florence at the present TURISM: perception of the tourist dimension IMMAGINE: image of the city VAL_ZONA: evaluation of the district

0

Indicator s with negative polarity V187: happiness IRR_MOB: irregularity in the daily route SERVIZI: services SICUREZZA: personal safety

Fig. 29A. Individuals’ profiles for each group.

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Cluster profile plots 1

2

SERVIZI V176 V143 SICUREZZA V071 V187 IMMAGINE VAL_ZONA TURIS IRR_MOB

3

SERVIZI V176 V143 SICUREZZA V071 V187 IMMAGINE VAL_ZONA TURIS IRR_MOB

4

SERVIZI V176 V143 SICUREZZA V071 V187 IMMAGINE VAL_ZONA TURIS IRR_MOB Indicators with positive polarity V071: satisfaction for the district V143: life in Florence at the present V176: satisfaction for one’s life in Florence at the present TURISM: perception of the tourist dimension IMMAGINE: image of the city VAL_ZONA: evaluation of the district

SERVIZI V176 V143 SICUREZZA V071 V187 IMMAGINE VAL_ZONA TURIS IRR_MOB Indicators with negative polarity V187: happiness IRR_MOB: irregularity in the daily route SERVIZI: services SICUREZZA: personal safety

Fig. 29B. Indicators’ profiles for each group.

composite indicators—collected at a disjointed level within a reference conceptual model—needs to consider the risk that an excessive synthesis may produce especially in the presence of multidimensional characteristics. A unique value that synthesizes too many component of subjective QOL may be not only attractive but also useless from a city management point of view. Alternatively, the efforts to perform deep analyses in order to explore the presence of typical citizens’ profiles by well-defined composite indicators can be recompensed by valuable and significant interpretation. Finally, the long-term value of QOL studies relies heavily on the ability to create a reliable and longitudinal database. The utility of the efforts done in order to design and to accomplish a study like the current one relies on the availability of timely, up-to-date information. In the case of this particular study, officials— composing the Florentine research group—have expressed interest in continuing with the survey,38 and discussed the importance and the opportunity to build a system that is kept up-to-date. At the present time, the authors are hopeful that this kind of QOL measurement and monitoring system will come to pass.

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+2

laurea dirigenti

centro anziano solo

single critici coppie

anziani in famiglia pensionati due anziani

I cintura

uomini impiegati soddisfatt i famiglia diploma

donne in tegrati II cintura non occupati si accon tentano licenza media

+2

periferia

artigiani commercianti

studenti operai

Residence area centro → center 1a-cint → close-to-the-center area 2a-cint → mid-suburban area peri f → suburban area Profession non_o cc → not employed pens → retire d stud → student dir → manager or assimilated imp → employee art com → art isan/ trade r op → worker Sex donn e → femal e uomini → male

Household 2 anzi ani → elderl y person liv ing with anot her elderly person 2 n_anziani → young couple anz i n fam → elderly person living in an enlarged family anzi ano solo → elderly single n_anz in fam → not- elderly person living in an enlarged family n_anziano so → young single Standard of education obbl → compulsory education sup → secondary school univ → university degree Group SODD → the satisfied CRITICI → the critical ACCONT → the satisfied-with-little INTEGRATI → the integrated

Fig. 30. Description of the group’s characteristics by some basic variables (multiple correspondence factor analysis).

Notes 1. Before performing the statistical analyses, the basic variables were submitted to a new defining, performed consistently with the aims of the study and with the conceptual model. Following is the description of the basic variables submitted to the new defining. • Age (AGE). Four categories were defined: (1) 18–30 (13%); (2) 31–49 (34%); (3) 50–64 (25%); (4) 65 and above (29%).

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• Profession (PROF). The new defining of this variable is obtained by the combination of two variables—professional condition and professional position: (1) not employed (unemployed, house working, military/social service) (10%); (2) retired (retired or invalid) (31%); (3) student (6%); (4) manager or assimilated (manager, official, contractor, autonomous) (18%); (5) employee (clerk, staff, partner of cooperative society) (22%); (6) artisan/trader (5%); (7) worker (8%). • Residence area (GEO). The new defining of this variable has taken into account the territorial distribution of the 20 census areas (employed for the sampling frame) and their position with reference to the city center: (1) central area (16%); (2) close-to-thecenter area (19%); (3) mid-suburban area (20%); (4) suburban area (45%). • Household (FAM). The new defining of this variable has taken into account the number of the family members, their ages, and civil status. Six family typologies were defined: (1) elderly person living alone (8%); (2) single (9%); (3) elderly person living in an enlarged family (7%); (4) not-elderly person living in an enlarged family (47%); (5) elderly person living with another elderly person—elderly couple (14%); (6) notelderly person living with another not-elderly person–young couple (16%). • Standard of education (STUDY). (1) Qualification corresponding to the compulsory education (49%); (2) qualification corresponding to the secondary school (30%); (3) qualification corresponding to at least a university degree (21%). • Proportion of one’s life spent in Florence as a resident (PERC_IM). The ratio between the age at one’s registration in the City General Register and the present age was calculated. The following categories were defined: (1) not more than 50% of one’s life spent in Florence as a resident (29%); (2) from 51% to 90% of one’s life spent in Florence as a resident (28%); (3) more than 90% of one’s life spent in Florence as a resident (43%; 40% from birth). In the application of this variable we have to consider that Florentine citizens exist that usually live a relatively long part of their life in Florence not as a resident—but as usually happens among university students. The gender variable was rarely employed because of its poor discriminant capability. 2. Obviously, the substitution of the nonresponses produced a sample affected by a form of self-selection susceptible to introduce distortions, but the strict control of the strata (in terms of area, sex, and age) can help to reduce the effects. In spite of the presence of the substitution list, some strata did not reach the expected numerosity at the end of the survey. In order to cope with this residual quote of nonresponses, the weights were multiplied by the reciprocal of the response rate (calculated for each unit belonging to the hth stratum as the ratio between the number of respondents for the h stratum and the number of the drawn units for the h stratum). This choice assumes that inside each stratum the respondents and nonrespondents are homogeneous as regards the involved characteristics. The high level of stratification of the sampling design and low rate of nonresponses (1.3%) made the assumption realistic and any source of distortions noninfluential. 3. The English version of the questionnaire presented in Appendix A needs a back-translation for accuracy of the meaning, in the case some researchers would like to apply this in an English-spoken context. 4. Even if the two questionnaires come from the same conceptual model, they required different scaling approaches. The data allowed the comparison of the two scaling approaches adopted for the same variables (single-item indicators) for the two surveys. 5. The data collected in both surveys allowed the accomplishment of the following comparison analyses (not presented here): • Comparison between the perceptions of the year before the survey (perception of the 2002 vs. perception of the 2003); this kind of analysis is finalized to assess the stability of subjective perception of the past

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• Comparison between the present perception (expressed in 2003 survey) and the past perceptions (expressed in 2004 survey); this kind of analysis is finalized to assess the presence of the “memory effect” • Comparison between the present perceptions (2003 survey vs 2004 survey); this kind of analysis is finalized to measure the individual change 6. One of the aims of the Florentine project was to accomplish and repeat cyclically this kind of surveys. 7. In this context the analysis of the single-item indicators is not presented. 8. The extracted dimensions (varimax rotation) explain the 56% of the total variance. 9. The definition of the indicators has not considered the adjectives industrious–indolent and formal–informal since they registered no significant loading. 10. In this method of calculus, we decided not to consider the different weight (component score) recorded by each item since the weights of the items defining each indicator have the same amount. 11. This indicator has produced a significant level of internal consistency (Cronbach alpha = 0.7). 12. This indicator has produced a significant level of internal consistency (Cronbach alpha = 0.7). 13. This indicator has produced a high level of internal consistency (Cronbach alpha = 0.8). 14. This indicator has produced a high level of internal consistency (Cronbach alpha = 0.8). 15. This indicator has produced a high level of internal consistency (Cronbach alpha = 0.8). 16. The relation was measured by the Pearson coefficient. Analogous results were obtained by applying the Spearman coefficient for ranked data. 17. The internal consistency of the group of items produced a quite satisfying result (Cronbach alpha = 0.7), considering that the instrument was submitted here for the first time. 18. The produced cluster tree was obtained through the hierarchical approach (distance: gamma; linkage: complete). 19. The grouping analysis, realized by the hierarchical cluster analysis (distance: gamma, linkage: complete) allowed to verify the aggregation process of the single-item indicators. 20. The principal component analysis (varimax rotation) has extracted five dimensions (56% of the total variance explained). 21. Also in this method of calculus, we decided not to consider the different weight (component score) that each item registered since the weights of the items defining each indicators registered almost the same amount. 22. This indicator registered an interesting internal consistency value (Cronbach alpha = 0.7). 23. This indicator registered a high internal consistency value (Cronbach alpha = 0.8). 24. This indicator registered an encouraging internal consistency value (Cronbach alpha = 0.6). 25. This indicator registered an interesting internal consistency value (Cronbach alpha = 0.7). 26. This indicator registered an interesting internal consistency value (Cronbach alpha = 0.7). 27. The grouping analysis, realized by the hierarchical cluster analysis (distance: gamma, linkage: complete) allowed to verify the aggregation process of the single-item indicators. 28. Each dynamic indicator represent a comparison with respect to traffic condition (ZONA1S), presence of services (ZONA2S), road network condition (ZONA3S), urban environment (ZONA4S), urban green (ZONA5S). 29. The produced configuration, obtained by a varimax rotation, explains the 55% of the total variance. The figure shows the items’ position in the space defined by three dimensions. 30. The produced cluster tree, obtained through the hierarchical approach (distance: euclidean; linkage: complete) allows to represent the items aggregation process, which clearly helps to distinguish three groups of items. 31. The multidimensional scaling allows to represent geometrically a multidimensional space and to describe a model underlying the observed data. The obtained configuration (stress: 0.07; proportion of explained variance: 0.99) helps to identify the position of the item in the defined space.

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32. The maximum value is theoretical since it could be observed only in the case of zero recorded as minimum value. 33. The five dimensions explain the 65% of the total variance (rotation method: varimax). 34. The hierarchical cluster analysis was applied on the matrix of the distances—defined in terms correlation coefficient (1−r)—between the composite indicators and adopted a joining algorithm defined in terms of complete linkage method. Generally, this combination allows pointing out homogeneous groups (Aldenderfer and Blashfield, 1984; Lis and Sambin, 1977). 35. In this phase, the additive tree method was applied in order to model the distances between the indicators. The produced hierarchical trees imply that all within-cluster distances are smaller than all between-cluster distances, and that within-cluster distances are equal (“ultrametric” condition). Additive trees represent similarities with a network model in the shape of a tree. The distances between indicators are represented by the lengths of the branches connecting them in the tree. From the statistical point of view, the outcome is rather satisfactory (stress = 0.05, r2 = 0.93). 36. In the first phase of this analysis, a hierarchical cluster analysis was applied in order to verify the existence of a restricted number of typical profiles among the respondents. In the second phase, the application of the k-means approach allowed to identify, verify, and interpret the obtained typologies. 37. The first two factors extracted account for 19% of the total inertia (n = 1165). 38. The presentation of the data and results of the second survey is not in the purpose of this work.

References Aldenderfer, M.S. and Blashfield, R.K. (1984). Cluster analysis. Sage University paper series on quantitative applications in the social sciences, series no. 07–044. Beverly Hills, CA: Sage. Bramston, P., Pretty, G., and Chipuer, H. (2002). Unravelling subjective quality of life: an investigation of individual and community determinants. Social Indicators Research, 59(3):261–274. Christakopoulou, S., Dawson, J., and Gari, A. (2001). The community well-being questionnaire: theoretical context and initial assessment of its reliability and validity. Social Indicators Research, 56(3):319–349. Del Vecchio, F. (1995). Scale di misura e indicatori sociali. Bari: Caccucci. Horn, R.V. (1993). Statistical Indicators. Cambridge: Cambridge University Press. Lis, A. and Sambin, M. (1977). Analisi dei cluster. Padova: CLEUP. Michalos, A.C. (2003). Policing services and the quality of life. Social Indicators Research, 61(1):1–18. Michalos, A.C. (2005). Arts and the quality of life: an exploratory study. Social Indicators Research, 71(1):11–59. Michalos, A.C. and Zumbo, B.D. (1999). Public services and the quality of life. Social Indicators Research, 48(2):125–156. Schifini, S. (1996). Teoria degli indicatori sociali. In Strassoldo, M., Mattioli, E., and Schifini, S. (eds.), Teoria dei numeri indici dei prezzi e degli indicatori economici, finanziari e sociali. Padova: CEDAM. Sirgy, M.J. and Cornwell, T. (2001). Further validation of the Sirgy et al.’s measure of community quality of life. Social Indicators Research, 56(2):125–143. Sirgy, M.J., Rahtz, D.R., Cicic, M., and Underwood, R. (2000). Underwood, a method for assessing residents’ satisfaction with community-based services: a quality-of-life perspective. Social Indicators Research, 49(3):279–316.

PERCEPTION AND EVALUATION OF THE QUALITY

115

Appendix A: The Quality of Life in Florence 2003 OCTOBER

QUESTIONNAIRE NUMBER INTERVIEWER CODE

■■■ ■■

The City of Florence is undertaking a major effort to enhance the quality of life in the city by developing policies and programs designed to meet resident’s needs. Together with the Department of Statistics of the University of Florence we plan to identify indicators of quality of life in Florence that capture the level of residents’ satisfaction with the city’s living conditions. Your cooperation in completing this survey questionnaire will help us with this task.

116

FILOMENA MAGGINO

1. Relation with the City Relation with the Neighbourhood Area 1. How did you choose the district where you live? (more answers admitted). ➢ I chose it (the district is lovely, comfortable, . . .) ■ ➢ I always lived here ■ ➢ For financial reason (purchasing or renting cost of the house) ■ ➢ The relatives are close ■ ➢ Working reasons ■ ➢ I found my house here (I didn’t choose it) ■ ➢ I have chosen the house, not the district ■ ➢ Others (please, point out) ■■

2. You are: ➀ the owner / the usufructuary of your house ➁ tenant of your house ➂ others (please, mention explicitly) 3. You live: ➀ with your parents family ➁ with your family ➂ alone ➃ with a cohabitant ➄ (please, mention explicitly)

(v1) (v2) (v3) (v4) (v5) (v6) (v7) (v8)

(v9)

(v10)

4. How long do you live in this house? Point out”zero” if less than one year. ■■ (v11) 5. From 0 (at all) to 10 (completely), can you tell how much you are satisfied about your house? ➀➁➂➃➄➅➆➇➈➉ DK■ (v12)

6. From 0 (worst evaluation) to 10 (better evaluation), how do you evaluate your district as regards following aspects?

7. In your opinion, in comparison with 5 years ago, the evaluation is better (+), same (=) or worst (-)? I lived in another district ■

➢ Cleaning (roads, sidewalks,. . .)

➢ Road condition

➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ DK ■ ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ DK ■ DK ➀➁➂➃➄➅➆➇➈➉ ■ ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ DK ■

➢ Traffic signals (zebra crossing, traffic lights,. . .)

➀➁➂➃➄➅➆➇➈➉

➢ Street islands

➀➁➂➃➄➅➆➇➈➉

➢ Public transport

➀➁➂➃➄➅➆➇➈➉

DK ■ DK ■ DK ■

➢ Removal of the architectonic barriers

➀➁➂➃➄➅➆➇➈➉

DK ■

(v28)

+ =

− DK ■

(v29)

➢ Differentiated waste collection

➀➁➂➃➄➅➆➇➈➉

DK ■

(v30)

+ =

− DK ■

(v31)

➢ Chemist’s shops, ambulatories

➀➁➂➃➄➅➆➇➈➉

DK ■

(v32)

+ =

− DK ■

(v33)

➢ Removal of waste from garbage cans

➀➁➂➃➄➅➆➇➈➉

(v34)

+ =

➢ Post offices, banks

➀➁➂➃➄➅➆➇➈➉

DK ■ DK ■

(v36)

+ =

− DK ■ DK − ■

➢ Supermarkets / hypermarkets

➀➁➂➃➄➅➆➇➈➉

DK ■

(v38)

+ =

− DK ■

(v39)

➢ Stores (clothes, shoes,. . .)

➀➁➂➃➄➅➆➇➈➉

DK ■

(v40)

+ =

− DK ■

(v41)

➢ Schools (kindergartens, primary schools)

➀➁➂➃➄➅➆➇➈➉

(v42)

+ =

➢ Parking places

➀➁➂➃➄➅➆➇➈➉

(v44)

+ =

➢ Quiet (little noise)

➀➁➂➃➄➅➆➇➈➉

(v46)

+ =

➢ Street lights

➀➁➂➃➄➅➆➇➈➉

(v48)

+ =

➢ Public gardens

➀➁➂➃➄➅➆➇➈➉

DK ■ DK ■ DK ■ DK ■ DK ■

(v50)

+ =

− DK ■ DK − ■ − DK ■ DK − ■ − DK ■

➢ Sporting installations and facilities

➀➁➂➃➄➅➆➇➈➉

DK ■

(v52)

+ =

− DK ■

➢ Road traffic ➢ Bikeways

− DK ■ − DK ■ DK − ■ − DK ■

(v13)

(v14)

+ =

(v16)

+ =

(v18)

+ =

(v20)

+ =

(v22)

+ =

(v24)

+ =

(v26)

+ =

− DK ■ DK − ■ − DK ■

(v15)

(v17)

(v19)

(v21)

(v23)

(v25)

(v27)

(v35)

(v37)

(v43)

(v45)

(v47)

(v49)

(v51)

(v53)

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FILOMENA MAGGINO

8. How long it takes you to walk from your home to (minutes) ➢ Your family doctor ■■■ ➢ The nearest chemist’s shop ■■■ ➢ The district center ■■■ ➢ The district Register Office ■■■ ➢ The supermarket ■■■ ➢ Your usual grocer’s shop ■■■ ➢ The local market ■■■ ➢ The nearest bus stop ■■■ ➢ The police office/station ■■■ ➢ Your bank ■■■ ➢ The post office ■■■ ➢ The kindergarten and/or primary school ■■■

DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■ DK ■

(v54) (v55) (v56) (v57) (v58) (v59) (v60) (v61) (v62) (v63) (v64) (v65)

Which mean do you use to go throughout the city 9. With reference to last week, by which mean did you go to: By private By motor- By By I didn’t go to car bike bicycle By bus walking anywhere ➢ . . . work/school

➀

➁

➂

➃

➄

➅

DK ■

➢ . . .other places

➀

➁

➂

➃

➄

➅

DK ■

10.How long it takes you to go for the daily route (to go to work/school)? Minimum time (minutes) ■■ (v68) Maximum time (minutes) ■■ (v69) DK ■

(v66) (v67)

(v70)

11. Using a score from 0 (at all) to 10 (completely), can you tell how much are you satisfied for your district? 0 ➀➁➂➃➄➅➆➇➈➉ DK ■ (v71) 12. and in comparison with 5 years ago? ➀ More satisfied ➁ The same ➂ Less satisfied ➃ I lived in another district DK ■

(v70))

13. As you know, urban deterioration is a process shared by many cities. In your opinion what is “deterioration” for a city? Indicate which are, in your opinion, the three factors that mostly characterize it (in order: 1 = the most important). (v73) A. burned / damaged cars ■ (v74) B. abandoned / destroyed bicycles, motorbikes ■ (v75) C. damaged / burned garbage cans, abandoned house refuses ■ (v76) D. abandoned / degraded buildings ■ (v77) E. damaged / out of order / absent public lights ■ (v78) F. little illegal garbage dumps ■ (v79) G. dirty walls ■ (v80) H. unclean streets ■ (v81) I. ruined streets and sidewalks, broken manhole covers ■ (v82) J. urban vandalism (damaged benches, traffic signals or signs,.) ■ (v83) K. neglected public garden ■ (v84) L. others: ■ (v85) DK ■

119

PERCEPTION AND EVALUATION OF THE QUALITY

14. Some problems of the urban environment are common to many Italian cities. With regard to Florence, put the following problems in order, according to which is worrying you (1 = the most, 6 = the less). (v86) A. urban deterioration ■ (v87) B. road accidents ■ (v88) C. acoustic pollution (noise) ■ (v89) D. atmospheric / olfactory pollution ■ (v90) E. dangerous roads (streets, crossroads, . . .) ■ (v91) F. too much traffic ■ DK ■ (v92) 15. Indicate your level of agreement with the following proposals concerning environmental politics set up in Florence. Strongly Slightly Slightly Strongly agree agree disagree disagree ➢ block off to private-cars traffic

➀

➁

➂

➃

➢ “ecological days”

➀

➁

➂

➃

➢ alternating private-cars traffic

➀

➁

➂

➃

➢ free electric-bus in the center of the city

➀

➁

➂

➃

16. There are many road works ahead in Florence. Tell how much you . . . Much Quite Little At all ➢ believe to be well informed about road works ➀ ➁ ➂ ➃

DK ■ DK ■ DK ■ DK ■

(v93)

(v94)

(v95)

(v96)

DK ■

(v97)

➢ accept to suffer temporary inconveniences for the improvement of the city

➀

➁

➂

➃

DK ■

(v98)

➢ believe that the road works are able to improve the mobility

➀

➁

➂

➃

DK ■

(v99)

17. Like other great cities, Florence presents some important social phenomena. In your opinion, how much are the following phenomena relevant in the city of Florence? Very Quite Little Presence of important important important At all ➢ pushing drugs

➀

➁

➂

➃

➢ nomads

➀

➁

➂

➃

➢ clandestine immigration

➀

➁

➂

➃

➢ crimes (thefts, bag-snatchings, . . .)

➀

➁

➂

➃

➢ street prostitution

➀

➁

➂

➃

➢ homeless people

➀

➁

➂

➃

DK ■ DK ■ DK ■ DK ■ DK ■ DK ■

(v100)

(v101)

(v102)

(v103)

(v104)

(v105)

120

FILOMENA MAGGINO

How much do you feel secure walking along the roads of

18. and in comparison with 3 years ago?

very quite little secure secure secure at all DK

more

same

less DK

➢ your district, daytime

➀

➁

➂

➃

■ (v106) ➀

➁

➂

■ (v107)

➢ your district, nighttime

➀

➁

➂

➃

■

(v108)

➀

➁

➂

■

(v109)

➢ the center, daytime

➀

➁

➂

➃

■

(v110)

➀

➁

➂

■

(v111)

➢ the center, nighttime

➀

➁

➂

➃

■

(v112)

➀

➁

➂

■

(v113)

➢ other district, daytime

➀

➁

➂

➃

■

(v114)

➀

➁

➂

■

(v115)

➢ other district, nighttime

➀

➁

➂

➃

■

(v116)

➀

➁

➂

■

(v117)

19. Last year did you, or someone of your family, suffer: ➢ a personal theft (bag-snatching, pick-pocketing, . . .) ➢ a theft at home ➢ an annoyance ➢ an assault ➢ a fraud ➢ a vandal action

➀ yes ➀ yes ➀ yes ➀ yes ➀ yes ➀ yes

➁ no ➁ no ➁ no ➁ no ➁ no ➁ no

(v118) (v119) (v120) (v121) (v122) (v123)

20. Indicate your agreement or disagreement as regards the following assertions concerning tourism. The tourism: agree disagree ➢ brings money ➀ ➁ DK ■ (v124) ➢ causes inconveniences to residents ➀ ➁ DK ■ (v125) ➢ creates jobs ➀ ➁ DK ■ (v126) ➢ contributes in damaging and dirtying the city ➀ ➁ DK ■ (v127) ➢ helps the development of a multicultural society ➀ ➁ DK ■ (v128) ➢ increases the risk of damages for monuments and artistic beauties ➀ ➁ DK ■ (v129) ➢ increases the prestige of Florence in the world ➀ ➁ DK ■ (v130) ➢ makes the cost of city life increase ➀ ➁ DK ■ (v131) ➢ makes city life more dynamic ➀ ➁ DK ■ (v132) ➢ causes high costs for modernizing of the infrastructures ➀ ➁ DK ■ (v133) 21. There is a proposal about the introduction of new tax concerning a contribution that each tourist should pay for the administration of the city infrastructures. Are you favorable or unfavorable? ➀ favorable ➁ unfavorable DK ■ (v134) 22. Using a score from 0 (at all) to 10 (completely), can you tell how much you agree with the following assertions? Florence. . . : ➢ . . . facilitates communication among people ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ DK ■ (v135) ➢ . . . facilitates cultural activities ➀➁➂➃➄➅➆➇➈➉ DK ■ (v136) ➢ . . . increases aesthetic sensibility and artistic sensitivity ➀➁➂➃➄➅➆➇➈➉ DK ■ (v137) ➢ . . . offers same opportunities of other great cities ➀➁➂➃➄➅➆➇➈➉ DK ■ (v138) 23. Using a score from 0 (at all) to 10 (completely) tell how much, in your opinion, Florence is suitable for: ➢ a child ➀➁➂➃➄➅➆➇➈➉ DK ■ (v139) ➢ an elderly person ➀➁➂➃➄➅➆➇➈➉ DK ■ (v140) ➢ a disabled person ➀➁➂➃➄➅➆➇➈➉ DK ■ (v141)

121

PERCEPTION AND EVALUATION OF THE QUALITY 24. Point out the figure that better represents the “life” in Florence ...

➢ in the past

➀

➁

➂

➃

➄

➅

➆

DK ■

➢ at the present

➀

➁

➂

➃

➄

➅

➆

DK ■

➢ in the future

➀

➁

➂

➃

➄

➅

➆

DK ■

(v142) (v143) (v144)

25. Think about Florence. For each pair of adjectives, point out the position that is closer to the adjective that describes your ideal city in a better way. Please, don’t dwell too much. Tolerant Beautiful Innovator Organized Easy-going Well-known Active Secure Open Appreciated Planner Silent Formal Pleasant Industrious Tidy Courteous Gratifying Fast Livable Hospitable Amusing Lively Relaxing Caring Stimulating Dynamic Comfortable Civil Unique

Intolerant Ugly Conservative Disorganized Quarrelsome Unknown Inactive Insecure Close Despised Improvisator Noisy Informal Unpleasant Indolent Chaotic Rude Disappointing Slow Unlivable Inhospitable Boring Placid Stressful Uncaring Depressing Static Uncomfortable Uncivil Common A

B

C

D

E

F

G

DK ■

(v145) (v146) (v147) (v148) (v149) (v150) (v151) (v152) (v153) (v154) (v155) (v156) (v157) (v158) (v159) (v160) (v161) (v162) (v163) (v164) (v165) (v166) (v167) (v168) (v169) (v170) (v171) (v172) (v173) (v174) (v175)

26. Using a score from 0 (at all) to 10 (completely), tell how much are you satisfied for your life in Florence. ➢ At the present ➀➁➂➃➄➅➆➇➈➉ DK ■ (v176) ➢ One year ago ➀➁➂➃➄➅➆➇➈➉ DK ■ (v177)

122

FILOMENA MAGGINO

2. INDIVIDUAL LIFE CONDITIONS 27. I am going to draw up a list of individual life aspects. Put them in order from that you believe is the most important (1) to that you consider the less important &circ8;. A. Friendship ■ (v178) B. Physical aspect ■ (v179) C. Career ■ (v180) D. Culture ■ (v181) E. Family ■ (v182) F. Earnings ■ (v183) G. Social relationship ■ (v184) H. Health ■ (v185) DK■ (v186) 28. Looking at the following face expressions, point out the face that better represents your happiness condition at the present.

DK ■

(v187)

29. In order to evaluate the importance of social relations in our city, indicate how much support... . . . you receive from

. . . practical ...

. . . psychological . . .

Much Quite Little At all

➢ ➢

Relatives Friends

➀ ➀

➁ ➁

➂ ➂

Much Quite Little At all

➃

DK■

➃

DK■

(v188) (v190)

➢

Neighbors

➀

➁

➂

➃

DK■

➢

Acquaintances and colleagues

➀

➁

➂

➃

DK■

(v192)

(v194)

➀ ➀

➁ ➁

➂ ➂

➃

DK■

➃

DK■

(v189) (v191)

➀

➁

➂

➃

DK■

➀

➁

➂

➃

DK■

(v193)

(v195)

30. and how much support. . . ... you receive from

... practical ...

... psychological ...

Much Quite Little At all

➢ ➢

Relatives Friends

➀ ➀

➁ ➁

➂ ➂

Much Quite Little At all

➃

DK■

➃

DK■

(v196) (v198)

➢

Neighbors

➀

➁

➂

➃

DK■

➢

Acquaintances and colleagues

➀

➁

➂

➃

DK■

(v200)

(v202)

➀ ➀

➁ ➁

➂ ➂

➃

DK■

➃

DK■

(v197) (v199)

➀

➁

➂

➃

DK■

➀

➁

➂

➃

DK■

(v201)

(v203)

123

PERCEPTION AND EVALUATION OF THE QUALITY

31. Using a score from 0 (at all) to 10 (completely), tell how much are you satisfied for your relation with: 0 ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ (v204) ➢ Relatives DK■ 0 ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ (v205) ➢ Friends DK■ 0 ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ (v206) ➢ Neighbors DK■ 0 ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ (v207) ➢ Acquaintances and colleagues DK■ 32. During last month, how many times you carried out the following Indicate zero if no activity was carried out. ➢ Leisure activities (cinema, theater, concert, discotheque, restaurant, pizzeria, . . .) ➢ Cultural activities (museum, art exhibition, cultural meeting, . . .) ➢ Social, politic and voluntary activities, . . . ➢ Sport activities

free-time activities?

■■ ■■ ■■ ■■

(v208) (v209) (v210) (v211)

33. Are you able to satisfy your free-time requirements in Florence? ➀ Yes (go to 36) ➁ No DK■ (v212) 34. If no, which is the predominant reason? (indicate only one predominant reason). ➀ Financial reason ➄ Personal (lack of time, schedule problems, . . .) ➁ Work ➅ Absence of public transports ➂ Family reason ➆ Parking problems, . . . ➃ Health ➇ Others DK ■ (v213) 35. Do you believe that the income of your family is adequate to the demands of your family? ➀ Completely adequate (go to 38) ➂ Partially inadequate ➁ Partially adequate ➃ Completely inadequate DK ■ (v214) 36. Can you indicate the monthly sum that could be added to your income in order to satisfy your family needs? ➀ 0–250 Euros ➁ 251–500 Euros ➂ 501–1000 Euros ➃ Over 1000 Euros DK■ (v215) 37. Comparing the financial situation of your family at the present time with that of the past year, you believe that it is: (v216) ➀ Bettered ➁ unchanged ➂ worsened DK■ 38. Using a score from 0 (at all) to 10 (completely) can you tell how much are you satisfied for your quality of life? 0 ➀ ➁ ➂ ➃ ➄ ➅ ➆ ➇ ➈ ➉ DK■ (v217) 39. and in comparison with one year ago? ➀ better than ➁ the same as ➂ worse than

one year ago

DK■

(v218)

124

FILOMENA MAGGINO

3. INDIVIDUAL DATA 40. Educational qualification: ➀ No one ➁ Elementary certificate ➂ Second level certificate ➃ General Certificate of Education (with no university admittance) ➄ General Certificate of Education (with university admittance)

➅ Post-GCE Diploma ➆ First level degree ➇ Degree ➈ Doctorate (v219)

41. Your professional condition If 1, go to 43, others: go to 44. ➀ Employed ➅ Student ➁ Unemployed in search of a new job ➆ Retired ➂ Unemployed in search of the first job ➇ Unfit for work / invalid ➃ The job will begin in the near future ➈ Military / social service ➄ House working ➉ Other __________________ 42. You are ➀ Full time employed 43. Which is your professional position? ➀ Subordinate ➀➀ Manager ➀➁ Official ➀➂ Employee / staff / clerk ➀➃ Worker or similar ➀➄ Apprentice ➀➅ At-domicile worker

➁ Part time employed

(v220)

(v221)

➁ Autonomous ➁➀ Contractor ➁➁ Autonomous professional ➁➂ Autonomous worker ➁➃ Partner of a cooperative society ➁➄ Cooperating with family firm (v222)

For all respondents Would you accept to be re-interviewed? If so, would you like to indicate the phone number for the new possible contact? ➀ from 8.00 to 9.00 a.m. Home ■■■■■■■■■■■ (v223) Time ■ (v224) ➁ from 9.00 a.m. to 1.00 p.m. ➂ from 1.00 to 3.00 p.m. Mobile ■■■■■■■■■■ (v225) Time ■ (v226) ➃ from 3.00 to 6.00 p.m. Work ■■■■■■■■■■■ (v227) Time ■ (v228) ➄ from 6.00 to 9.00 p.m. ➅ from 9.00 to 10.00 p.m. Other ■■■■■■■■■■■ (v227) Time ■ (v230)

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PERCEPTION AND EVALUATION OF THE QUALITY

For the interviewer ■■■

Length of the interview (minutes)

(v231)

Other persons present during the interview 0

nobody

➀ one

➁ two

➂ three or more

(v232)

➃ minimum

(v233))

Level of collaboration of the respondent ➀ excellent

➁ good

➂ mediocre

ANNOTATIONS

FILOMENA MAGGINO, Researcher and Professor of Social Statistics, Università degli Studi di Firenze, Italy [email protected]

City of Winnipeg Quality-of-Life Indicators PETER HARDI1 AND LÁSZLÓ PINTÉR2 1

Senior Fellow, International Institute for Sustainable Development (IISD), Canada 2 Director, Measurement and Assessment Program, International Institute for Sustainable Development (IISD), Canada

Introduction People value the quality of life (QOL) in Winnipeg. They appreciate the size and pace of the city and its amenities; they are strongly attached to their neighborhoods; and they feel that Winnipeg is a great place to raise a family. They would like to see this QOL maintained for future generations, but they are concerned that it may be fading. At present we can only speculate on the future and that is not good enough. We need to be able to measure our efforts and to know if we are moving in the right direction. We also need measurement to assess the effectiveness of current policies and to design new ones as necessary. People in other places have asked similar questions. A number of towns and cities have established sustainable development as a community goal and developed measurement and reporting systems to measure their progress toward this goal (e.g., Hamilton-Wentworth, Ontario; Seattle, Washington). Sustainable development, like QOL, is a holistic concept that includes consideration of economic development, social vitality, and environmental health. The concept of QOL as used in this project has five distinct parts (Figure 1). Although QOL is nested within the broader concept of sustainable development, there is only one major difference between the two concepts. Sustainable development implicitly refers to the importance of intergenerational equity while QOL does not or only does so implicitly. Both QOL and sustainable development are integral parts of the vision and guiding principles of Plan Winnipeg. Adopted in 1993, Plan Winnipeg is a long-term plan intended to guide Winnipeg into the 21st century. The plan sets out a vision for Winnipeg, which is developed in consultation with community stakeholders. The vision is for Winnipeg “to be a vibrant and healthy city which places its highest priority on QOL for all its citizens.” Progress toward this vision is governed by three guiding principles: quality customer service, sustainable development, and healthy community. The city was conducting a review of Plan Winnipeg and the continuing validity of the “content” of the plan commencing on September 1997. Since the adoption of Plan Winnipeg, the city has learned that to assist in measuring progress toward its vision, a set of ‘signposts’ called indicators need to be identified. By observing the indicators over time, citizens, political leaders, business leaders, and community groups will be able to better understand the impacts of decisions

127 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 127–176. © 2006 Springer. Printed in The Netherlands.

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di

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ty of Quali life

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Fig. 1. Quality of life.

and actions. To assist in the measurement process, the city has decided to develop community indicators as part of the plan review. The development of community indicators is one of the primary goals of this project.

What was the project about? This project was about measuring progress. Assisted by a wide variety of citizens, a QOL indicator framework and indicators were to be developed. As part of this, an action plan outlined the steps necessary for the City of Winnipeg to adopt QOL measures. This project had four main objectives: 1. To identify and actively involve key participants and stakeholders to develop community indicators 2. To establish an indicator development process by which an indicator framework and specific indicators can be developed, periodically reviewed, and refined for the City of Winnipeg 3. To implement the above stated process and develop a set of indicators to be included in the Plan Winnipeg review 4. To develop an implementation plan to establish appropriate administrative systems to support measurement and reporting of progress toward Plan Winnipeg’s vision.

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Who were the participants? This was a collaborative project that involves a partnership between the Strategic Planning Division of the City of Winnipeg and the Measurement and Indicators Program of the International Institute for Sustainable Development (IISD). The lead agency for this project was the Strategic Planning Division and it was responsible for overall project direction and product delivery. IISD provided support and expertise throughout the project with specific responsibilities linked to indicator development.

How was the project initiated? This project was developed on the basis of the mutual interests of the City of Winnipeg and IISD at pursuing an indicator development project for Winnipeg.

What are the outputs? The project has two main outputs: 1. An indicator framework for the City of Winnipeg that relates measurement of progress toward the community’s vision of Winnipeg to the City of Winnipeg’s overall performance measurement system. 2. A final report that includes: (1) a framework and set of community indicators (approximately 20–30); (2) a subreport regarding the assessment of data availability; and (3) a generic implementation plan to address data collection and institutionalization of the indicator framework describing possible approaches that the city may choose to carry out the measurement of the community indicators.

What does this report represent? The body of the report begins in the next section on “Process,” with a discussion of the process used in arriving at a set of issues that stakeholders found important to the QOL in Winnipeg. We then introduce the processes of indicator development and aggregation. QOL framework is presented in the section under “quality-of-life framework.” The section on “a sample list of quality-of-life indicators for the City of Winnipeg” examines the availability of data to create indicators for these issues. The last section, “Implementation Plan,” presents an implementation plan for creating a set of indicators and aggregations, and comments on institutionalization.

Process What is a quality-of-life framework? A framework is a structure or tool that is used to provide support or order to a group of ideas. When applied to issues, a framework can assist in providing a comprehensive evaluation and in clarifying many issues. A good framework helps to

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provide unique insights into issues. A framework can be very simple or complex. For example, a set of issues can be grouped by the sector of the economy, environment, or the geographic location that they mainly influence. The creation of a QOL framework includes the development of a structure of issue categories to order QOL issues. This is followed by the generation and selection of issues. The selection of QOL indicators to measure selected issues is the last stage of framework development.

What is a quality-of-life indicator? Indicators are signs or signals of complex events and systems. They are bits of information pointing to characteristics of systems or highlighting what is happening. Indicators are used to simplify information about complex phenomena, such as sustainable development or, in this case, QOL, in order to make communication easier and quantification possible. An indicator can be a variable (e.g., the total amount of organically farmed products) or a function of variables (e.g., a ratio such as amount of recycled material vs. total amount of solid waste). An indicator can be a qualitative variable (e.g., safe–unsafe neighborhood, participatory–nonparticipatory decision-making), a ranking variable (e.g., best or worst training program, lowest or highest mortality rate), or a quantitative variable (e.g., energy use in kilowatt hours/year). Although quantitative indicators are the most widespread, qualitative indicators are also important when the issue to be measured is nonquantifiable (e.g., cultural values), when the information is based on opinion surveys (e.g., yes or no answers to questions such as “Are you satisfied with your situation?”), when quantitative information is not available (data are missing), when high costs prohibit the use of quantitative indicators, or when a simple signal, such as a red light on an instrument panel or dashboard, is sufficient to initiate action. In practice, indicators can be distinguished as system indicators or performance indicators. System indicators summarize sets of individual measurements for different issues characteristic of the human/social system and the ecosystem, and communicate the most relevant information to decision-makers. System indicators are based on technical and scientific insights whenever possible. However, due to the uncertainties of the natural and social systems this is not always possible. Both science and the policy process determine the standards and benchmarks to which indicators are related. Indicators are a product of a compromise between scientific accuracy and the needs of decision-making, and urgency of action. Performance indicators are tools for comparison, incorporating a descriptive indicator and a reference value or a policy target. They provide decision-makers with information on how they are doing with regard to policy goals.

What is a quality-of-life index? Another type of indicator, presenting highly condensed information obtained by aggregating data, is called an index. Decision-makers often ask for a very limited number of indexes that are easy to understand and use. A typical example of an

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index is the gross domestic product (GDP). To develop an index, the different indicators contained in the index need to be weighted according to their relative importance. In the case of the GDP, the weighting factor is the monetary value of the goods produced. However, when considering environmental, social, and institutional aspects, this becomes a major problem since many of those goods cannot presently be given a monetary value. Indexes are also limited in their analytical power since they simplify the link between the index and the real world.

How is an indicator developed? Developing an indicator involves a process that moves from the general to the specific and then back. We begin with a broad issue category, for example, individual well-being. This category is then divided into subcategories of issues or smaller groups of issues, such as safety or health. In the division of categories, subcategories, and issues there is a significant amount of choice. The categories and subcategories for the issue framework are chosen by the project team to represent QOL as comprehensively as possible. Stakeholder participants select the issues that they consider most important within each of these categories. For example, issues under the safety subcategory might be crime or accidents. Following the decisions of stakeholders the project team performs a data availability assessment to determine whether sufficient data are available to create indicators to measure the issues that the participants felt were most important. Data related to the crime or accident issue might include the number of transport-related deaths per 1000 population, the number of murders per 1000 population, the number of fires per 1000 homes, etc. Indicator development proceeds with the selection of one or more of these available pieces of data based upon a number of criteria. The result is indicators that may be based on one or more pieces of information with relevance to the crime and accident issue. If fewer indicators are desired, these indicators can be aggregated to form a single indicator on the safety subcategory. This indicator may be further combined with other subcategories to provide a single aggregate indicator or index for individual well-being. In this project the development of QOL framework followed a somewhat more complex, but a largely similar, path.

How are indicators reported? There is no golden standard for the preparation of QOL or sustainable development reports, but there are some general rules of thumb that can provide help in the preparation and presentation of indicators and reports. Figure 2 provides an example of a general template for indicator reporting. Clarity of communication is a basic requirement for the presentation of indicators. They should be presented graphically, accompanied by brief explanations, using nontechnical language. Simple symbols can be used, for example, to link the particular indicator to the overall life quality framework or to identify the direction of change. Text, symbols, and charts are the basic building blocks, accompanied by appropriate references and if necessary background numbers, usually in an appendix.

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Unemployment down

Clear title and place of issue in indicator framework

Figure to symbolize improvement, decline, no change, or inadequate data Why is unemployment an issue? Rationale for including issue in indicator set

What are the current trends?

Explanation of current trends, including their statistical probability

Unemployment in City X between 1970−1998

% of workforce

8

City X National average

Chart title providing detail

Legend

6 Targets for future 4

Clear unit of measure

2 Trend lines for city and e.g., national averages for comparison 0 1970

1980

1990

1998

2000

Time series data Clear unit of measure

Source and definition: What do the numbers mean?

What are the reasons for this trend?

What are our options?

Identification of data source for further reference and definition of indicator

Explanation of the indicator, including its statistical significance and reliability

Identification and explanation of policies and processes influencing the indicator; linkage to other issues and indicators Identification of possible policy directions and alternatives

Fig. 2. Example of general template for indicator reporting.

A QOL report would of course include a number of indicators. Although these indicators and their accompanying analysis may appear on separate “indicator sheets,” it is particularly important to point out that most of them represent processes and phenomena that are strongly linked. Beyond pointing this out in general, it is even more important that every indicator is linked to other indicators, policies, and the web of environmental and socioeconomic matters that have a direct or indirect influence on it. Again, this can be done both graphically by showing the place of the indicator in the comprehensive QOL framework and in the analysis. One of the basic functions of indicators is to provide a comparison. This comparison can be based either on targets, benchmarks, or performance in the past. In

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fact, it can be based on all of this. The indicator chart should be based on time series data, thus providing an opportunity for comparing development and dynamics over time. If an accepted target value is known it should be added to the chart so that readers can make an assessment of progress, the direction of current change, and the distance from the target. In addition, comparable trends from either other jurisdictions or other scales or locations can be added to provide a third layer of comparability. This may be either figures from the national or global scale or examples from other cities that are well known by the public. While there are no perfect examples to illustrate this sort of reporting, there are many indicator reports that integrate some of the key points. An interesting example is the report published by the Pierce Country Department of Community Services in the State of Washington (see sample pages in 6).

Framework Development At the outset of this project, a number of sustainable development indicator frameworks were considered for organizing QOL issues and the development of related indicators. The City of Winnipeg met several times to discuss possible indicator frameworks with IISD. IISD produced a paper for the city that surveyed indicator frameworks. Among the frameworks discussed was the multiple-asset framework of the World Bank; this framework is organized around the concept of measuring the wealth of society through the division of resources into four categories: (1) human capital, (2) human-made capital, (3) social capital, and (4) natural capital. The Prairie Ecozone section of the provincial State of the Environment Report for 1997 provides an example of a similar framework and division of assets: natural resources, human-made capital, community assets, and individual well-being. Several requirements were chosen to guide framework development: 1. The framework should be holistic, that describes the entire urban system. 2. The framework should maintain some level of compatibility with existing frameworks in City of Winnipeg documents (e.g., Plan Winnipeg), and the framework used in provincial sustainable development reporting. 3. The framework should facilitate the selection of indicators that are relevant to the community and at the same time provide feedback to city council and the city administration. The resulting framework (Figure 3) combined elements of the multiple-asset framework and the provincial State of the Environment Report. These were adapted to the needs of the City of Winnipeg and the issues raised by citizens during public consultations.

Stakeholder Participation Selection of stakeholders. The City of Winnipeg and IISD held a number of joint meetings that discussed the type and form of stakeholder participation that would be required for the development of the issue framework. Amongst the criteria that were eventually used in selecting participants was a need to maintain gender equality and to have participation from a relatively broad group of citizens that included

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Quality of life

Issue categories

Issues

Indicators

Data

Fig. 3. Quality-of-life framework.

representatives from labor, public, private, and civil society. In order to maximize the representation of different points of view, people from “umbrella groups” were chosen where possible, including members of neighborhood communities, the business community, professional associations, unions, educational organizations, indigenous groups, and nongovernmental organizations (NGOs). Issue identification and prioritization. A multistakeholder process conducted through a focus group meeting was used for issue selection (Figure 4). Selected participants were invited to attend a daylong meeting to suggest and rank issues falling under the different categories that had been assembled. Participants were provided with an information packet containing a number of documents that included an issue paper on frameworks and indicators in the context of sustainable development reporting and a description of the process. The focus group meeting occurred on November 6, 1997, at IISD. There were a total of 29 attendees (Appendix A) including personnel from IISD and the City of Winnipeg. Twenty participants represented different communities and interests within Winnipeg. The framework for organizing indicators had four parts that collectively ensured that all aspects of sustainable development were addressed. Four main categories of issues and indicators were created. These were: (1) urban environment, (2) human-made capital, (3) community assets, and (4) human well-being. The framework also reflected the equitable distribution of assets within and between generations as an overriding concern of sustainable development. A question and answer session provided an opportunity for discussion by participants before the process began (Appendix B). Generation and listing of the first set of issues, clarification of the suggestions, as well as the individual ranking of issues was done by breakout groups.

CITY OF WINNIPEG QUALITY-OF-LIFE INDICATORS

Whole group

Breakout groups

Introduction and statement of task

Silent generation of quality-of-life issues

“Round robin” listing of issues

Group discussion and clarification of issues

Individual selection and ranking of the top issues from the list

Integration of results— preliminary grouping of issues

Stakeholder survey

Draft indicator framework survey provides stakeholders the opportunity to identify their top two issues and provide

Data availability assessment

Identification of quality-of-life indicators

Implementation plan

Fig. 4. Multistakeholder process.

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The results of the brainstorming sessions were presented at a plenary session. Although reranking of the issues by the plenary was the next step planned, the participants felt that there was insufficient time left for regrouping the issues, eliminating overlaps, and providing justification for selection. The group as a whole agreed to adjourn the meeting, to leave time to combine the two lists and identify the next step in the process. Following the meeting, the city contacted all workshop attendees for their comments. Based on the feedback from participants, the city decided to modify the process and use a series of focus groups and surveys to ensure a broader representation of the community. In the interim, the Manitoba Round Table (RT) on Environment and Economy made a decision to focus its efforts on urban sustainability and initiated discussion with the city on collaboration related to the reporting of sustainable urban QOL indicators. A draft issue framework survey, prepared by IISD and the city, was sent to participants and others who indicated an interest in participating but were unable to attend on the day of the workshop. The survey contained 160 issues identified by workshop attendees, which had been sorted into both categories and subcategories. These categories and subcategories were produced after a review done by the working group that considered a number of current municipal QOL sustainable development reports in North America. This was done in order to ensure a comprehensive framework was developed. Based on the review and the discussions to date, the category human-made capital was renamed urban economy while the human well-being category was split into two new categories individual well-being and community leadership and pride. The addition of subcategories and example issues enhanced the descriptions for each category. A review of other City of Winnipeg documents, surveys, and focus group reports provided further public input on issues of concern for the survey and the framework. Participants were asked to provide comments and suggestions regarding the categories and subcategories, and to choose their top two issues from those suggested, or to suggest a new issue as a choice (Appendix C). The categories, subcategories, and the top two issues selected by participants provided the QOL issue framework for the city (Table 1).

Indicator development Development of a preliminary set of indicators began with the assignment of indicators to the top two issues identified in the survey results, where possible. Using a set of indicator selection criteria, the list of indicators was narrowed. Although six selection criteria are defined here, this list is by no means exhaustive. 1. Policy relevance. Is the indicator linked to one or several issues around which key policies are formulated? Indicators of sustainable development are intended to improve the outcome of decision-making on levels ranging from individuals and communities to the province, country, or world. Unless users can see the connection between the indicators and the critical decisions and policies, it is unlikely to motivate action. It is for this reason that appropriate explanations of the implications for sustainable development and linkages to other issues are included in the discussion of indicators.

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Table 1. Quality-of-life framework. Category

Subcategory

Urban environment This category includes the natural and built environment. The natural environment refers to resources such as water, air, and green space. The built environment includes the infrastructure necessary to support urban life, for example, buildings, streets, sewers, powerlines, communications equipment.

Natural environment: the physical elements that are both living and nonliving utilized by residents of Winnipeg.

●

Land use management: activities and outcomes associated with planning, allocation, and regulation of land in Winnipeg.

●

Infrastructure and services: includes the planning, construction, and maintenance of services or physical structures that assist in the everyday activities of people. Consumption and conservation: includes the physical consumption of resources and material and the efforts or alternative activity to optimize efficiency. Employment: means jobs and people. The type, sector, nature, and value of work required in the community; and the characteristics of the labor pool, including age, skill set, availability, and status of employment. Municipal finances: the ways city revenue is earned and spent; ways decisions, or choices are made in managing finances; criteria used to determine consumption, spending, and investment; evaluation of tax and other revenue-generating programs or activities.

●

Urban economy This category includes not only the private and public funds expended in the city, but also the “economic engine” that produces capital. This comprises the sum of all work created in Winnipeg, and the processes, assets, and knowledge that support job creation and economic development.

Issues

●

●

●

●

●

●

●

● ●

Clean city Water quality and supply/ quality access to drinking water

Vibrant core/vibrant downtown/downtown area/vacancy Urban sprawl

Deterioration of infrastructure Well-functioning infrastructure and its maintenance

Water conservation/ conservation water/energy Waste minimization

Quality of jobs/meaningful employment Brain drain and out-migration of professionals, technicians, and artists

Financial management Over reliance of the City of Winnipeg on property taxes

(Continued)

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Table 1. Quality-of-life framework––Cont’d Category

Subcategory

Economic vitality: public and private institutions and activities that promote economic movement in the community and create new industry, business growth, and development. Community assets Housing: provision of The basis for Winnipeg’s overall basic housing community assets is its needs in an equitable, people and its demographic accessible, and efficient profile. Cultural identity manner, availability of and heritage are values adequate and affordable that are part of how housing both for people rate their QOL. purchase and rent. Community assets also include our institutions, Culture, arts, and such as a well-functioning entertainment: arts, health and education beliefs, institutions, and system. other human activity or thought; opportunities for practicing them; promotion of artistic and cultural life within and outside the city; commitment of government and private sector to support diverse cultural activities. Recreation and leisure: conditions for actively spending free time for passive or active leisure; quality and availability of sport, recreation programs, and hobby opportunities. Government services: activities and initiatives to provide for basic needs of people and the community. Includes the number and quality of services available for residents in Winnipeg.

Issues ●

●

●

●

Attracting diverse businesses/diverse economy Environment supportive of small businesses/fostering local community–based business Affordable housing/affordable, integrated, and accessible housing Protection of quality of housing stock

(no specific issue has been identified)

●

●

Flourishing and well-established community centers Availability to sports facilities

●

Access to public transportation/transportation (equal and accessible options)

●

Logical urban planning

CITY OF WINNIPEG QUALITY-OF-LIFE INDICATORS

Individual well-being This category includes both psychological and physical well-being of Winnipeg residents.

Education: community investment in the resources required to promote mechanisms and institutions that provide for quality and accessible knowledge and learning opportunities. People: population characteristics and demographics; ethnic diversity and aboriginal affairs. Neighborhoods: community networks and opportunities for interaction and cooperation; grassroots institutions and community impact. Safety: physical and perceived security of individuals both in private and public settings; conditions necessary to preserve and protect their integrity and property. Equity: social justice and human rights extended to all. This includes fairness and equal access to services by all citizens in Winnipeg. Education: acquiring and using quality skills and knowledge through formal and traditional channels; personal levels of skills and knowledge. Wealth: tangible assets of material and financial security. Health: mental and physical well-being of individuals.

●

●

●

●

●

●

●

●

●

●

● ● ●

● ●

●

●

Community leadership and pride

Leadership and governance: the format, style, and

●

139

Postsecondary education and training Public education (re: costs)

Opportunities for aboriginal people Human cultural mosaic

Informal and formal volunteerism Sense of community and neighborhood

Personal and property security for people Crime and safety

Measures of social justice/equity Basic physical needs met for all

Education Quality education Inclusive education

Income Material comfort at affordable price Health access to and within health care services Water quality and supply Governance with strong and local accountability (Continued)

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Table 1. Quality-of-life framework––Cont’d Category

Subcategory

Cities are changing all the time. A shared purpose and a solid understanding within the community of its past and its future direction exemplify community leadership and pride.

effectiveness of leadership and management of the community’s affairs; a strong vision of where the city should be going and how it should get there; institutional guarantees for participating in decisionmaking; accountability of institutions; elected and appointed officials. Image and identity: perception of the community and the role of individuals in it. How people in Winnipeg feel about their city and how people outside the city perceive it to be? Citizenship: active participation in community affairs; sense of belonging and privileges.

Issues ●

Responsive, respected, and trusted governance

●

Improved community image Self-image Distinctive character

● ●

●

●

Sense of individual empowerment Participation and belonging

2. Simplicity. Can the information be presented in an easily understandable, appealing way to the target audience? Even complex issues and calculations should eventually yield clearly presentable information that the general public understands. 3. Validity. Is the indicator a true reflection of the facts? Were the data collected using scientifically defensible measurement techniques? Will one arrive at the same result if two or more measurements of the indicator are made? Methodological rigor is needed to make the data easily understood by all audiences. 4. Data availability. Are good quality time series data available at a reasonable cost or is it feasible to initiate a monitoring process that will make the information available in the future? Information tends to cost money, or at least time and effort from many volunteers. 5. Representativeness. Is the indicator about a very narrow or broad QOL issue? The list of potential indicators is endless. For practical reasons, indicators that combine information on a range of issues should be preferred. For example, average life expectancy is a useful indicator of human health that aggregates information of many trends that influence this single outcome, such as incidence of diseases, lifestyle, the rate of fatal accidents, or even the effectiveness of the health system.

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6. Sensitivity. The scope of a single indicator is usually limited, even if it satisfies the criteria of representativeness, if we compare it with the issues decisionmakers have to address. Staying with the example of human health, while life expectancy measures an overall outcome, there are measures in the QOL indicator set that will describe factors that influence health, whether it is child/infant mortality, the availability of hospital beds, or toxic substances in the environment. In cases like this, finding a way to aggregate associated measures will help create an overall picture about a complex issue, such as health, and facilitates its communication to the public and policymakers. Aggregation is an important tool, but it is not without risks, and requires careful consideration of what is to be included in an aggregate measure and with what weight.

Quality-of-Life Framework QOL framework contains five main categories with numerous subcategories. The framework and the definitions for these categories and subcategories are provided in Table 1. This is the same framework that was given to survey recipients with the exception that examples were provided for issues within the different categories and subcategories. Here the issues under each subcategory are the top two issues selected by the participants. The selection of these issues by stakeholders completes the development of the QOL issue framework.

A Sample List of Quality-of-Life Indicators for the City of Winnipeg Based on the results of the issue identification exercise and the data assessment, a list of draft indicators was compiled. The list is clearly preliminary, given the limited scope of stakeholder participation in the issue identification process and gaps in the quality and availability of data. Nevertheless, both the issue identification and the data assessment exercise led to some concrete information in some, though not all areas. Indicators selected satisfy both the criteria of data availability and reliability as well as relevance for stakeholders. In some cases the lack of data or the uncertainty in the definition of issues allows only educated guesses at best and calls for additional data collection (e.g., neighborhoods, citizenship). Table 2 contains indicators that describe some key aspects of an issue identified and have at least some underlying data and data collection infrastructure. The indicator accompanying an issue is obviously not the only possibility to measure that issue. In most cases there are options, for example, to express an indicator in per-capita terms or in terms of economic output, and so on. Finding the best way of expressing an indicator depends mainly on the policy context it is used in and the associations the public makes with respect to the particular issue. If the concern is pollution, one can simply select the change in pollution levels or emissions over time. However, if there is specific interest in the volume of pollution we produce compared with the rate of economic activity, expressing it in terms of

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pollution per unit of economic output may be more appropriate. Selecting the indicators will require further input from stakeholders and data managers, for which Table 2 can be a starting point. Table 2. Suggested quality-of-life indicators. Category: Urban Environment Subcategories and Issues Natural environment ● Clean city ● Water quality and supply/ quality access to drinking water

Suggested Indicators Air quality index

Number of good air quality days

Water quality index

Percentage of biological oxygen demand (BOD) Aquatic invertebrate population in city streams Pesticide use

Frequency of environmental accidents

Number of contaminated sites Land use management ● Vibrant core/vibrant downtown/downtown area/vacancy ● Urban sprawl

Urban sprawl

Urban forests Consumption and conservation ●

Water conservation/ conservation water/energy

Automobile ownership/registration Recycling rate

Definitions As defined in Manitoba’s State of the Environment Report, 1997 Defined as the number of good air quality days per year or the number of days with air quality in the “good range” As defined in Manitoba’s State of the Environment Report, 1997 Defined as the average BOD reduced in wastewater. Defined as the relative abundance of aquatic invertebrate species in city streams. Volume of pesticides used by privately registered applicators (liters). Defined as the number of environmental accidents in Winnipeg and St. Boniface. Defined as the number of contaminated sites in Winnipeg. Defined as the ratio of number of new homes built in rural municipalities adjacent to Winnipeg to the number of new homes built within Winnipeg. Size, variety, and condition of forests Defined as the ratio of automobiles per 1000 population. Percentages of paper, glass, and aluminum disposed

CITY OF WINNIPEG QUALITY-OF-LIFE INDICATORS ● Waste minimization

Average waste disposal Natural gas consumption

Electricity consumption

Water consumption

Energy consumption

Infrastructure and services ● Deterioration of infrastructure ● Well-functioning infrastructure and its maintenance

Expenditure on road infrastructure

Infrastructure expenditure

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which are recycled. Volume/capita Defined as natural gas consumption (cubic meters) per household. Defined as electricity consumption (kilowatt hours) per household. Defined as the average water consumption for all uses (liters per day per person). Defined as the total energy usage (mega joules) per annum per person. Defined as per-capita expenditure in dollars on roads. (Should include capital and maintenance expenditure on all roads within the city’s vicinity.) Defined as per-capita expenditure in dollars on infrastructure.

Category: Urban Economy Subcategories and Issues

Suggested Indicators

Employment Basic labor force ● Quality of jobs/meaningful employment ● Brain drain and Unemployment rate out-migration of professionals, technicians, and artists Employment growth

Municipal finances Government income ● Financial management ● Over reliance of the City of Winnipeg on property taxes Capital expenditure

Change in income

Definitions Measures the basic labor force/per population ratio. Defined as the average proportion of unemployed as a fraction of the workforce. Defined as the average annual growth rate of the number of employed persons, aged 15 and above. Defined as the total government income in dollars annually, both capital and current divided by population. Defined as the government capital expenditure in dollars per person. Defined as the average annual change in real per-capita income. (Continued)

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Table 2. Suggested quality-of-life indicators––Cont’d Category: Urban Economy Subcategories and Issues

Suggested Indicators

Definitions

Property tax rate

Defined as the percentage of the market value of the dwelling unit, which is collected as annual property tax. Defined as GDP by industry.

Economic vitality GDP by industry ● Attracting diverse businesses/diverse economy ● Environment supportive of small businesses/fostering local community–based business Category: Community Assets Subcategories and Issues

Suggested Indicators

Definitions

Housing ● Affordable housing/ affordable integrated and accessible housing ● Protection of quality of housing stock

Average household size

Defined as total population divided by total household. (Can be used to determine demand for housing.)

Household formation rate

Defined as rate of growth of numbers of households or the sum of population growth rate and the estimated percentage decline in household size. (Used as a prime indicator for housing demand.) House price to income ratio Defined as the ratio of the median market price of a dwelling unit and the median annual household/ family income. House rent to income ratio Defined as the ratio of the median annual rent of a dwelling unit and the median household/family income of renters. (This indicator may be key measure of housing affordability.) Mortgage affordability Defined as proportion of households who are

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Excessive housing expenditure

Inadequate housing

Culture, arts, and entertainment (no specific issue has been identified) Recreation and leisure ● Flourishing and well-established community centers ● Availability to sports facilities Government services ● Access to public transportation/transportation (equal and accessible options) ● Logical urban planning

Monument list

eligible for and can afford the maximum loan on a median priced formal sector house. Defined as the proportion of households in the bottom 40% of incomes who are spending more than 30% of their incomes on housing. Defined as the proportion of dwellings that are deemed to be inadequate or in need of major repairs. Defined as the number of buildings in the city on the heritage or monument lists

Recreation facility use

Indoor and outdoor facility use by groups of population

Government employees

Defined as the total government employees per 1000 population. Defined as the ratio of total expenditure in dollars by the government on infrastructure services. (Includes operations, maintenance, capital expenditures, on physical infrastructure such as roads, railways, water supply, electricity, and garbage collection and social infrastructure such as health and education expenditure.) Defined as the total expenditure, both capital and current, public and private, on social services in dollars per person. Defined as expenditures by educational level, source of funds, and level of government

Infrastructure expenditure

Expenditure on social services

Education ● Postsecondary education and training

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Public expenditure on education

(Continued)

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Table 2. Suggested quality-of-life indicators––Cont’d Category: Community Assets Subcategories and Issues

Suggested Indicators

Definitions

Public education (re: costs) Neighborhoods ● Informal and formal volunteerism ● Sense of community and neighborhood People ● Opportunities for aboriginal people ● Human cultural mosaic

University degrees

Number of university degrees conferred per person.

●

No suitable indicator has been identified

Migration rate Household type

Aboriginal people

Net migration to and from the city. Percentages of households with more than one adult with no children, single-parent household, more than one adult and children, one person only. Basic socioeconomic profile

Category: Individual Well-Being Subcategories and issues

Suggested indicators

Definitions

Safety ● Personal and property security for people ● Crime and safety

Crime rate

Number of reported crimes (number of victims, male and female) annually per 1000 population (sexual crimes, family violence, murder, and theft). Defined as the proportion of deaths per 1000 population from transport-related causes. Defined as proportion of road fatalities who are pedestrians Defined as the number of medical services per 1000 population and per-capita cost by gender. Defined as the proportion (in percentages) of

Transport fatalities

Pedestrians fatally injured

Health Medical services ● Health access to and within health care services

●

Water quality and supply

Infant/child mortality rate

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children by gender who die before reaching their fifth birthday. Education Education ● Quality education ● Inclusive education

School enrollment rates

●

Equity ● Measures of social justice/equity ● Basic physical needs met for all

The number of students at a specific level of education, as a percentage of population at that level (using age to determine the level) or the percentage of children of eligible age by gender who are enrolled in primary and secondary education.

Life expectancy at birth

Defined as the number of years a newborn infant would live if prevailing patterns of mortality at the time of birth were to staythe same throughout the child’s life. (This indicator is used for computing the Human Development Index at the city level). Social safety Financial and other support provided for disadvantaged groups. Family income Total families income by annual income groups, average, low, and median annual income. Personal disposable income Employment disposable income by gender and work activity. Personal saving rate Percentage of real income

Wealth ● Income ● Material comfort at affordable price

Category: Community Leadership and Pride Subcategories and issues

Suggested indicators

Definitions

Leadership and governance ● Governance with strong and local accountability ● Responsive, respected, and trusted

Diversity of elected officials

Measure the extent to which different groups (racial, gender) are actively represented per 1000 population (Continued)

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Table 2. Suggested quality-of-life indicators––Cont’d Category: Community Leadership and Pride Subcategories and issues governance

Suggested indicators

Definitions

Voter participation rate

Measure number of registered voters as active participants or defined as the percentage of adult population (having reached voting age) who voted in the last municipal election. Population percentage by home languages spoken

Image and identity Home language ● Improved community image ● Self-image ● Distinctive character Citizenship No suitable indicator ● Sense of individual has been identified empowerment ● Participation and belonging

Data Availability Assessment Report The purpose of the data assessment section is to help identify and describe data to be used for the empirical analysis of QOL issues. Assessing QOL requires vast amounts of statistical data to construct indicators related to key issues. Typically, the necessary data required for measuring the various components of QOL may not be compiled. There is the need to assess the availability of data across the broad categories and subcategories that constitute a QOL framework. These data will strengthen the quantitative basis for the assessment of the “State of Winnipeg,” including economic, demographic, environmental, and other factors. Such data are usually collected by major governmental statistical agencies and institutions, some private and public organizations and institutions, NGOs, and others. Data are needed for longer historical periods, including details on the data collection methods. The availability of historical data will help construct indicators and assess the effectiveness of past and present policies that collectively and individually determine the QOL. It allows for trends to be identified and priorities addressed. The long-term objective of the data assessment is to assist in designing programs to improve the quality and availability of harmonized data sets consistent with important issues in measuring QOL for Winnipeggers. Based on the assessment, recommendations will be provided to fill data gaps and increase the efficiency of existing information, measurement, and reporting systems. The city’s information system has many elements necessary for the analysis of holistic concepts like QOL. Although there are many existing data sets that are validated and up to date, their relevance for the measurement of QOL has not

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been determined. Data are often collected around narrow issues that may or may not have direct linkages to QOL. Lack of necessary data on one hand and availability of data irrelevant from the perspective of QOL creates several potential data constraints. These constraints will have significant influence on the indicators selected. In response to the data constraints in measuring QOL, this project also compiled a directory of data sources and contacts within the City of Winnipeg and other levels of governments and organizations. This database will contribute to the identification of data gaps and promote solutions that address other data constraints. The long-term mandate of the data assessment is making data more accessible to the wider public on sustainable development or QOL issues. This section of the report is divided into four parts, which: (1) discusses the methods used to assess data availability; (2) presents the results of the data availability assessment; (3) discusses the results and data management issues identified; and (4) provides recommendations with respect to the establishment of a QOL indicator framework based on data availability, respectively.

Methods of Assessment Based on the QOL framework that was generated by the project team and using the broadly defined categories and subcategories as guides, data sources for the City of Winnipeg, other governmental organizations, community organizations, and business groups were identified and interviewed using a standard survey format. The assessment focused on determining information for the following components, which are found in the data availability study work plan (Appendix D): 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Category and subcategory Data sources Time period of data/record Unit of measurement Frequency Data collection method Data storage format Geographic coverage Restrictions Cost

Based on these components a form and an electronic database was designed that would allow entering the necessary information regarding the data availability assessment. Potential data sources were grouped into two main areas: (1) City of Winnipeg sources and (2) others, including federal and provincial governments, NGOs, educational institutions, and special interest organizations. 1. City staff were identified and contacted by phone and asked to comment on data availability based on the above components. In addition, staff were asked

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to comment on collateral activities or initiatives related to data management. Major data sources were identified in the following departments: Assessment Department Business and Liaison and Intergovernmental Affairs Civic Buildings Community Services Department Corporate Finance Corporate Services Department Land and Development Services Department Parks and Recreation Department Social Services Department Streets and Transportation Water and Waste Department Winnipeg Hydro Winnipeg Police Service Winnipeg Transit 2. With respect to other organizations the identification of data sources took place in two phases. The first phase was to consult Statistics Canada, specifically scanning the CANSIM database. Wherever data sets fit into any of the broad categories/subcategories this was noted and then later entered into the database. This gave us an insight as to the type of information/data that is housed by Statistics Canada, which could be used to measure QOL. The second phase was to list other key data sources that were identified in the work plan. Some of the major key sources that assisted with data assessment are as follows: Canadian Business Center Centra Gas Coalition to Save the Elms Dafoe Library, Government Document Section, University of Manitoba Environment Canada Friends of Bruce Park Institute of Urban Studies Manitoba Agriculture, Technical Services and Training Manitoba Bureau of Statistics Manitoba Education and Training Manitoba Environment Manitoba Hydro Manitoba Natural Resources Manitoba Naturalists Society Manitoba Product Stewardship Program Manitoba Public Insurance (MPIC) Manitoba transport, Driver and Vehicle licensing Manitoba Urban Affairs Probe Research Inc. Social Planning Council of Winnipeg Zoology Department, University of Manitoba Winnipeg Police Service

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The preliminary list of key data sources contained about 50 institutions. Nearly half of them have not provided information and/or do not have any relevant data. Annual reports produced by the City of Winnipeg and other publications including government documents from the Dafoe Library assisted in the identification of other data sources as well as providing actual data. Face-to-face meetings proved to be the most effective means of obtaining information regarding data availability. The Dafoe Library was also used to get other Statistics Canada information, which is not part of CANSIM. The Canada Year Book was used to obtain extra information on some of the issues and to identify other potential information sources.

Results/Findings The results discussed below are based on the information contained in the data availability table in http://www.co.pierce.wa.us/pc/abtus/ourorg/comsvcs.htm. Category/subcategory. The data availability assessment identified a large number of data that relate to the QOL framework. At an aggregated level of broad QOL categories, data match to a large extent the issues identified through the focus group meeting. However, at the issue or subcategory level a number of data gaps were observed. This can be illustrated by examining the difference between the sets of issues produced by the stakeholders (section on “Quality-of-Life Framework”) and the data identified in the assessment report (http://www.co. pierce.wa.us/pc/abtus/ourorg/comsvcs.htm). Major data gaps exist for leadership and governance, image and identity, culture, arts, and entertainment, neighborhoods, citizenship, and equity. This will have an impact on determining a final set of indicators used to measure QOL. Table 3 is a summary of data identified by data sources at the broad category level of the framework. To gain comprehensive knowledge of all the details of all data available based on the survey, please refer to http://www.co.pierce.wa.us/pc/abtus/ourorg/ comsvcs.htm. Data sources. The data availability assessment revealed that a wide range of public and private organizations, including those highlighted above, are important sources of data for the City of Winnipeg. In many cases these organizations stated that Statistics Canada was their primary data source. Data for Winnipeg were mainly from the Census Track Profile (A & B) put together by Statistics Canada. Our findings reveal that it is important to scan through Statistics Canada’s database when assessing data or gathering the necessary information about QOL. For example, the recent demographic profile produced for the City of Winnipeg used Statistics Canada census data. Another statistical data organization is the Manitoba Bureau of Statistics; they collect data on food prices for Winnipeg, Brandon, and 17 northern communities. They also gather data for other institutions and agencies, beyond what Statistics Canada collects, but most of these data are confidential and may not be available to the public. Examples include data for the Canada Mortgage and

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Table 3. Data identified by existing data sources. Broad Categories

Subject Areas

Urban environment

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Urban economy

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Agriculture/farmland Air quality Automobile Building permits Chemicals Electrical Energy Forest Land Minerals Natural areas and parks Pesticide Recycling River water quality Road conditions Sewer Traffic Transportation Waste Water New housing Natural gas Weather Wildlife Business bankruptcies Businesses Consumer bankruptcies Consumer Price Index Debt Direct and indirect taxes Employment Expenditure Financial performance GDP Industries Investment Manufacturing Part-time and full-time workers Professional services Property taxes Revenue, basic labor force Store sales Subsidies Transfer payments Unemployment, wages and salaries Vocational training

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Community assets

● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ●

Individual well-being

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ●

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Aboriginal persons Demographic characteristics Dwelling characteristics Enrollments in educational institutions Ethnic origins Family characteristics Grants to educational institutions Households Housing Housing rent, starts, stocks, selling price Immigrants and refugees Indoor and outdoor facilities Investment in housing Languages, education (postsecondary, primary, elementary, universities) Leisure activities Marital status Medical services Migration Mortgage-interest rate, loans Population characteristics Public and private schools Public transportation Recreation Religion Revenue and expenditure of schools Seniors Automobile injuries, theft, vandalism, collisions Crimes Disabled Divorces Family income Health care Homicide Hospitals—number of beds, grants, expenditure Household characteristics Infant mortality rates Life expectancy Mental health Personal savings, income Revenue Robbery Sexual assaults Single parents Suicides Universities/colleges enrollments and diplomas granted Visible minorities Vital statistics Youth (Continued)

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Table 3. Data identified by existing data sources––Cont’d Broad Categories

Subject Areas

Community leadership and citizenship

● ● ● ●

Citizenship Distribution of House of Commons seats Elections Immigrants

Housing Corporation (CMHC) in general and for some specific industries and businesses. The Manitoba Bureau of Statistics also collects some business information about Winnipeg, but otherwise collaborate with Statistics Canada for most of their data. Since many departments within the City of Winnipeg, and almost all other agencies or institutions use fully or partly Statistics Canada data, scanning through Statistics Canada’s database should be the first step in acquiring data that can be used to assist in developing measures for QOL. It is also important to note that the City of Winnipeg does collect and utilize data on its own. Major data sources for the City of Winnipeg, aside from Statistics Canada include: Forestry Branch Database; Solid Waste Departments Database; Streets and Transportation Department’s Paver System that maintains information on quality of streets in Winnipeg; the Assessment Department’s Database; Water and Waste Department Water Quality Database; Winnipeg Police Services Crime Statistics Analysis Database. It was also observed that Statistics Canada does not always collect itself all the data that it maintains in its database. Other than the census-related data, most of its data are obtained from other government departments and some private institutions. For example, it collaborates with Health Canada, Agriculture Canada, Manitoba Environment, Winnipeg Police Services, just to name a few, in gathering data for its database. In spite of these other sources of data, Statistics Canada remains the primary data warehouse for data about Winnipeg. Other than the traditional major sources of statistical data such as public and governmental agencies/departments/institutions, the public and private sectors rely on the use of public opinion polls as another major source of data on a variety of issues. The success of this technique has produced a significant amount of data. However, sophisticated software may be required in handling the vast amount of information produced by polls. Some of the data are available in organized form, such as annual reports, articles, and other similar documents. Tables in these reports also provide additional data/information. For example, the Canada Year Book has a significant amount of data related to QOL issues. Other sources of information are local nonprofit groups. Several of these groups collect data, but their efforts have largely focused on local issues, such as specific sections of rivers or streams below the scale of the city as a whole. Their efforts also vary in focus, frequency, and level of scientific rigor.

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Time period of data/record. Most of the time series data assessed start from the 1960s, 1970s, and the 1980s. Some of the census data from Statistics Canada go back to the 18th century. However, most of the survey and public opinion poll data are for a specific period. For example, the Winnipeg Area Study (WAS) provided survey data covering the period 1981–1993. However, most of the issues that were surveyed differ or changed from year to year, and it may not be possible to determine any trend for most of the specific issues over the years. Our assessment also found that long-term monitoring was not considered a priority for most data collected. This is an important consideration with respect to measuring QOL, because time series data are required to determine historical trends and their changes. The lack of long-term data was most noticeable in regard to the natural environment. Finding data sets that go back further than 5 or 10 years is difficult, beyond that is almost impossible. Obviously, without monitoring that extends to these time periods, it will be difficult to detect anything but major changes to the environment. Some of the exceptions to this include water and air quality monitoring for a selected set of variables and monitoring sites. The stocks/flows of hazardous and solid waste streams is another area where much monitoring has occurred. Government departments, agencies, and crown corporations (e.g., Manitoba Hydro) that have been charged with the responsibility to manage these wastes have kept good records of how much waste they have received and what has happened to the waste. In addition, some localized monitoring has been performed by students and university researchers, government agencies and departments, and a few local nonprofit organizations. In a few cases data existed in more than one organization, but for different time periods and for different decision-making purposes. Integrating such data may be possible if they meet minimum criteria of compatibility. For example, census data and other survey data addressing the same issue may be combined and individually synthesized to provide new insights into historical trends. Yet it will be difficult to specify a time period for analyzing all QOL issues adequately. The lack of historical data in some cases is due to incomplete archives of the institutions responsible for the data collection. This is typical of some of the education-, police-, and highways/transportation-related data. Frequency. Most of the data assessed are collected on an annual basis except census data that are collected every 5 years. Some of the data that are collected on a daily, monthly, weekly, quarterly basis can be aggregated to produce an annual data set. For example, City of Winnipeg wastewater quality data and Dutch Elm disease data, although they are collected on a daily basis, could be aggregated to produce an annual data set. In such cases we can make measurements on an annual basis without difficulty. Data collection method. The collection method is important for knowing how well the data represents reality. With most of Statistics Canada and City of Winnipeg departmental data we were not able to determine the data collection method, since

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we scanned their database only for broad data categories and subcategories.1 However, for most of the other sources, we were able to determine their method of collection. For example, MPIC collects their data based on claims reported, and some of the environmental data based on various monitoring systems. Data storage format. Most databases are now stored in computer files to allow for direct input and data manipulation and are also available in hard copy. This in the long run will help facilitate easy analysis and interpretation of the data. For example, Manitoba Education and Training, MPIC, and the Social Planning Council of Winnipeg are setting up database of this kind. All the data from Statistics Canada are in both hard and soft copy,2 but some of the other sources have data only in hard copy. Some of the annual reports do have their data tables both on hard and soft copy, for example, the Canada Year Book. Most of these data are surveys conducted by private institutions and the news media in relation to the analysis and interpretation of a particular situation. The City of Winnipeg stores data in both electronic and hard copy; however, some data may exist only within various hard copy annual reports or reports provided by outside sources and may not be contained in any formal electronic database. Some government departments do not have their data in a user-friendly format, and this makes it difficult and time consuming to interpret and analyze their data. For example, understanding the air quality data from Manitoba Environment requires in-depth understanding of a coding system. Several government departments and institutions do not have any mechanism in place for storing their data and have no future plans for doing so. They continue to store their data on punched cards, magnetic tape/discs, microfilm, etc. When a study is over, the departments responsible for the data do not see the use in transferring/transforming the data to be easily accessible by modern computer technology. This makes it difficult to get access to these data, which could help with determining historical trends on some of the issues in measuring QOL. Some data files are very large and complex, and require familiarity with the program being used. For example, the WAS data is stored on the University of Manitoba Dafoe Library UNIX directory. In this case some knowledge of statistical software is required to manipulate the files. Without in-depth familiarity with this software and if only a few data sets are required, one would find it easier to work from a printed version. In at least one government department, staff changes combined with inadequate database documentation have limited the ability of staff to extract information from the database and reduced the usefulness of the collected information. Geographic coverage. About 90% of data from Statistics Canada are on national, provincial/territorial levels, and not broken down by individual communities. Most of the data from Statistics Canada that covered Winnipeg are census related. Although other sources do have data on Winnipeg, most of these are surveys for specific periods. Geographic coverage of data collected by city departments varied.

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The scale at which city departments collect data is currently not coordinated. Some data may be collected at the neighborhood level and others may not. Scale will also have influence on how the City of Winnipeg reports on QOL. Many important observations, trends, or issues may be lost by reporting on a citywide basis and may not be effective in illustrating subcity trends. At the same time, there may be instances where trends may not be suitable for reporting at a larger scale such as local water quality data. The use of Statistics Canada data about Winnipeg has been complicated by the fact that their interest is in Census Metropolitan Areas (CMA) and not in specific cities or communities. For example, since 1993, census division 11 is Winnipeg and Headingly combined, and not just Winnipeg. The only way to get around this problem is by subtracting the population of Headingly from Winnipeg and doing the other calculations accordingly. In cases where data is not available on a district basis census, the only other approach possible is to break down provincial scale and apply these to Winnipeg. Since these statistics represent provincial averages, the accuracy for Winnipeg varies with the data used, and making the adjustment may be difficult because of technical and resource constraints. Restrictions. Access to some databases other than Statistics Canada may be restricted.3 Also there are restrictions in acquiring data from the universities, since these are meant for students, staff, and faculty members only. In order to access the Data Library Services at the University of Manitoba, a University of Manitoba UNIX account is required. This makes it difficult for the public without any link to the university to access the database. Discussions with several institutions and agencies indicated a reluctance to provide information for political reasons. Cost. Most organizations do not collect and store their data because of cost,4 and they prefer Statistics Canada to do so. The main reason for this is that they do not have adequate funding for this purpose. Most of the data collected are paid for by private organizations and are either confidential or restrictions are placed on their release. There is a cost involved in acquiring data from Statistics Canada, unless the data is obtained from CANSIM through the universities. There may be costs involved in acquiring data from some of the other major sources as well, especially those in soft copy. The cost is usually dependent on the time spent in retrieving the data. Statistics Canada is collaborating with universities and other institutions to make its data more accessible and cheaper to the public and researchers through a program that they called “Data Liberation in Canada.” Discussion. The data availability assessment revealed that there is a significant amount of data collected and stored by the City of Winnipeg’s individual departments. This data as well as data from other sources can contribute to the development of a QOL report for the City of Winnipeg. Although the specific type and quality of data was not identified in detail, the assessment indicated that many departments collect, store, manipulate, and utilize data for management, decisionmaking, and service delivery activities. As a result many departments operate and

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maintain stand-alone databases and data management initiatives that are specific to their needs. The assessment also revealed that aside from departments developing and maintaining data collection activities, the City of Winnipeg also relies on many outside sources for meeting specific data needs, such as Statistics Canada, provincial organizations, and professional consulting firms. Linking different data sources and creating a database to archive all existing sources of QOL data will provide a new opportunity for systematic review of existing work from a historical perspective. A common challenge faced by experts involved in QOL or sustainable development measurement and reporting has been that time and resources rarely permit them to gather sufficient quantity and quality data to perform analysis. This was one of the major problems in the Manitoba State of the Environment Report 1997. The creation of a database or linking the sources of already collected data will help maximize the use of existing databases. In addition, almost all the organizations with which we had meetings were interested in the project, and would like a follow-up meeting or a copy of the final report of the project. Some wanted to know how our stakeholder group was selected and why they where not part of the stakeholders group (e.g., MPIC). Some showed an interest in being a part of the Technical Advisory Committee (TAC) if one is formed to help interpret and analyze their data (e.g., Manitoba Education and Training). The definition of geographic scale and time period for any particular issue or indicator should depend on the context and accessibility of data. It is important to be flexible so that issues will be analyzed based on availability or potential availability of data. Statistical interpolation can also be used to complement some of the data sets that lack historical data, provided we have adequate information to estimate values from the known ones in the same range. In the same way, extrapolation can also be used on some data sets that are not as recent or complete as expected. It is important to note that almost all of Statistics Canada data are time series data.

Data Management Issues Methodological issues. Data management is a generic problem that applies to all research and not just long-term monitoring. However, it is an especially serious problem when one is considering data sets that extend beyond a decade or more. Given the circumstances, forming a Data Management Task Group within the City of Winnipeg would represent major progress in improving current and long-term data collection and analysis on QOL and sustainable development. Following are some specific issues regarding methodology, including how organizations define and collect specific data. These issues will all have some degree of impact on the outcome of developing a QOL framework and respective indicators and measures. Definition and classification of data varied among the different organizations and institutions (for example, there is a difference between the definition of a passenger on an airline and one on a bus). It is likely that there will be problems in reconciling units between different aspects being measured. This may hinder the ability to perform comparative analyses.

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There are discrepancies in the methods used to collect similar types of data from different sources. For example, Statistics Canada gathers their automobile accident record data directly from the police. The police collect their data based on reported accidents that cause more than $1000 in damage or those that involve major bodily injury or death. However, similar data are collected by MPIC based on the number of reported claims. Therefore, the number of accidents recorded by MPIC is far greater than the number recorded by the police. If this kind of data is to be used, it is important to note both the source of the data and the method of data collection to avoid any ambiguities. In most cases, surveys are used by data collection agencies. In many cases the definition of issues being surveyed are not harmonized, and while the data collection process is still in progress, the issues tend to change. This makes it difficult to determine long-term trends. For example, the focus of some of the issues to be surveyed kept changing as the data collection effort progressed in the Probe Research Inc. and the WAS studies. Despite problems like this, most of the surveys can serve as a baseline for future comparison, especially the issues identified by stakeholders as important but which lack adequate data. Many institutions collect the same data for different objectives. For example, accident records from MPIC are mainly used for price setting to determine which types of cars are accident-prone and their impact on insurance rates. The same type of data from the Winnipeg Police Service, or Statistics Canada as a secondary source, can be used to determine the number of accidents occurring in a particular month or city. These two different sources of data can be used for comparative analysis. This type of comparison may help identify some biases in the data collection and interpretation. Legislative changes are another source of difficulty. This is most noticeable in regards to licenses where regulations and requirements change periodically creating the need to convert data collected before and after any changes. Another area where this problem occurred was in regards to provincial protected lands, since government definitions and classification systems have been changed more than once. This has led to a difficult problem in the interpretation of any long-term assessment of protected land. It was also observed in the data availability exercise that data often existed in an uncollated form. This requires searching through files manually and the creation of a periodic summary. This is a problem when one attempts to find out the number of applicants for some licenses. In addition, at least one government department has a database that was maintained over the years by a former employee. They have continued to add information to this database on a regular basis but the correct procedures to do the detailed queries required to fully access the information left with the employee. This points to the need to institutionalize data collection as a distinct responsibility. Institutional and organizational issues. The assessment revealed that it is not clear to which degree City of Winnipeg departments currently interact with each other regarding information and data requirements, data communications and reporting, and planning and data management activities. In fact, such activities

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are largely independent and ad hoc at the present time with no overall corporate direction or corporate procedures evident. This is not to say that information does not get used for corporate reporting but that at present there are gaps in the utilization of data at the corporate level. Benefits of addressing corporate coordination of data management and reporting for the City of Winnipeg include: accessibility and awareness, reduction in data overlap, compatibility of data and databases, the fostering of decision-making, and more efficient reporting and decision-making mechanisms. Although it often makes sense for City of Winnipeg departments to collect and maintain independent databases, it is equally important that such data be available at a corporate level for many reasons. Possibilities for the integration of databases throughout city departments should be investigated as part of establishing proper data management and reporting mechanisms for a QOL initiative. Perhaps the most obvious administrative problem occurs in relation to the creation of new databases by the different organizations/departments/institutions. Who is to provide the impetus for the creation of a new database? Even where a well-developed substantive need already exists, there are still problems in establishing new data archives in a way that will provide complete geographical coverage when combined with other existing databases. Criteria for establishing databases must clearly extend far beyond simple political boundaries. For example, a local watershed is a useful boundary for describing water quality and pressures that influence it. Recent reorganization activities within the City of Winnipeg present an excellent opportunity to investigate corporate data management and communications structure. In addition, projects such as the Intranet project currently being developed can contribute to potential products for such a structure. The Information Technology Services Division of the Corporate Services Department would also be a necessary leader of any such project. Related data collection and management activities/initiatives. In the City of Winnipeg, a mechanism existed whereby departments reported on annual accomplishments. Such a system presented opportunities with respect to data management and reporting for QOL. Departments could be required to report on agreed upon trends in addition to their annual accomplishments. Such information could then be utilized to produce a QOL report. A number of other related data collection and management activities and initiatives were identified. ●

City of Winnipeg restructuring activities. Driven by the need to reduce fiscal constraints and improve efficiency of services, restructuring is the time for seeking opportunities, innovation, and alignment. From this perspective, it will be important to review and possibly redefine relationships among and between units within the City of Winnipeg and reassign missions, roles, and tasks. The key aspect for the city will be to increase its responsiveness to changing demands for services in the community that contribute to continued sustainable development and high QOL. As such, it is important that the community’s

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expression of QOL be understood, and that efforts be explored to define relationships that contribute to integrating sustainable development principles into the new organizational structure. Management reference model. In November 1997, the City of Winnipeg initiated a project to develop a business model for the entire City of Winnipeg using a framework called the Management Reference Model for Government Services (MRM/GS). This initiative will provide a framework for defining business functions of the City of Winnipeg in terms of services provided to the public. It also includes software that allows for the storage and analysis of such information. The information gathered from the project will support many of the city’s business objectives, including business planning, organizational restructuring, performance measurement, information technology planning, program-based budgeting, and activity-based costing. There are numerous possibilities to link the information obtained through MRM/GS to information required for a QOL reporting framework. The input and output measures included in the MRM/GS apply to the City of Winnipeg as an organizational entity. On the other hand, performance indicators in the QOL framework measure overall outcomes for the community of Winnipeg as a whole, not only for local government itself. Potential opportunities should be explored fully with respect to making the structure and function of the MRM/GS compatible with QOL indicators and measures. Corporate planning framework. Activities such as the MRM/GS and QOL reporting also lend themselves well to ongoing activities to realign the current corporate planning framework. This framework describes processes that are currently used to identify priorities, set budgets, and establish long-term planning goals. It is unclear at this point of time how such a framework will evolve as a result of current reorganization activities. Nevertheless, any future linkages and potential compatible activities should be identified and explored in relation to a QOL reporting framework. This is especially true with respect to what such a framework will require for data and information reporting. Data management systems. There are currently several data management systems operating or available within the City of Winnipeg and its community partners. Some of the more interesting systems that currently exist within the City of Winnipeg that have significant potential with respect to not only a QOL reporting program but also many other initiatives such as MRM/GS are the land-based information system and the Map Info software team. These systems currently provide input, storage, and manipulation of data at a geographic level over time and allow for queries to be made on a wide array of data that traditionally would not have been addressed in concert with other information. Map Info can take data from the Language-Based Intelligent Systems (LBIS) and display data graphically. Such a tool has a great deal of potential with respect to performance measurement activities including QOL reporting. As such these systems should be investigated thoroughly as major data management components of any QOL reporting program. City of Winnipeg corporate Intranet initiative. As discussed, many departments currently operate databases that store information specific to their requirements. These databases presently are not easily accessible to other departments

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or individuals that may need information contained in the database. The city has recognized the potential constraints that such a structure can produce and has initiated the development of a common and easily accessible Intranet server to provide access to departments for information files and databases. The objective is to produce a forum whereby a coordinated corporate effort can be arranged around information and data. Departments would be able to contribute both data and information to the server and allow for obvious connections to be made. QOL framework could benefit from this project since coordinated access would be provided to data from many sources. Any future development of the intra-net should consider its linkages to the QOL measurement system. A number of organizations besides the City of Winnipeg are also involved in data management initiatives. ●

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Census data consortium. Due to a lack of available census data at the neighborhood level, several partners, headed by the Social Planning Council formed a consortium to purchase special tabulations of census data from Statistics Canada. The consortium project led to the creation of a comprehensive demographic and socioeconomic database for Winnipeg and its vicinity. Data Library Services at the University of Manitoba. This service was established in 1995 with support from the Academic Computing Department at the University of Manitoba. Its mission is to assist students, staff, and faculty at the University of Manitoba in identifying, acquiring, and manipulating data. These data are for noncommercial purposes only. It is expected that nonprofit organizations and institutions will be allowed to participate in the future. The Data Liberation Initiative, which began in 1996, provides Statistics Canada data to subscribing institutions, and the Inter-University Consortium for Political and Social Research (ICPSR) provides access to thousands of data files, emanating from countries around the world.

Recommendations The following recommendations address the current difficulties encountered in finding or accessing appropriate data for measuring QOL in Winnipeg. ●

The City of Winnipeg should form a Data Management Task Group. This working group should itemize and describe core data sets, to enhance harmonization for use in this project and other related projects and to find ways to improve data availability for the specific issues identified for measuring QOL for the City of Winnipeg. Such a group would also enable the City of Winnipeg to address many of the issues identified above regarding related data collection and management activities and initiatives in a coordinated corporate-wide fashion. Also this group should identify the departments that may be collecting data within the City of Winnipeg.

The task force will encourage Statistics Canada and other governmental agencies to include key QOL issues/questions on future censuses, and other surveys related to QOL and sustainable development.

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We recommend that the representatives of the City of Winnipeg meet with their counterparts on the provincial level to discuss the potential for establishing joint surveys on specific QOL and sustainable development issues. If feasible, it will be important to link the City of Winnipeg data sources to those of the Province of Manitoba. This will help determine the type of data available within the city and on the provincial level. In circumstances where City of Winnipeg data is not available for a particular issue, then province-wide data could be used. This database can also be used for comparative analysis purposes. There is a need for local, provincial, and national level government to become financially involved in the support of data collection agencies and groups. Acquiring data in Canada generally is very expensive and time consuming. This is unlike the situation in the United States where accessing data can be both easy to obtain and inexpensive, since much of it is sponsored directly by the federal government. The City of Winnipeg and the Province of Manitoba should assess their current data collection efforts for the elimination of duplications and deficiencies. The proposed data management task group could undertake this effort. The task group should organize public opinion surveys to collect data in areas where it is not available. Also survey and public opinion poll procedures should be conducted in areas where province-wide data is used for city data to verify the result of the data analysis and help explain any discrepancies. The City of Winnipeg should form a TAC to give comprehensive advice to the Data Management Task Group. Because of the complex aspects of measuring some QOL issues, there is a need to seek advice regarding the acquisition of data and to establish the reliability of what can be measured and aggregated. This will provide credibility to the process. Some of the members of this group should be experts in the departments from which we are gathering data, since they may give input as to how to interpret and analyze their data. If there is more than one data source available with the same type of information for the indicator, one should make use of at least two or more of these sources. In that case one can check for discrepancies and also compare them. Those responsible for data storage should use the most readable format available. The Data Management Task Group should prepare recommendations for the city to update out-of-date storage systems. More than one copy of data should be kept. To sum up, the data assessment initiative has revealed some difficulties and challenges facing the current data collection and management practices and in acquiring adequate data for measuring the QOL in Winnipeg. It identified some of the major areas for which data are currently needed and in some cases the general approaches by which data can be obtained. There is a need for more work in terms of both the collection and the management of data. This will invariably improve the measurement process. We cannot predict the future without appropriate and adequate data to measure the present situation. Addressing the recommendations related to data availability will alleviate many of the difficulties that have been discussed. The implementation plan provides guidance for the next stage in moving toward QOL reporting. ●

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Implementation Plan The implementation plan is a series of activities intended to create a QOL indicators measurement and reporting system in the City of Winnipeg. It builds on earlier stages of the Plan Winnipeg Review process and integrates the tasks completed in the framework of the current agreement between IISD and the City of Winnipeg. In order to guarantee the success of QOL reporting in the long term, necessary institutional capacities and responsibilities need to be identified. Core responsibilities rest with City of Winnipeg offices and officials, but there are specific roles for other levels of government, NGOs, residential groups, and the private sector. Public participation and adequate communication of results to the public is very important to ensure the transparency and openness of the process. The implementation plan also takes into consideration the collaboration between the city administration and the provincial government. Given that not only the socioeconomic and ecological foundations for QOL but also the needs and priorities of Winnipeggers change over time, reporting on QOL is an ongoing, cyclical process. Figure 5 provides an example of a general community indicator process based on the approach of Sustainable Seattle in the United States. The basic purpose of this cycle is to ensure policymakers as well as citizens receive adequate feedback to evaluate and, as necessary, adjust their decisions related to QOL issues. Identifying issues, creating and monitoring indicators, and developing institutional responses are essential components of this cycle. Visualizing it as one cycle is useful, but it must be recognized that several subcycles underpin an effective measurement and reporting system. For example, preliminary indicator sets may need to be revisited as new data becomes available or new issues become important to the public or policymakers. The objectives and periods of each cycle depend on a number of factors, such as the frequency of data collection, the availability of funding, the community’s need to measure changes in QOL, and the information needs of decision-makers. Institutional and political support for achieving these objectives is essential. The lessons drawn from our own experiences with measurement projects on the local level and from the sustainable development planning process of many local governments, summarized in the Local Agenda 21 Planning Guide of the International Council for Local Environmental Initiatives, support our emphasis on two primary activities that are critical factors for success: ●

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There is a need to dedicate resources for an organization to steward the implementation of the QOL measurement and reporting process. The current organizational structures used for the planning process within the City of Winnipeg were created to respond to a different task. An organizational structure that directly reflects the tasks that are required to successfully implement the plans, with well-defined responsibilities, authorities, capabilities, and resources (both human and financial) should be put in place. The city government must integrate public input and stakeholder responses into the implementation plan and should keep communication open throughout implementation.

THE COMMUNITY INDICATORS PROCESS Identify your community’s shared values and visions Consider how your project links to other local efforts

STEP 3

STEP 4 STEP 2

Clarify your purpose

Review existing models, indicators, and data Tailor your project to local needs

Build crosssectoral and personal relationships

Draft a set of proposed indicators

STEP 5 STEP 1

Draw on local experts Begin with an

Inspiration

Convene a participatory selection process

STEP 6

to create an indicator project

Narrow the list to a manageble number Update the report regularly

STEP 10 STEP 7

Mobilize community action Publish and promote the report

STEP 9

Perform a technical review

Retain indicators that were popular with the selection panel if possible

STEP 8

Research the data

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Develop a strategy for broad-based community involvement

Make additional adjustments to indicator list as needed

THE PROCESS IS AS IMPORTANT AS THE PRODUCT

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Source: Redefining progress, The Community Indicators Handbook, 1997. Fig. 5. Indicator reporting process.

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In the data availability report we emphasized the technical and professional needs to make the QOL reports comprehensive, compatible with stakeholders’ needs, scientifically sound, statistically reliable, and easily communicable. A review of accessible databases, information resources, and analytical capabilities is useful to understand current limitations and potential investment requirements. As the detailed recommendations have been described in the section “Data Availability Assessment Report,” here we simply summarize the necessary steps to put those recommendations into practice. The implementation plan identifies three major stages of the reporting process. Keeping in mind that the first stage of the implementation plan need not be repeated in full every time a QOL indicator set and indicator report is compiled, the production of a QOL indicators report should be repeated every 2–4 years. There is a need to revisit the framework and vision on a longer term periodic basis. 1. The first stage focuses on the data collection and processing tasks, including the necessary institutional arrangements, feedback loops to high level decisionmakers, the creation of a database, as well as adequate data management, statistical and econometric analytical apparatus. This stage includes an iterative process for developing the QOL indicator set, leading to the compilation of an indicator report. 2. The second stage consists of the writing of the full QOL report that is based on the indicator report as its core, but complements it with an analysis of crosscutting issues and trends. QOL report includes case studies to illustrate the major trends identified and aggregate indexes as appropriate. 3. The third stage focuses on the production, dissemination, and use of the QOL report. This stage includes a technical review, graphic design, and final editing. Details of the report release, dissemination, and promotion are worked out in a marketing plan, including planning to ensure that the report reaches key policymakers. The detailed implementation plan is as follows (Figure 6): Work plan Stage 1 Preliminaries Planning and preparations ● ●

Consultation process Framework selection

Develop indicator set ● ● ● ●

Analyze results of consultations Conduct data availability study Clarify methodology Draft first indicator set

Produce IISD’s report and implementation plan Identify institutional responsibilities

Task

Stage 3

Stage 1 Preliminaries Planning and preparations Develop indicator set, produce report Make institutional arrangements Finalize plans Collect and process data Produce first draft Discuss report Produce second draft Stage 2 Develop quality-of-life report Write and edit final draft Final report Stage 3 Publish Disseminate Feedback

Source: Approximately 29 months is needed, out of which 10 months work is already accomplished (from June 1997 to March 1998). The remaining task is doable in a little bit more than a year and a half after start with institutional arrangements. *A cell represents 4 weeks.

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Time* cumulation by stage Stage 1 Stage 2

Fig. 6. Work plan.

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Approve institutional host of the project; define responsibilities Confirm TAC; clarify its role; select members; nominate contact persons for each participating department and agency Select editorial board and define terms of reference Establish Data Management Task Group; define its role; and set conditions for institutional memory Define report structure and table of contents Present work plan with time line and budget to Executive Policy Committee, to relevant subcommittee of the Provincial RT; get approval

Finalize plans ● ● ●

TAC review of IISD’s data report and implementation plan Finalize data collection and indicator plan; assign responsibilities Harmonize with Sustainable Development Coordination Unit (SDCU) of Province

Collect and process data ● ● ● ●

Assemble data Evaluate data assembled; establish need for further data Econometric analysis of data TAC discussion of the results of data processing

Produce first draft of indicator report ● ● ●

Compile indicator set Analyze trends Preparation for public discussions

Discuss draft report with focus groups ● ● ●

Hold focus group meetings Use other channels for public input Present findings to RT

Produce second draft of indicator report ● ● ● ●

Rewrite first draft TAC discussion Identify topics for illustrative case studies (Box stories) Contact groups/organizations to provide facts for case studies

Stage 2 Develop QOL report ● ● ● ●

Apply Bellagio principles to evaluate results of indicator report Analyze linkages and apply aggregation methods Prepare Box stories for illustration Final methodology test

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Write and edit the draft report ● ● ● ● ●

First edit TAC review and second edit Selection of illustrations, graphical and photo materials Preliminary graphic design and cover Present results at RT and Executive Policy Committee meetings

Write and edit final report ● ●

External reviews and public input Final edit and design changes

Stage 3 Publish report ● ● ●

Preparation for release report Media campaign Print and release report, both in soft and hard copy

Disseminate report ● ●

Reach all relevant target audiences Set up interactive Internet site for better communication

Feedback process ● ● ● ●

Analyze feedback Channel feedback to relevant decision-making bodies Make suggestions for changes in future reports Make suggestions for necessary organizational changes

Notes 1. Information collected in relation to this field was not included in the data availability report (Appendix D) due to the limited amount of information available for some variables and limitations of space. 2. Hard copy refers to data found in a document or report that is available on paper. Soft copy refers to data stored in some form of computer database system or format. 3. Information collected in relation to this field was not included in the data availability report (Appendix D) due to the limited amount of information available for some variables and limitations of space. 4. ibid.

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Appendix A: Minutes with general questions and answers—First Focus Group Meeting at IISD (November 6, 1997) PLAN WINNIPEG REVIEW 1997/1998 MEASURING PROGRESS TOWARD THE VISION First Focus Group Meeting

Minutes November 6, 1997 International Institute for Sustainable Development (IISD) Canada Board Room 7th Floor, 161 Portage Avenue East Winnipeg, Manitoba Tel: 958-7700 Participants. There were a total of 29 attendees including IISD and the City of Winnipeg staff. Twenty participants represented different communities and interests of the city. Appendix A is the listing of the focus group participants. Introduction. Peter Hardi (IISD) outlined the day’s agenda and the objectives of the meeting. A brief overview of IISD and the Measurement and Indicators Program was given, and a short review of the Manitoba State of Environment Report was outlined. Vision for the City of Winnipeg’s future. Gerry Couture briefly outlined the vision of the city, what they expect from this project, and the possible transition to Sustainable Development Reporting. He also talked briefly on Plan Winnipeg and its importance in building a better city for its residents by measuring progress toward the vision. Objectives and mechanics of the process. Peter Hardi used a flow chart (see Appendix B) to describe the process to be adopted at the meeting, explaining each stage of the flowchart as it relates to the project. He also introduced the conceptual framework adopted in the Manitoba State of Environment Report to explain and describe the framework of QOL for the City of Winnipeg. The categories were: urban environment, human-made capital, community assets, and human well-being. László Pintér briefly outlined the mechanics of the process (individual brainstorming, joint discussion, and scoring) to be used during the meeting. General questions/answers. There was an open discussion, mainly questions from the stakeholders. The following are some of the several questions from the stakeholders. Peter Hardi and Gerry Couture responded to the questions. ●

Has any city in Canada done this type of work? Answer: No city or province in Canada has undertaken any measurement initiative of this kind. There was a brief discussion about Sustainable Seattle as one of the first cities to start something like this although not the same, but still they have not aggregated their indicators. (Peter Hardi)

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Are there any mechanism in place to link the cities and countries that have started these initiatives? Answer: Yes, but not really on sustainable development rather on Agenda 21.

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Is the stakeholder group at this meeting a good representation of Winnipeg? What criteria were adopted in selecting the stakeholders? Answer: No, since we cannot accommodate everybody; however, we tried to invite about 40 people. Some of them could not make it because of time limitation on most part. Also we will put the findings and result on the website for public input. (Peter Hardi)

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Does the 300 indicators in Plan Winnipeg describe the vision of the City of Winnipeg? Answer: These are the issues of importance to the communities in Winnipeg, and we may need to measure them some time to determine their direction if data are available. (Gerry Couture)

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What boundaries is the vision based on? Answer: The city government specified the boundaries as those of the City of Winnipeg proper. IISD has no say in this; much depends on what has been defined by the city to measure. (Gerry Couture, Peter Hardi)

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Has any measurement been done on the 300 indicators identified in Plan Winnipeg? Answers: No, these are not really indicators, just statement of important issues that we have to consider when making decision. (Gerry Couture)

After the general question and answer session, the plenary group was broken up into two smaller groups of ten participants each. Generation and listing of first set of issues, clarification of the suggestions, as well as the individual ranking of issues was done by each of these groups. László Pintér and Peter Hardi facilitated the small group meetings; Juanita Huteley and Chuck Mrena were the rapporteurs. After lunch the results of the brainstorming sessions were presented, first by László Pintér and then by Peter Hardi. However, before reranking of the issues by the plenary a major discussion evolved. Many participants felt that there was no sufficient time left for regrouping the issues, eliminating overlaps, and providing justification for selection. At this point several of the participants suggested that the session should be adjourned until the two lists were combined and the next step in the process is identified. The group as a whole agreed to this suggestion and the session was ended. Peter stated that the combined list with proposed subcategories for clearer view of the issues would be sent to the participants for review. To aid the process, the City of Winnipeg’s “Plan Winnipeg” document was made available to participants. Representatives of the city accepted a suggestion to review all recommendations of previous community involvement in the Plan Winnipeg process. IISD will compare those issues with the present selection and present to the participants.

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The participants were requested to provide feedback after they got the documents from IISD. It was agreed that the next meeting would take place in the new year.

Appendix C: Participant Comments and Suggestions/Additional Issues for the Survey Participant survey #1 1. Add another issue to land use management regarding statutory provision for citizen input into land use planning. 2. Add another issue to infrastructure and services regarding maintenance and renewal of infrastructure and services. 3. All of issues under employment were indicated as important.

Participant survey #2 1. Social services, which are neither government nor do they fall in categories of recreation (e.g., youth drop in programs, seniors services, all types of social services provided by nonprofits, voluntary organizations, which include a staff and volunteer delivery model). 2. Add another issue to municipal finances regarding financial management with a focus on spending. 3. Under community assets, comments regarding community-based social services should be subcategory of recreation; culture, education, etc. are being used. Winnipeg has a significant and very critical system of resources provided by this sector and exclusion, while inclusion of other sectors would be viewed as a statement of lack of importance. 4. Add another issue to wealth subcategory regarding the ability to purchase basic needs through employment, e.g., percentage of income for basic needs.

Participant survey #3 1. Add another issue under government services regarding responsive and effective political leadership.

Participant survey #4 1. Add another issue under land use management regarding building on neighborhood uniqueness and strength. 2. Add another issue under municipal finances regarding spending on arts groups vs. social spending. 3. Add another issue under culture, arts, and entertainment regarding affordability of events. 4. Add another issue under education for community assets regarding special education needs—integration, student support. 5. Add another issue under education for individual well-being regarding opportunities for ongoing education.

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Participant survey #5 1. Add another issue under municipal finances regarding spending priorities.

Participant survey #6 1. In general, notes that the problem which affected the workshop has not been cured—too many issues are subsets of one central issue, but carry same weight. If this problem is not resolved, it will be difficult to get a meaningful result. 2. In the urban environment category, drinking water will become a future issue. 3. In the urban economy category—too many issues are only slight variations of the same major issue. 4. In the community assets category add zoning. Many issues listed are almost identical to many issues; some are covered elsewhere. Integration of city and provincial government programs and vision needed. 5. In the individual well-being category issues listed are duplicates, issue #5 does not belong. 6. Add zoning to community assets under the housing subcategory as an issue. 7. Add another issue under recreation and leisure, issue #5 from land use management. 8. Add another issue under education in the community assets category regarding primary/secondary education quality. 9. Add another issue under neighborhoods regarding community clubs.

Participant survey #7 1. Add another issue under community assets, education regarding the efficiency and accountability of the system. 2. Add another issue under individual well being, health regarding efficiency of health care delivery.

Participant survey #8 1. As we move forward into the future, I believe that our success as a city is dependent upon our ability to tap into global economics. In order to accomplish this, we require ● ●

Strong focused leadership. A big picture framework for our city that all future decisions are made against.

2. I believe that if we as a collective community cannot think big and opt instead for maintenance of the status quo, we will continue to deteriorate as a city. 3. Add another issue under urban economy, municipal finances regarding the over reliance of revenue generation by the public vs. private.

Participant survey #9 1. Add and responsibilities to the definition on citizenship under the community pride and leadership category. 2. Stop urban sprawl. 3. Under consumption and conservation issue # 7 encompasses #s 1,2,3,5, and 6.

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Participant survey #10 1. Add another issue to land use management under urban environment category regarding the regulation of building height to ensure access to sunlight. 2. Under government services issue # 18 universal access includes to all citizenry, young, old, or ethnic, etc. 3. Under people in the community assets subcategory comment that ideally it would be possible to live rurally and possible to live in city depending on choice. 4. Add another issue under safety, individual well-being regarding children protected from emotional, physical traumas of hunger, cold, violence, parental preoccupation with survival. 5. Add another issue to education under individual well-being regarding lifelong learning. 6. Add another issue to citizenship under community leadership and pride regarding trust in positive outcomes.

Participant survey #11 1. Under individual well-being the term wealth should not be used, we must find another term to describe this issue. 2. Under government services in the community assets category all issues are critically important and very difficult to rank.

Participant survey #12 1. Add another issue under land use management regarding equitable system of taxes/user fees (i.e., for more effective management of sprawl/accessibility). 2. Add another issue under infrastructure and services regarding green space/ quality of urban landscape. 3. Add another issue under vitality regarding investment, local. 4. Under people migration requires more people in less people out. 5. Add another issue to wealth regarding discretionary income (personal disposable income).

Participant survey #13 1. 2. 3. 4. 5.

Ecological footprint contains many of the categories listed. Under housing add the issue of safety. Under recreation and leisure add the issue of open spaces. Under wealth add the issue getting by. After reading the survey there is room to boil down the framework a bit by focusing on the language used to establish a sound framework that can then go out to more groups and be added. There is considerable overlap.

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Appendix D: City of Winnipeg Project: Data Availability Assessment Work Plan Objectives/Goals: The objective is to assess data availability based on the “Indicator Framework Survey,” and to produce a final report regarding findings, problems, and difficulties. The mandate is to develop appropriate indicators based on the availability of data; this will help resolve some of the major data problems experienced in sustainable development research project. We are also interested in knowing the type and format of data available, and whenever applicable we may collect and store the data for future reference.

Project Scope Tools/activities: ●

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Create a folder under the shared drive mainly for the data availability assessment report (this will be available only for IISD staff) If feasible, create a database to store available data sets A table/database with all the necessary information about each data set Any data retrieved should be stored both in hard and soft copy Document all problems and difficulties in obtaining the necessary data

Focus of data assessment ●

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Category/subcategory (relevance of database on the “Indicator Framework Survey”) Data source Summary description of data Name/phone of department or contact person Time period of data/record Unit of measurement Frequency(e.g., monthly, quarterly, annually) Data collection method Data storage format (e.g., hard copy, soft copy—tape, floppy disk, IBM format, Mac format, Mainframe, spreadsheet, Database, text, etc.) Geographic coverage Restrictions/conditions Cost/price of information

Key data sources ● ●

Major government statistical departments and agencies Publications (e.g., State of Environment Report, Statistical Record of the Environment, Economic and Social Journals, Annual Reports, Year Books, etc.)

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Other private and public organizations and institutions (e.g., NGOs, Social Planning Council of Winnipeg, Urban Studies Institute, Prairie Research Associates, Research Institutions, surveys, etc.) News Media (e.g., Free Press) Libraries (e.g., Dafoe—periodicals section) Business (financial institutions, insurance companies, real Estates agencies Individuals (e.g., professors, graduate students, etc.)

PETER HARDI, Senior Fellow, International Institute for Sustainable Development (IISD), Canada [email protected]

LÁSZLÓ PINTÉR, Director, Measurement and Assessment Program, International [email protected]

Sustainable Seattle: The Case of the Prototype Sustainability Indicators Project MEG HOLDEN Assistant Professor, Simon Fraser University

Introduction to Sustainable Seattle As an organization, Sustainable Seattle (S2) can be considered to have gone through seven main phases to date (see Table 1). The organization’s inception occurred with a forum organized in late 1990 by a nongovernmental organization visiting Seattle from Washington, DC.1 The keenest participants in that forum continued to meet and, in an early phase of meetings and slow agenda-setting, devised a plan for assembling a civic panel that would set measurable indicators of sustainable community over the course of a 6-month process. This process led to the heyday of the organization, which involved the production of three successive sustainability indicator reports in 1993, 1995, and 1998 by volunteers and disseminating around the world both the reports and the processes underlying it. Following this was a spin-off phase in which the organization advanced about a dozen new initiatives and adopted a new role as a “center for applied sustainability” or umbrella for sustainabilityrelated initiatives regionally. Organizational changeover followed, on three fronts: leadership, volunteer base and interest, and organizational structure. This led to a downturn in activity and energy. Despite attempts to rebuild this energy through new structures and completing a series of paid contracts, the organization next went through a near-death phase in which the director departed and the board of directors considered folding the organization on several occasions. Torch holders remained, however, keeping the organization alive through its latest reorganization in which a new office, new director, mostly new board, and new slate of activities have been established. Once again in 2006, an update of the prototype sustainability indicator project is on the agenda. This very brief chronological description of S2 suggests a contested history that is painfully familiar to many civic organizations. Following an energetic beginning, sparked by trends and personalities outside the region, S2 first garnered a great deal of volunteer support and produced a remarkable and innovative product, earning recognition and critical acclaim. This initial energy and success led to an awkward transition and difficulty in finding and securing a unique role for the organization in the local social and political culture that could be maintained over the long term. This awkward transition has been the demise of many worthy nongovernment efforts, and for several years in the late 1990s and early 2000s seemed likely to be the demise of S2 as well. The fact that S2 has managed nonetheless to reconstitute, reorganize, reorient, relocate, and “refund” itself speaks to the organization’s enduring resonance and resilience. This continued relevance is tied as

177 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 177–202. © 2006 Springer. Printed in The Netherlands.

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Table 1. Sustainable Seattle’s organizational life cycle. Date

Phase

1990–1991 Inception

Key Characteristics ●

●

1991–1992 Early phase

● ●

1993–1997 Heyday

●

●

1994–1998 Spin-off phase

●

●

1996–1999 Changeover and downturn

●

●

●

1998–2001 Near-death phase

●

● ● ●

2001–2004 Torch holders and reorganization

●

●

●

“Sustainable Seattle Forum” organized by Global Tomorrow Coalition Organization forms through follow-up meetings: “A Volunteer Network and Civic Forum” Civic panel process The radical new idea of sustainability indicators developed From public input to publication: “Indicators of Sustainable Community” reports released in 1993, 1995, and 1998 Getting the word out globally: S2 representatives attend dozens of conferences, receive awards, host meetings, and run workshops About a dozen new initiatives begin (most of which flounder) S2 adopts new slogan: “Center for Applied Sustainability” Changes in leadership: original three leaders leave leadership function; new director position is adapted into a contractor position Changes in volunteer base and interest: difficulty following the act of the indicators Organizational changes: S2 moves from the YMCA to an independent office and acquires 501(c)3 status Attempts to reinvent, containerize, and institutionalize the organization Various contracts are pursued for revenue Executive Director leaves the organization Board considers folding S2 forms alliance with Cascadia Consulting and assembles new board New initiatives in sustainability education, civic awards, and neighborhood indicators launched with major grant financing S2 relocates to independent office and launches original indicator report update

tightly to the process by which S2 pursued its flagship indicator project as to the indicator project itself. One of the benefits of examining the history and ethnography of S2 in this way is to better grasp the organization’s operational and process-oriented understanding of “sustainability” and “sustainable development.” The organization’s history proves that although S2 chose to pursue its goal of advancing sustainable development through selecting and measuring a set of numeric indicators, the organization’s intention was not so narrow. The intent of founding S2 members was to initiate and contribute to a citywide conversation about sustainable development that in time would lead to a new system of urban policy and practice. In a 1996 article in the Seattle Weekly, an S2 member defined sustainability like this:

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Sustainability refers to something specific and critically important, albeit complex: our long-term cultural, economic, and environmental health and vitality. It links these issues together rather than thinking of them as separate. It is often defined as “meeting the needs of the present without compromising the ability of future generations to meet their own needs.” A society that is sustainable will endure for generations and improve over time; one that is not will experience a decline in quality, equity, and prosperity. (True, 1996)

To S2, sustainability has been put into practice as a multifaceted idea. First, it is concerned with linkages among social, cultural, economic, and environmental issues, in that “decisions, actions, behaviors, and designs that cover the full range of consequences will most likely lead to more sustainable outcomes than those that only look at one dimension of concern.” Second, S2 took a diversity-based, collaborative, and inclusive approach to sustainability, arguing that “diversity in both ecology and culture promotes long-term stability by providing flexibility,” and that “sustainability calls for the elimination of poverty.” Third, some need for devolution of power in order to move toward sustainability is called for: “issues of equity (social, economic, environmental) cannot be resolved without fully inclusive and broad participation of an informed public, considering both today’s needs and the needs of future generations” (Sustainable Seattle, 1993a). For those involved with the organization, some of the main benefits have had less to do with indicators and more to do with raised awareness of the utility of a collaborative process, an enhanced ability to think holistically according to a sustainability framework, and an understanding of the value and importance of sharing decision-making powers both inside the organization and throughout the official and unofficial local governance channels. The S2 process model for initiating evolution toward sustainable development will be further explored through looking at the organization’s life stages in turn.

Inception: Origins of S2 as a Volunteer Network and Civic Forum (1990–1991) In Seattle at the dawn of the 1990s, the notion of sustainable development resonated with many active citizens and local leaders as an “exercise in thinking global”2 about environmental issues and their implications, highlighted by the World Commission on Environment and Development (1987). Sustainable development also provided interested Seattleites with a useful framework for combining environmental, economic, and social concerns locally. Several S2 founders remembered their immediate interest in the notion of sustainable development: I’ve been thinking about sustainability for years, and now it has a name, and it’s right along my ethos, my passion!3 The concept, even its early fuzzy non-form, resonated with something deep inside.4

On November 27, 1990, the Global Tomorrow Coalition convened a daylong symposium on the idea of sustainable development indicators at the University of

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Washington. This forum was designed with national and international consultation that brought into focus “a need both to develop concrete measures of progress toward sustainability and to expand the national dialogue on the application of these indicators.”5 The forum engaged a cross section of local citizens in envisioning a sustainable future for Seattle’s region, including the development of “practical indicators of sustainability for Greater Seattle,”4 incorporating the foremost concerns in people’s minds, and a public–private partnership action strategy. The Global Tomorrow Coalition presented participants with a challenge: to create a new vision of a sustainable future based on new indicators to measure progress toward that vision. The offer was to “share in an unusual opportunity to break new ground in order to build more effective structures and institutions that will govern the lives of coming generations in their city, state, and nation in keeping with the values of sustainability.”6 One participant described the feeling in the room at the end of the daylong meeting: At the end of it, you could just feel in the room, there was excitement about the topic . . . . And so a number of us, at the same time, raised our hands . . . saying, we can’t stop here. It was a sudden infatuation with a real issue, the skills we had, the kind of feeling or sense of power to make change. So we all said, well, okay, let’s have a follow-up meeting and talk about this.3

A prominent Seattle philanthropist in attendance, Kay Bullitt, offered to sponsor the follow-up meeting. Belinda Berg from the Global Tomorrow Coalition, and Nea Carrolla locally based professional facilitator, were the two participants to plan and facilitate the event. Carroll, a locally based group of about 30 arrived at the top of Seattle’s historic Smith Tower on February 21, 1991, to sit in a circle and determine what to do next. This turned into a series of meetings through a process that one of the attendees called “magic”: . . . the magic was it was a group of people who all . . . wanted to do something with each other—oh, he’s here and she’s here and yeah I’d love to do something with them—and this topic was perfect for all of us . . . . Sustainability. Sustainability and the indicators. The indicators were one way to approach doing something about this amorphous thing called sustainable development.3

Early Phase: The Leaders begin Meeting (1991) A volunteer planning team of six met almost weekly through the spring of 1991. Participants began to shake themselves out into various roles, and more interested people joined in. The early group included Richard Conlin and Jan Drago, two future members of City Council; Steve Nicholas, a Seattle City planner; Susan Hall and Nea Carroll, prominent mediators and facilitators; Karla Berkedall, a popular minister; Vicki Robin, a writer and leader of the Voluntary Simplicity Movement; performers; world travelers; and others who were greatly energized by the idea of

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sustainable development. They thought of themselves alternately as “volunteers,”7 “a merry band of people with a high degree of inspiration,”8 and “just smart activists.”3 One participant talked about the draw of the nascent organization: People were just very drawn by the idea of talking about sustainability and looking for what we could do, what it meant for us. Everybody could feel something new was needed and sustainability was a very new term with no currency at the time.8

Early discussions were exploratory, generating a lot of creative approaches to the vague topic of sustainable development from different angles. After 6 months of work, they had reached consensus on a name, “Sustainable Seattle: A Volunteer Network and Citizen’s Forum,” an “agreement with each other” that served as a charter,9 and a definition of sustainability as “long-term cultural, economic, and environmental health and vitality” (AtKisson, 1996, p. 2). They discussed local issues they considered important, ranging from child poverty to regulatory pressures on small businesses, to the potential impact of global warming (AtKisson, 1996). Participants say the most valuable part of their early meetings was their “vagueness,”8 their “shared consciousness of change that [they] wanted to create . . . without trying to answer too specifically how to go about it.”3 Early in 1991, the ad hoc group found a home at Metrocenter, the community service and adult-focused branch of the Seattle YMCA. Metrocenter was the chosen site primarily because of member Richard Conlin’s influence as a Metrocenter employee; Conlin suggested that the organization serve as a “Sustainability Secretariat.” Providing infrastructural support for individuals and small organizations interested in community change but not interested in starting a new 501(c)3 nonprofit organization was not a new role for Metrocenter, but S2’s focus on sustainable development rather than the traditional YMCA goals of individual development and leadership was new. Jennifer Parker, executive director of Metrocenter at the time, noted that S2 never had “like cousins across other YMCAs,” because the S2 approach addressed a broader audience and oriented itself closely with policy development. However, Metrocenter was “open to the idea of interpreting community development in a broader way and allowing [the hosting of S2] to happen.”10 The first unofficial S2 Board of Trustees included 19 members, from the city government, the Chamber of Commerce, the Boeing Company, the Audubon Society, the Bullitt Foundation, a religious leader, a labor union leader, university faculty and students, and the Rotary Club. Three people volunteered to serve as cocoordinators: AtKisson, who was the editor of a sustainability-oriented magazine called In Context, Carroll, and Conlin. These three individuals became the “willing triumvirate” who kept S2 focused and moving forward over the organization’s first 5 years (1991 to late 1995). In September 1991, the group established a set of seven goals: 1. To educate ourselves and other citizens about the values, principles, and practices of sustainability 2. To provide a forum for dialogue about the meaning and practice of sustainability

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3. To seek to establish sustainability as a key criterion in planning and decisionmaking 4. To facilitate the development of cooperative partnerships in efforts to move toward sustainability 5. To monitor sustainability through developing indicators of economic, cultural, and environmental health 6. To identify, encourage, and link existing efforts for sustainability 7. To work together to build a more sustainable way of life11 The development of indicators appeared fifth in this list. Maintaining breadth in ideas and approaches to sustainability was more important than any particular approach. It seemed to participants that “whatever you wanted to do, there was space.”8 Members formed committees they called task teams, semiautonomous entities responsible for developing volunteer assistance, funding, or other resource requirements. The original three task teams were the Indicators Project, the Speakers, and Roundtable Task Team, which planned showcases12 and events, and the Publications and Outreach Task Team, which focused on a S2 newsletter and other outreach. Early participant Lee Hatcher explains the group’s coalescence around the idea of indicators this way: When the discussions were first going on about what to do, they revolved around: well sustainability seems like a good concept but how would we start getting it introduced? Because we understood that this was a fundamental paradigm shift we were working on, where you don’t really know what the paradigm’s going to end up being . . . how do you do that? And we came to the conclusion that it was the feedback system that was the big lever that we had. And that’s why we said: indicators!13

Heyday: The Radical New Indicators Experience (1991–1998) The S2 indicator task team’s work continued where the Global Tomorrow Coalition’s forum had left off, to develop a draft set of possible sustainability indicator choices.14 The task team investigated ways to select a set of indicators, when it became clear that this would be a great opportunity for public involvement. In October 1991, Carroll suggested a structure in which a large and diverse civic panel would be set up, drawn from opinion leaders in the different topics of interest. This civic panel would meet three to four times over 6 months with dates and workshop content laid out for participants in advance, so participants would know the time commitment required of them and that they “weren’t committing to too much.”3 Invitations to participate on the civic panel went out to 150–200 people on May 14, 1992. To decide upon the recipients of the letter, S2 volunteers “brainstormed a list of who’s who, the people [they] thought would be the most progressive, interested, good folks who wanted to see something like this happen. In education, health, economics.” In turn, S2 trustees named themselves on the stationery and put “enough names on the invitation letter to get attention.” About one-third of those invited were elected officials, one-third were leaders of

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nonprofits or institutions, and one-third were active citizens and respected opinion leaders, a mix that “would catch the community’s attention but not be coming from any one political party or persuasion.” The letter touched on the upcoming Rio Earth Summit, the opportunity to explore the idea of sustainable community in Seattle, the promise of the idea of sustainability indicators for Seattle and for cities all over the world, and the great reservoir of creativity, common sense, and energy among those who would serve on the civic panel.3 S2 received over a hundred positive responses to the initial mailing. Around 80 of those invited were able to attend the civic panel orientation on June 11, 1992. Through panel and subgroup meetings from June to December 1992, considerable evolution of panelists occurred, with 150 people eventually participating in the process. By the time we got to the third workshop, some people had dropped out, some new people had come in that weren’t real known leaders but they were willing to work. And so something happened by the time we got to the third workshop where just through the process of hearing about it and the original people we involved, we had this whole new group emerge who wanted to be part of Sustainable Seattle.3

Volunteers were prepared as facilitators by Carroll to keep the civic panel process tightly focused and substantive. The process operated according to consensus rules and included detailed feedback forms, brainstorming sessions, group assessments, indicator linkage exercises, implementation strategizing, dramatic readings, and celebration.15 After an orientation, the panel began work by dividing themselves into ten topic areas of interest and expertise: education, transportation, health, resources, economy, social environment, natural environment, population, culture and recreation, and community participation and involvement. They later reconvened as a large group to synthesize the material. Panelists in each topic area were asked to consider what indicators might comprise a complete picture of the city. They asked themselves three questions: which suggested indicators might be key, which might be more secondary, and which would be difficult to measure but provocative and would capture people’s attention? In small topic groups, panelists were asked to do the following: ●

● ●

●

● ●

Define the basic conditions in your topic area that must be met in order to have a sustainable community Provide input on criteria that should be used to select the “best indicators” Review S2’s draft list of indicators in each topic area, and add and modify this list with the group’s ideas Select, in each topic area, what the group considers the best “bellwether” test of movement toward or away from sustainability over time Evaluate each indicator against the “criteria check list” Provide ideas on how best to introduce indicators to the community and media16

Later, in order to narrow the indicator set, panelists engaged in exercises to link indicators into pairs and to map out the ways in which different indicators were connected to one another and to sustainability. One exercise involved the circulation of panelists to other topic groups in which they were not experts, to understand

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the linkages from a different perspective.13 In the last workshop, all indicator selections were put up on the wall and panelists played a “green dot game” in which they selected, using green paper stickers, their “most preferred” indicators overall, creating a comprehensive list of 99 indicators across ten topic areas.17 The average panelist contributed 10 hours of volunteer time over the 6-month period. This process model, described as “alive”8 and “very attention-getting,”3 served S2 well: the civic panel arrived at a list of 99 proposed key indicators across the ten topic areas. Indicators included basic statistics such as “total population of King County” and “adult literacy rate” as well as more creative measures like “participation in the arts” as a measure of community participation and “hours of paid work at the average wage required to support basic needs” as an economic measure. The civic panel was the main catalyst of S2 and the best example of the organization at its prime. It brought out “a fabulous cross-section of the [local] leadership,”18 and established a community vision of and commitment to the indicator project. The other achievement of the civic panel process was group inspiration: “the astonishing power of inspiration that [the process] has . . . people start to ‘get it’ and then they really get engaged with it.”13 Some of those involved reflected on what about the process they found most striking: Our sense of commitment to each other and the future7 The care being taken to include all people and ideas in sensitive dialogue13 The spirit of voluntarism and commitment people expressed The energy and commitment of a group of people (and) remarkable capacity for working toward consensus and sense of open forum The quality of the people and the clarity of what was being sought19

From Public Input to Publication After completing the civic panel process, S2 returned to its core group of about 30 people. From the set of 99 indicators from the civic panel, the task team chose a set of 20 indicators for the initial report, a limitation based mainly on data availability constraints.20 This “winnowing” process involved a lot of “creative, behindthe scenes work,”3 honoring the intentions of the civic panel and keeping the selection criteria while making the most practical cuts. To be selected for inclusion, indicators had to exhibit four characteristics: 1. Bellwether tests of sustainability, and reflect one aspect of something basic and fundamental to the long-term economic, social, or environmental health of a community over generations 2. Understandable and acceptable by the community as a valid sign or symptom of sustainability 3. Interesting and appealing to the local media in monitoring, reporting, and analyzing general trends toward or away from sustainable community practices 4. Statistically measurable in our geographic area, and preferably comparable to other cities/communities; a practical form of data collection or measurement exists or can be created21

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The indicators task team had other parameters. The team also aimed to develop indicators that were: “rigorous” and “logical” without sacrificing the vision, insight, or values of the civic panel or S2 process to date; linked to each other and to a whole picture of sustainability; within their sights for data acquisition; and well presented.22 Because this was a volunteer-driven process, data availability was a key concern. Volunteers pored over public documents and databases, called dozens of officials at all levels of government, and contacted scores of organizations to find the best available data. This forced some changes in the indicators themselves. For example, a measure of “homelessness” selected by the civic panel was changed to “housing affordability,” which had a more reliable data source and is a major condition that causes homelessness. At the same time, certain indicators with no reliable data source were kept as “placeholders” where they seemed absolutely critical. This was the case with the indicators “youth involved in community service” and “hours spent on arts instruction in schools.” The hope was that public or private agencies would begin to track these indicators through the publicity of the report (AtKisson, 1996, p. 3). The task team sorted the indicators into correlated clusters using matrices23 and held an “indicator marketplace” in which draft texts for each indicator were posted around a room for round-robin editing.24 The indicator task team’s efforts to suggest potential causal links between indicators was a major point of interest, both during the civic panel process and in the report. Participants attempted to create lines of causality between indicators in social, environmental, and economic categories. For example, rising child poverty was connected to a decline in wild salmon by postulating that increased child poverty can lead to increased incidence of street crime, which can decrease the perception of safety in the streets, causing people to drive rather than walk, increasing pollution from car exhaust in streams, and ultimately killing salmon. Postulating such linkages was intended to encourage people to think about whole systems, feedback loops, and unintended consequences, rather than to provide definitive explanations. Participants described the linkages they created as “a bit of a stretch” for most readers but significant for providing “intuitive links” between apparently unrelated sustainability issues.2 The process also stressed the ways in which key indicators were related to environmental, economic, and social aspects of sustainability. The indicator task team felt strongly about this: “Connectivity is key to making this process truly reflect sustainability.”25 For example, although the wild salmon indicator was categorized as an indicator of the sustainability of the natural environment, demonstrating water quality and the impact of land-use change, this indicator is also economically important, because of the fishing industry’s large role in the Northwest economy, and socially important, as salmon are a symbol of the Northwest, important to everyone’s conception of the region, as well as critical to the subsistence of native people. People found the interconnected and holistic nature of this process stimulating, exciting, and focused, partly because of the independent and open nature of S2.

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It was a very loosely organized organization and people got to take whatever their area—if you were working on energy or if you were working on transportation or health or whatever, there was a lot of independence working on it. So that energized people and people just got really hooked on it.2

The coordinators and task team leaders also kept an eye on integrating information and assuring quality work. Many civic panel volunteers were recontacted for research assistance on the report. S2 also convened a group of volunteer scientific reviewers and sent each indicator data set out for review. The group paid careful attention to report layout, knowing that design would greatly affect the way the report was seen and read. They worked on breaking the report into simple, bold topics, showing on a single page and in simple language: what’s the indicator, what does it mean, where do the data come from, and what has it got to do with sustainability. The intent was a tactful combination of scientific validity and popular interest: To present these overall trends in a way that quickly communicated the state of the City and its direction of change, while not hiding the complexity of the systems on which its health depended. Organizers used the image of an instrument panel, where the general state was discernible at a glance, but where detailed evaluations were still available for those who wanted them. (AtKisson, 1996, p. 5).

The first 36-page report was released November 8, 1993, the work of at least 200 people and over 2500 hours of volunteer time.26 At a cost of $10 per report, the revenue balanced the organization’s budget for 1993.27 Requests for copies came in from 36 states and 21 nations.28,29 The first printing of 1400 sold out and the second printing sold an additional 1100 copies. Of the 20 indicators measured, the report showed that four were moving toward sustainability, five showed no movement, and eleven were moving away from sustainability (Sustainable Seattle, 1993) (see Table 2). After completing this first round of the indicator process, S2 drafted an organizational plan30 of the critical elements of the process. They included a commitment to work in the spirit of trust, respect, and participatory, shared leadership “which allows roles and responsibilities to be flexible, but clearly delineated,” with meeting facilitators to help “maximize inclusion and participation, while also making sure that decisions get made and projects get done.” Other successful elements of the process were consensus-based decision-making, interpersonal relationships, and the notion of continuous learning, allowing participants to learn from mistakes, innovate, and “change course if that is what best serves our overall mission and specific goals.” The second report was updated and rereleased on November 15, 1995, now including the full set of 40 indicators. S2 employed a local survey firm to research more subjective indicators like perceived quality of life (QOL) and neighborliness in Seattle. The difficulty of collecting information increased with this report, because many of the final 20 indicators had never been measured (AtKisson, 1996). This report was the work of over 250 volunteers and sold over 4500 copies at $15

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Table 2. Sustainable Seattle’s 1993 Indicators of Sustainable Community.

POPULATION and RESOURCES

ENVIRONMENT

Indicator

Trend

Number of good air quality days per year Percentage of Seattle streets meeting “pedestrian-friendly criteria” Wild salmon runs through local streams Gallons of water consumed per capita in King County Total population of King County Tons of solid waste generated and recycled per capita per year in King County Vehicle miles traveled per capita and gasoline consumption per capita Renewable and non-renewable energy consumed per capita

ECONOMY

Percentage of unemployment concentrated in the top ten employers Hours of paid work at the average wage required to support basic needs Percentage of children living in poverty Housing affordability for median- and low-income households Per capita health expenditures Library and community center usage rates

CULTURE and SOCIETY

Percent of youth participating in some form of community service Adult literacy rate Participation in the arts Percent of population voting in odd-year (local) primary elections Juvenile crime rate Percentage of infants born with low birthweight

apiece. It was also reprinted and distributed in the United Kingdom by Local Agenda 21, a nongovernment organization working to implement the United Nation’s Local Agenda 21.31 Results in 1995 showed that 8 indicators were moving in a sustainable direction, 18 showed no trend, and 14 were declining in relation to sustainability (Sustainable Seattle, 1995). The third and, to date, final report was released on April 20, 1998.32 A group of 75 mostly new volunteers were primarily responsible for preparing it.33 At $15 apiece, the report sold 600 copies by December 199834 and orders for this report continued to trickle in to S2 thereafter. Table 3 shows the 1995 and 1998 Indicators of Sustainable Community, along with the trends observed in each report.

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Table 3. Sustainable Seattle Indicators of Sustainable Community with 1995 and 1998 trends (Sustainable Seattle, 1995, 1998). Indicators

Air quality Pedestrian and bike-friendly streets Impervious surfaces Open space near urban villages Wild salmon returning to spawn Wetland health Biodiversity (amphibian & plant) Soil erosion

Air quality Pedestrian& bike-friendly streets Impervious surfaces Open space near urban villages Wild salmon returning to spawn Ecological Health

Voter participation Library & community center use Perceived quality of life Equity in justice Low birth weight infants Gardening activity Neighborliness Public participation in the arts Childhood asthma hospitalization

POPULATION and RESOURCES

Adult literacy High school graduation Ethnic diversity of teachers Arts instruction Volunteer involvement in schools Community service by youth Juvenile crime

Pollution prevention Total water consumption Population growth rate Solid waste generated & recycled Vehicle miles traveled and fuel consumption Local farm production Renewable & nonrenewable energy use

ECONOMY

Employment concentration Real unemployment Work required for basic needs Community capital Distribution of personal income Health care spending Housing affordability ratio Children living in poverty Emergency room use for non-ER

1998

Soil erosion

Energy use per dollar income Employment concentration Unemployment Emergency room use for non-ER Housing affordability ratio Community reinvestment Work required for basic needs Distribution of personal income Health care spending Children living in poverty

YOUTH and EDUCATION

Population growth rate Pollution prevention & renewable resource use Solid waste generated & recycled Vehicle miles traveled and fuel consumption Residential water consumption Farm acreage Renewable & nonrenewable energy use

ENVIRONMENT

Indicators

Equity in justice Volunteer involvement in schools Adult literacy High school graduation Ethnic diversity of teachers Arts instruction Community service by youth Juvenile crime

HEALTH and COMMUNITY

1995

Voter participation Gardening activity Public participation in the arts Library & community center use Perceived quality of life Low birth weight infants Neighborliness Childhood asthma hospitalization

Boldfaced type connotes changes in indicator placement or definition from the 1995 to the 1998 report. Arrows indicate the nature of the sustainability trend in each indicator category: a larger upward-facing arrow means more indicators tending toward sustainability in a category and downward-facing arrow means negative sustainability trends in the corresponding indicators. Sideways-facing arrows indicate either an indeterminate trend or insufficient data.

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Getting the Word Out Many of those involved in S2 were well connected to the international sustainable development movement, giving the indicator reports a good deal of word-of-mouth publicity. At a Town Meeting on the Earth Summit in Seattle in late 1991, Conlin made a presentation about S2, its early activities, and its quickly growing reputation: Although we have not attempted to secure media attention as yet, we have been overwhelmed by the number of people who want to be involved in this project. New volunteers appear every day, having heard about us from friends and associates. An astonishing number of people are working on education or action projects to promote sustainability . . . . While we were initially concerned whether it was possible to get people involved in a concept as difficult to define as “sustainability,” our current concern is how to successfully manage the human resources and energy that the concept arouses.35

This interest snowballed through many parts of the world. Table 4 shows a sampling of the speaking occasions to which S2 was invited in the 1990s. Requests for the reports poured in from as far afield as Lebanon, Hungry, Austria, and Costa Rica36: “Somewhere in there, the grapevine took over; we were sending copies of

Table 4. Invited presentations on S2’s Indicators of Sustainable Community 1991–1999. Year

Invited Presentation

Location

1991 1992 1992 1992 1994 1994 1994 1994 1994 1994 1994

UN Preparatory Committee for the Earth Summit Belgian Environment Ministry39 Department of Housing and Urban Development40 Balaton Group41 annual meetings Upper Valley 2001 conference Sustainable Santa Barbara42 Dutch Ministry for Environment and Spatial Planning Society for Sustainable Living Conference43 Sustainable St. Louis39 Heinz School39 Federally sponsored videoconference on urban sustainable development President’s Council on Sustainable Development (PCSD) Global Forum ‘9444 Defining Sustainable Communities conference Sustainability Indicators Congress Kansas State College conference Sustainability indicators conference Habitat II conference45 Quebec Union for Sustainable Development Forum International Network of Green Planners conference46 International Network of Green Planners conferences46 Sustainability conference47

New York Brussels Washington

1994 1994 1994 1994 1995 1995 1996 1996 1998 1999 1999

Vermont Santa Barbara The Netherlands Prague, Czech Republic St. Louis Pittsburgh Seattle Seattle Manchester, UK Berkeley The Netherlands Kansas France Istanbul Quebec Brussels Curitiba Hawaii

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the report everywhere, it was getting talked about in conferences.”37 In December 1996, S2 received visits from reporters from Swedish National Broadcasting and Korean radio for interviews.38 Word reached S2 that a Sustainable Penang organization had been created after the Malaysian representatives at the 1996 Habitat II conference learned about the initiative (Teng, 1999). S2’s work also reverberated to the head of Mongolia’s environmental planning department.47 Diffusion in other states and countries happened beyond the control of S2 members. Somehow [the indicator project] got written up in things and talked about and people would call in and write for the report, so. It just took off and before we knew it, we were more popular in other places than in Seattle.3

S2 leaders insist that they traveled to present their work only where invited. Thus, S2 did not drive the diffusion of the indicator reports, but followed this diffusion.39 S2 demonstrated an innovative, highly transferable, and successfully implemented idea for those committed to sustainable development in their home place, and the ranks of such committed people were growing throughout the 1990s.

Spin-off Phase and Spinning the Wheels? Center for Applied Sustainability (1994–1998) After the publication of the first report in 1993, S2 began to branch out. The indicators project settled into six work groups—update, linkages, economy, environment/resources, youth/education, and health/community—that continued to develop, disseminate, and market the indicators. A second branch of the organization focused on communities outreach, with a diversity of projects to take the ideas of sustainability to the city’s neighborhoods and apply them. These projects were pursued by ten work groups: neighborhoods, business, home, database, recognition awards, dramatic presentations, workshops, seven steps, and sustainability summit and a policy task team. S2’s goal for application of the indicators and ideas of sustainability generally was ambitious: To enable and inspire people in the many different communities of Greater Seattle to transform the values of sustainability into actions that will move Seattle, the region, and the planet towards long-term cultural, economic, and environmental health and vitality . . . . We will use the Indicators as a primary education tool, particularly to emphasize linkages among the different indicators and actions that affect them.38

Amid the proliferating organizational activities in the mid-1990s, S2 trustees were concerned that they were working beyond their capacities, that their organization “may not hang together as well as would be optimum,” and that task teams were not communicating.48 Also, as the organization became more professional and segmented, “it seemed it was less about our lives, less a citizen effort.”8 Although one of the organization’s goals stated in the 1996 organizational structure was to “work together in the spirit of joy, service, and community,” no hint of “working together”

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as a goal is to be found in the 1997 version of the organizational structure. By 1997, the director was asking for help from the board to keep the programs going.49 The idea to make S2 a center for applied sustainability as opposed to a volunteer network and civic forum appeared in late 1997. Creating a center for applied sustainability meant that S2 would not only continue volunteer-based work but also build partnerships with other groups in the area, using international connections to “feed new approaches to local organizations” and to launch its own projects.13 To advance the center for applied sustainability concept, the board published its first brochure and revived the quarterly newsletter. The board also created, in conjunction with other local sustainability groups, a sustainability library. Consulting on sustainability indicators was another piece of the work that members of S2 had been doing since 1995. Consulting contracts with groups from King County to California to China provided S2 with much-needed revenue, helped keep part-time staff employed, and spread the organization’s experience and insights on creating indicator projects to government agencies and nongovernment organizations elsewhere. These contracts also continued S2’s involvement with indicators after the reports no longer were being produced. On the other hand, contract work diverted attention and energy from serving S2’s leadership needs, other program initiatives, volunteer recruitment, and organizational needs. During this time, many active volunteers dropped out. While the core S2 group was struggling to launch various new efforts, S2 seemed to vanish for many of the volunteers who had been active with the 1998 indicator report. Once the indicators report was done, that was it . . . . I definitely was interested in continued involvement, but . . . we had this major focus of putting the document together, but then beyond that, there wasn’t [effort to] develop a plan to make improvements on each of these indicators and . . . actually move forward instead of just tracking . . . it wasn’t so much lack of vision or the people didn’t want to do it but it kinda’ wasn’t possible . . . .41

This feeling was contrary to the board’s intention: You don’t want to keep doing those unique, isolated things that just operate by themselves and spin off . . . . I’ve been involved in a lot of groups in the beginning and I know that often times the people who do that piece of it can’t move it to the next stage, whether it is out into more institutional realms or getting an organization that’s funded well enough that it can continue.2

Hatcher describes the volunteer indicator work as: “a burnout job. We got turned off indicators, I got turned off for a while even, you’re working another job and you’re doing this incredibly complex thing. So, the volunteer base kind of disappeared for a long time because they just couldn’t do it!”13 As much as this was a burnout problem, it was also an organizational problem. S2 did not devote time and energy to recruiting new volunteers and maintaining volunteer interest. The indicator project had initially been so exciting and rewarding for volunteers that many sought to find the next “big” project: “We got so much recognition for the

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indicators that . . . following that act is not something that needs to be sustained. But sustained is not the same thing as getting recognition, rewarded . . . making that kind of a splash.”51 When volunteers were not able to immediately find another project able to make a “splash,” many became discouraged. Those involved speak of this period as a time when “we were just spinning our wheels and trying to get organizationally going,”52 spending more time on organizational issues than on sustainable development. The organization’s activity and notoriety had risen to a peak and was struggling to plateau at a stable platform of performance. One founder, Vicki Robin, describes the early S2 work as “beachhead-work, you know, pioneering work. We founded a community and grew into it.” Despite efforts to regain and build upon that founding community, “we never found that next voice.”8 Some of the work groups in the communities outreach project, like the neighborhood network and the guide for sustainable living, partially fulfilled their goals, but none received anything like the “splash” of the indicator project and all had disbanded by 1998.

Changeover and Downturn: Leadership, Volunteer Base, and Organizational Structure (1996–1999) S2 underwent a major downturn in energy and productivity that began in 1996 and worsened from 1998 to 2001. This happened while sustainability ideas gained popularity in the local government and in the region at large. It is striking, if not ironic, that one organization in the Seattle area focused explicitly and exclusively on sustainability was struggling. At the staff and trustee retreat in March 1996, trustees expressed their concerns that the organization had become too reliant on its three original leaders: AtKisson, Carroll, and Conlin, that its volunteer-based structure was not sustainable, and that it had lost its organizational vision: We can’t depend on a willing triumvirate who have more to do in their lives. Procedures for transfer of power, decision-making, communication, and outreach all need to be determined. There’s a whole history of how we got here, and we were trying to solve yesterday’s problems with yesterday’s good ideas at the time. Bottom line, too big a container, too few people in it, not enough critical mass. We were trying to make an effort to involve lots of people, to accommodate anyone who wanted to volunteer with us. But we need to be thinking now in terms of mission, and what structure will accomplish that mission (rather than trying to keep people busy).53

The energy and intensity of early S2 benefited greatly from its strong core and mostly volunteer leadership. One by one, members of this core group left for other pursuits and resigned from the board. Conlin announced that he was leaving Metrocenter in February 1996 due to “some difficult administrative and fundraising challenges [that] made me believe that my position could not be effectively funded without adversely affecting the success of the programs that I oversee.”54 He went to work in publishing and then to his current position on city council.

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AtKisson announced that he was leaving for San Francisco on March 31, 1996, to work with the policy research organization Redefining Progress on that group’s indicator research effort. In 1995, Carroll shifted from being a trustee and coleader to an advisor in order to take on the work of producing the guidebook. In 1996, she had to retreat from this level of involvement again in order to address a serious illness. Another leader, Vicki Robin, began serving more of an advisory role as she put more time and energy into pursuing her efforts with the New Road Map Foundation and the Voluntary Simplicity Movement.55 Steve Nicholas left Seattle for a temporary planning position overseas. AtKisson wrote to the current S2 board in March 2000 to admit that he “hit a wall with regard to my work with S2 after about 5 years; I, and others of my cofounding colleagues, were ready to move on. I imagine that many if not most of you might feel similarly now.”56 He encouraged the current board “to reconsider any decision to merge S2 into another entity, unless you are very sure that S2’s legacy will continue in a way that maintains its identity and refreshes its capacity for innovation.” He told the board how much he would prefer to see them recruit their own replacements “from a younger (at least in energy and experience) cadre of Seattleites hungry to both make their mark on the city and advance sustainability in some way that the city and county cannot do.”56 The issue of the organizational transition from an organization with a pure volunteer base to a volunteer base with staff and board support first arose in 1994, upon the award of S2’s largest grant yet, $40,000 from the Bullitt Foundation. It seems virtually certain that momentum on all fronts will continue to build as time proceeds. Given the likelihood that the organization will continue to expand its activities, perhaps the key issue facing Sustainable Seattle is how to successfully evolve from being an almost entirely volunteer based entity to one that effectively utilizes staff support in ways that enhance and nurture the efforts of current and future volunteers. This will be a delicate transition, yet it is also one that is appropriate to address now.57

There was even discussion in 1994 over whether or not to accept this grant, for fear that the money would make volunteers compete with one another over funds. In early 1996, the director admitted: “We need to recognize that we are asking people to invest a lot of time and energy, and should be open to the question of whether there ought to be a monetary incentive.”58 Only a handful of S2 members remained who felt at all strongly about the indicators. The value and importance of what the group had accomplished with the indicator reports had not quite established itself as an institutional value by the time its original core moved on. The organization faced these organizational and leadership changes at the same time as the pressure from Metrocenter for financial independence mounted. The YMCA Metrocenter Executive Committee began to insist that S2 meet some minimum budgetary requirements. Between 1995 and 1997, the infrastructure at Metrocenter, so helpful for S2 in its early days, became restrictive. As S2 stepped up its fund-raising efforts, the organization had to observe the YMCA clearance process, which basically meant that S2 was unable to apply for the same

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grants as Metrocenter. At the same time, S2 was required to work with the Metrocenter Finance Committee and Board of Management to produce a balanced budget, including $30,000 new funding. Metrocenter warned S2: If the March [1996] review of the Sustainable Seattle budget suggests the likelihood of a substantial deficit, you should be aware that a swift termination of Metrocenter’s financial support of the program will be a clear possibility. Such a decision will not reflect any lack of interest for 1996 in Sustainable Seattle by Metrocenter, but will rather be a reflection of the fact that Metrocenter does not have the flexibility of investing substantial financial or management resources in Sustainable Seattle.59

At the strategic planning retreat in October 1996, S2 trustees had goals to build organizational self-sufficiency, focusing on linkages to more communities and circles of interest, diversifying volunteer involvement, and demonstrating sustainability in a pragmatic way.60 At the strategic planning retreat in February 1999, by contrast, the goals had changed. The five continuing board members and six new board members had goals that included: “integration of board members into a cohesive, familiar team” and “build team attitude among board of directors, staff, and program team.” They questioned the continued utility of S2’s indicator project. When discussing criteria for selecting new projects, members selected “missionfocused” and “business-like/accountable” as most important, while “Is there any passion for it?” “inspires others to action,” and “creates impact” fell to the bottom of the list.61 In 1997, Metrocenter began a “cash in hand” policy with S2, meaning the organization needed to contribute money “before we can make a copy, use the phone, or send mail.”59 Metrocenter’s stated policy in 1997 was to lay off S2’s program director if financing was not sufficient by June. Metrocenter staff had trouble obtaining information regarding financial forecasting and felt undervalued by S2: [Sustainable Seattle] had strong support from the outside and I think they felt to a degree that the Y was taking advantage of them, whereas the Y was feeling like, hey, we’re supporting you, we’re trying to do everything we can here and we’re not really getting appreciated . . . .10

In the end, Metrocenter found some of S2’s amateur accounting questionable and S2 members understood they had outstayed their welcome. S2 moved into independent office space in the near-downtown Cascade neighborhood in early January 1998.62

Near-Death Experience: Losing the Amoeba for Sustainability (1998–2001) Moving out of Metrocenter relieved the group of increasingly cramped operating conditions, but required a much more aggressive fund-raising campaign to cover salaries, rent, and overhead. This move also necessitated incorporation of S2 as a formal 501(c)3 tax-exempt nonprofit organization to allow tax-exempt donations,

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facilitate grant administration, and limit any liability of board members. This process was finalized on May 28, 1998.63 A meeting announcement in November 1997 begins with the following: “Money, Money, Money, Money. We need money! This meeting will be devoted to identifying funding opportunities and making commitments to pursue them.”64 This was reiterated the following month: “We still need operating money for programs and the office.”56 Board members redoubled their funding efforts but still came up short. They began targeting businesses to approach for fund-raising,66 consulted with professional fund-raisers,65 and discussed tactics such as retaining a loaned corporate executive, soliciting sponsors for specific indicators, holding house parties, and selling memberships. From June 1996 to June 1997, they sent out six grant letters and all were refused.59 In 1997, identification of 23 high-priority foundations resulted in donated equipment—desks, file cabinets, and partitions—from the local offices of Adobe and a $10,000 grant from Boeing.67 The difficulties encountered in fund-raising confounded even the experienced fund-raisers of S2. Trying to raise money for [Sustainable Seattle] is difficult, although I couldn’t understand why. I mean, it seemed like it had reputation, it had product, it had track record . . . why it couldn’t have gotten some significant funding under it, I don’t understand.2

Once a free-flowing volunteer community or an “amoeba-like organism with a certain level of complexity and a very clear goal,”3 S2 sought to become less chaotic and more governed. This fundamentally changed the role of the director and ultimately all those involved. To some founding members, this transition into a more structured organization was a very risky and creatively costly path. It’s a classic transition problem. We create something beautiful and then we try to put it in a container and it’s a very delicate thing figuring out how to put it in a container so that it’s still a living system and can keep going.8 Sometimes whatever that special magic is, or that something, you can’t—when you start trying to structure it, or package it, or whatever, you run into trouble.2

Frequently, the board discussed whether to continue the indicator work or pass it off to government.2 Conlin as city council member pushed S2 repeatedly in 1998 and 1999 to support his proposal to city council to create an office of sustainability that might eventually adopt S2’s indicators.68 The organization could not offer such support: “Rather than forming a separate department, we believe it is better to focus on ways that sustainability can be institutionalized throughout every city department. S2 wants to work with Richard to help make that happen.”69 The best thinking of the group continued to be that the advantages of an independent indicator effort outweighed the costs to the organization trying to keep it going. In October 2000, the board discussed again the future of the organization, after reviewing the financial report and determining “that money will effectively run out by the end of February unless we find other large sources of income,” and that they were “nearing the point of either initiating, with large funding, some significant new programs, or declaring victory and closing the doors.”70 For every

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board member who brought up the notion of folding the organization, however, there were always a few who replied: “we still think there’s something else to do, we’re just not completely sure what it is.”7

Torch Holders and Reorganization (2001–2004) Into the financial, organizational, and leadership crises stepped board member Marc Daudon, a principal of Cascadia Consulting, a Seattle-based environmental consulting firm. A partnership was negotiated in which Cascadia loaned S2 an executive director and office space and Cascadia gained a connection to sustainable development work that was broader than the firm’s environmental science focus.62 This partnership worked effectively to recruit a strong new board, establish a new program of work, and retain sufficient grant financing by 2004 to reestablish S2 with a new independent downtown Seattle office, a new executive director independent of Cascadia, and an additional full-time staff member. The new slate of projects taken up by S2 during this phase has had three main prongs: the development of a “putting sustainability into action” educational curriculum, reminiscent of the former sustainability curriculum task team, a sustainable community outstanding leadership awards program, reminiscent of the former legacy awards program, and the neighborhood indicators project. The neighborhood indicators project, begun in 2002, works within four disadvantaged neighborhoods to develop neighborhood-specific indicators based on existing neighborhood plans and street-level surveys of conditions. Entitled “Improving Quality of Life in Seattle’s Neighborhoods: Using Community-Based Performance Indicators to Measure What Matters,” the project has been funded by the Alfred P. Sloan Foundation from 2003 to 2007.63 The project retains S2’s traditional focus on public participation, recognizing linkages among issues and collaborative decision-making as crucial steps to solving systemic problems. Problems of crime, poverty, pollution, and unemployment, etc., need to be viewed with a mindset that seeks linkages which might not be initially obvious. Moreover, solutions need to be carefully examined to make sure that in solving one problem, we don’t inadvertently make another one worse. We believe that effective solutions are more likely to come out of processes that involve all stakeholders in a community—neighborhood residents, nonprofit organizations, local businesses, and government agencies. (Sustainable Seattle, 2003, p. 5).

The neighborhood indicator project was also designed to correct some perceived shortcomings of the original indicators project, primarily in the realm of connecting indicators to action and to policy: “the S2 Board believes [the Indicators of Sustainable Community] reports have missed the mark in significantly influencing actions and expenditures of local governments in the Seattle region” (Sustainable Seattle, 2003, p. 6). Current board members explain the difficulty in perceiving pathways to action in the original Indicators of Sustainable Community:

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. . . the scale of it is really hard for individuals to relate to because they don’t feel like they can influence it. So things like kids that drop out of school or salmon returning to certain streams . . . we may be interested in it, but . . . it’s not anyone’s agenda.73 The problem with our indicator process is that you can measure all these things but the responsibility to do something about them? . . . It’d be nice to find a way to really bring it back to the public officials and say, here’s the snapshot of where we are . . . and we need to make changes in these areas. And then be able to go back five years later and say, oh look! We changed our priorities and now we’re improving things.50

Another significant departure of this project from the original indicators project is in the absence of the language of sustainable development, opting instead for “a way to assess trends in a neighborhood’s perceived quality life” (Sustainable Seattle, 2003, p. 5). The project’s intent is to “identify activities, conditions, or services required within the neighborhood so that quality of life can be improved and sustained over the long term” (Sustainable Seattle, 2003, p. 13). One result of this practical QOL focus is a substantial level of buy-in from neighborhood participants who would have been more wary of a larger visioning process reminiscent of the neighborhood planning process of all Seattle’s neighborhoods undertook in the late 1990s. Another result is that the project has been unable to articulate the relationship of fixing sidewalks and street trees, for example, to progress toward a neighborhood vision, at least in its first year.74 The neighborhood indicators project is designed to tie neighborhood action goals and progress indicators to agencies responsible for action, to funding sources, and to deadlines for action. The call is for fiscal accountability: “Citizens have a right to know how effectively their tax dollars are being used” (Sustainable Seattle, 2003, p. 5). S2 hopes to institutionalize the monitoring process in each neighborhood, recognizing that change may not be apparent for several years. S2 foresees working toward city adoption of the project entirely by 2008: “S2 expects to have a continuing but less central role as the project matures and becomes institutionalized in city government” (Sustainable Seattle, 2003, p. 23). In 2004, the S2 board resolved to launch a renewal of the original indicator project, now referred to as the regional indicators project. The renewal effort will share some of the elements of the original indicator project and reinvent others. For example, the project may retain 20 of the 1998 indicators and select 20 new indicators, and the effort may enlist paid facilitators to guide the volunteer-driven work. Past members who were involved with the original indicator effort have been contacted to draw their experience back into the project. Fund-raising, consultation, organizing, and delegating responsibilities for the project, and nearly all other details remain to be determined.75 The next phase of the S2 life cycle, as the signature sustainability indicator project is reinvented and rereleased, will tell whether the sustainability indicator project can be considered the project capable of tying together the organization despite 14 years of often tumultuous, evolutionary change. The renewed regional indicator project is expected to be reported out in mid-2006.

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Conclusion The prototype sustainability indicator project, S2’s Indicators of Sustainable Community, originated as the initial operational arm of a much broader body of concern for local sustainable development. From its origins, S2 pursued sustainability indicator reporting as the best project to address environmental, economic, and social equity concerns under the umbrella of sustainable development. To S2, the challenge of sustainable urban development was a challenge to change the underlying logic that drives development by planning with a more integrated sense of the relationships among different planning issues and by looking farther into the future to determine the best course of action. The civic panel process was the keystone of the project’s success and the indicator reports are the organization’s “flagship”76 that draw in a diverse array of contributors to the worthy and difficult goals of sustainable development. Conlin described the indicators’ primary utility as a “conversation piece:” The indicators were kind of the conversation piece, around which conversations could be structured. And they gave us a focus and information and things that people could look at and say, yes, this is something worth talking about . . . . 7

More than this S2 has grown from a group with minimal financial needs to a competitor for major grants and partnerships with government agencies and businesses, and from a volunteer-based “amoeba” with a groundswell of support to a tightly managed nongovernment organization governed by a board of professionals. The many shifts in priorities, organizational structure, and human and financial capital insecurities faced by S2 are not uncommon among nongovernment organizations with similar beginnings and aspirations. The organization’s persistence through the last 16 years of such changes and challenges set it apart, as does the continued name and product recognition of S2 within the sustainability indicator movement. More than this, what could prove truly unique about S2 would be its ability to learn from its organizational history, even as a mostly new group of people in the different civic, national, and international context of 2006, as S2 reinvents its signature indicator project. Within the S2 story are ready lessons in the value of collaboration across civic interest groups not generally accustomed to working together but of recognizing and valuing even tenuous and intuitive links between diverse issues, of sensitivity to power and hierarchy issues rolled up inside what is on the surface of a rational, straightforward project to measure and report on indicators.

Notes 1. 2. 3. 4. 5.

The organization, Walter Corson’s Global Tomorrow Coalition, is now defunct. Sheila Kelly, early Sustainable Seattle trustee, interview March 20, 2002. Nea Carroll, Sustainable Seattle cofounder, interview April 18, 2002. Steve Nicholas, quoted in Sustainable Seattle “Process Notes,” July 21, 1994. Global Tomorrow Coalition and Citizens International Center (1990, December). “Sustainable Seattle: developing indicators for future progress.” Washington, DC.

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6. Global Tomorrow Coalition (1990, November 12). Background on indicators of sustainability. Preliminary Draft for discussion in advance of the Sustainable Seattle Forum. 7. Richard Conlin, Sustainable Seattle cofounder, interview January 9, 2002. 8. Vicki Robin, Sustainable Seattle cofounder, interview April 4, 2002. 9. Trustees for Sustainable Seattle (1991, June 6). “Our agreement with each other.” 10. Jennifer Parker, Metrocenter YMCA executive director, interview June 11, 2002. 11. Sustainable Seattle Trustees and Participants (1991, October 15). Meeting Reminder and Progress Report. 12. The showcase, called “Sustainability Night Live,” included skits such as: “Lifestyles of the Frugal and Obscure,” “The Price is Wrong,” “Mr. Rogers’ Sustainable Neighborhood,” and “As the Planet Turns” (Wilkins et al., 1995). 13. Lee Hatcher, early Sustainable Seattle trustee and former executive director, interview June 20, 2002. 14. Sustainable Seattle (1991, December 12). “Progress Report.” 15. Sustainable Seattle (1992). “The 1992 Civic Panel Process—An Overview.” 16. Sustainable Seattle (1991). “Civic Panel Discussion Guide.” 17. Sustainable Seattle Trustees (1992, December). Minutes and civic panel workshop notes. 18. Davidya Kasperzyk, early Sustainable Seattle trustee, interview March 22, 2002. 19. Sustainable Seattle (1994, July 12). Process notes from the All-Volunteer Meeting. Quotations from AtKisson, Kit Perkins, and Bruce Herbert, respectively. 20. Sustainable Seattle (1993, May). Proposed Key Indicators of Sustainable Community Version 8. 21. Sustainable Seattle (1992, October 22). Civic Panel Meeting No. 3: Indicators of Community Sustainability. 22. Indicators Project Task Team (1993, February 3). Re: Indicators winnowing meeting and indicators technical development next steps process and proposed key indicators. 23. “Memo to Indicators Project Task Team from Richard [Conlin], Nea [Carroll], Alan [AtKisson]” (1993, January 21). Re: New meeting dates. 24. “Memo to Indicators Project Task Team from Richard [Conlin], Nea [Carroll], Alan [AtKisson]” (1994, June 9). Re: Task team meeting. 25. “Memo to Indicators Project Task Team from Richard [Conlin], Nea [Carroll], Alan [AtKisson]” (1993, February 17). Re: Indicators winnowing meeting. 26. Richard Conlin. (1995, February 6). Letter to Jim Diers from the trustees of Sustainable Seattle. 27. “Memo to Indicators Project Task Team and new participants from Richard [Conlin], Nea [Carroll], [AtKisson]” (1994, January 28). Re: Task team meeting. 28. Sustainable Seattle (1994, Summer). Newsletter Issue No. 5. 29. Sustainable Seattle (1994, Winter). Newsletter Issue No. 6. 30. Sustainable Seattle (1995, March). Organization Plan, p. 6. 31. Doug Schuler (1995). “New community networks: Sustainable Seattle participatory action research.” Available at www.scn.org/ip/commnet/appF.htm. Accessed on March 5, 2003. 32. Lee Hatcher (1998, May 13). Report to the Board. 33. Richard Conlin (1997, June 3). Letter to Indicators Task Team. Re: Indicators update. 34. Lee Hatcher (1998, December). Executive Director’s Monthly Board Report. 35. Richard Conlin (1991). Testimony Before the Town Meeting on the Earth Summit: “Grassroots initiatives for sustainability.” Presented on behalf of the Trustees of Sustainable Seattle. 36. Sustainable Seattle (1994, Spring). Newsletter Issue No. 4. 37. Alan AtKisson, Sustainable Seattle cofounder, interview November 25, 2003. 38. Sustainable Seattle (1996, December 4). “Notes from trustee meetings held on November 13 and December 2.”

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39. Sustainable Seattle (1992, October). Newsletter Issue No. 2. 40. “Memo to Trustees, Indicators Project Task Team, Sustainable Community Task Team from Richard [Conlin], Nea [Carroll], Alan [AtKisson]” (1993, November 18). Re: important dates, update on activities. 41. The Balaton Group, also called the International Network of Resource Information Centers, was founded in 1981 by Donella and Dennis Meadows. The group is a network of more than 200 scientists in 30 countries, promoting sustainability in their own countries and gaining access to one another’s ideas, publications, teaching and research tools, training, data, funding, and moral support. 42. Alan AtKisson (1994, May 11). Letter to Betty Miller and Donella Meadows. Re: Report on Santa Barbara trip. 43. Sheila Crofut (1994, December 12–14). “Sustainable Seattle.” Paper presented at the Society for Sustainable Living Conference, Prague, Czech Republic. 44. Sustainable Seattle (1998, November 11). Board Meeting Minutes. 45. Sustainable Seattle Trustees (1995, January 6). To coordination team, trustees, all Sustainable Seattle volunteers. Re: Coordination team meeting. 46. Sustainable Seattle (2000, March 13). Board Meeting Announcement. 47. Sustainable Seattle (1998, November 11). Board Meeting Minutes. 48. Richard Conlin (1995, January 24). Memo to coordination team. Re: Processing the results of the planning retreat. 49. Sustainable Seattle (1997). Trustee Board Commitments. 50. Christy Halvorson-Shelton, current Sustainable Seattle board member, interview May 17, 2002. 51. Mark Aalfs, current Sustainable Seattle board member, interview April 10, 2002. 52. Susan Hall, early Sustainable Seattle trustee, interview July 15, 2002. 53. Sustainable Seattle Staff and Trustees (1996, March 23). Retreat notes. Quotations from Vicki Robin, Alan AtKisson, and Richard Conlin, respectively. 54. Richard Conlin (1996, January 3). Letter to coordination team members. Re: Leaving Metrocenter. 55. The Voluntary Simplicity Movement is an informational and motivational campaign to exemplify and promote “conscious, simple, healthy, and restorative living,” which usually means living with less money, spending less time on waged work, and paying more attention to the ethics, attitudes, expectations, and beliefs surrounding all actions (www.newroadmap.org). 56. Alan AtKisson (2000, March 13). Letter to Sustainable Seattle Board. 57. Minor Lile (1994, July 27). Letter to planning team. Re: An alternative proposal for utilizing the Bullitt Foundation Award. 58. Kara Palmer (1996, March 17). Letter to Sustainable Seattle stakeholders. Re: Critical time of programmatic and organizational changes. 59. Sustainable Seattle. (1997, July 9). Board meeting minutes, transition plan, and the case for Sustainable Seattle. 60. Program Team (1996, December 9). Memo to trustees. Re: Next steps for trustees. 61. Sustainable Seattle. (1999, February 28). Work Plan Retreat Agenda and Notes. 62. Sustainable Seattle (1997, December 4). Board Meeting Announcement. 63. Pamela Cairns (Graham and James LLP/Riddell Williams). (1998, June 1). Letter to Lee Hatcher Re: Internal Revenue Service. 64. Sustainable Seattle 1997 (6 November). Board Meeting Announcement. 65. Sustainable Seattle (1997, April 8). Board Meeting Announcement. 66. Sustainable Seattle. (1997, March 5). Draft Funding Strategy. 67. Sustainable Seattle (1998, May 11). Board Meeting Announcement.

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Sustainable Seattle Board Minutes., December 14, 1998 and January 11, 1999. Sustainable Seattle (1998, November 11). Board Meeting Minutes. Sustainable Seattle (2000, October 12). Board Meeting Minutes. Pamela Cairns (2000, October). Letter to Sustainable Seattle Re: Draft agreement with Cascadia Consulting. Rick Krochalis, former Sustainable Seattle board president, correspondence June 16, 2003. Rick Krochalis, interview March 20, 2003. Michelle Caulfield, Sustainable Seattle staff, interview August 20, 2004. Chantal Stevens, Sustainable Seattle executive director, interview August 20, 2004. Sustainable Seattle (1992, December 17). Planning meeting notes.

References AtKisson, A. (1996). Developing indicators of sustainable community: lessons from Sustainable Seattle. Paper commissioned by Environmental Impact Assessment Review. San Francisco: Redefining Progress. Sustainable Seattle (1993a). Definitions of Sustainable Development, Principles of Sustainability, Sustainable Communities Categories for Work Groups, Group Discussion Guide Developing the Assessment Framework. Seattle. Sustainable Seattle (1993b, 1995, 1998). Indicators of Sustainable Community. Seattle. Sustainable Seattle (2003, April). Improving Quality of Life in Seattle’s Neighborhoods: Using community-Based Performance Indicators to Measure What Matters. Grant proposal submitted to the Alfred P. Sloan Foundation. Seattle. Teng, H.N. (1999). The Sustainable Penang Initiative. Remarks given at Mayors’ Asia Pacific Environmental Summit, Honolulu, HI (January 31–February 3). Available at http://www.csis.org/e4e/Mayor42Teng.html True, K. (1996, December 11). Made to last. Seattle Weekly. Wilkins, F., Kass, S., and Ruben, B. (1995). Sustainable humor. Environmental Action 27(2):10. World Commission on Environment and Development (1987). Our Common Future. New York: Oxford University Press.

MEG HOLDEN, Assistant Professor, Simon Fraser University [email protected]

Using Community Indicators to Improve the Quality of Life for Children: The Sacramento County Children’s Report Card NANCY FINDEISEN President and Chief Executive Officer, Community Services Planning Council Inc.

While speaking at a convocation of community leaders at the Community Services Planning Council’s (CSPC) Health and Human Services Institute in Sacramento, California, cultural anthropologist Jennifer James told the audience that the leaders of the future will be the ones who can “tell the story.” She observed that people want authenticity and credibility in their leaders, but the effective leaders will be those who can translate data into “stories” that resonate with the public. This is the challenge to data experts intent on compiling, analyzing, and reporting community indicators to the public. From a community perspective, the format and context in which data are reported are as important as the actual data. Using community indicators to “tell the story” and inspire citizens to action is both a science and an art. The publication of the Sacramento County Children’s Report Card in 2000, 2002, and 2004 is a case study in using both the science and art of presenting quality-of-life (QOL) indicators for public benefit. The report card project provides examples of the challenges and opportunities that are present when data professionals and community activists join forces to establish a social index for measuring progress in meeting the needs of children and families in a local community.

Background In an effort to raise public awareness of the status of the community’s children, the Sacramento County Children’s Coalition adopted a plan in 1999 to create a Children’s report card, using health and socioeconomic indicators to “tell the story” of Sacramento’s children and their families. The coalition, appointed by the Sacramento County Board of Supervisors to advise elected officials and county staff on children’s issues, also wanted to create a foundation for development of community initiatives and programs to improve the health, safety, and well-being of children in the county and envisioned the report card as a vehicle for doing so. The coalition believed that the indicators contained in the report card would both educate the public and guide action to improve the welfare of children in California’s capital region. The coalition soon garnered the support of the board of supervisors and the Sacramento County Department of Health and Human services, which provided

203 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 203–228. © 2006 Springer. Printed in The Netherlands.

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initial funding for the effort. The nonprofit CSPC, which staffs the coalition and serves as a primary community repository for regional health and social indicator data, assisted the project. CSPC’s information systems staff were instrumental in helping the coalition and its volunteers identify, refine, and describe the key report card indicators. CSPC, a member of the National Association of Planning Councils, has been providing community-based research and planning services for over 65 years in the greater Sacramento area. Since 1985, through a collaborative effort among public and private sector data sources, CSPC has compiled and maintained a comprehensive database of health and social data for public use. This database provided the foundation for development of the report card, but additional work by CSPC staff and coalition volunteers was required to research and find additional data requested by committee members during the process.

2000 Children’s Report Card: An Emphasis on Public Participation Late in 1999, the coalition formed an Ad Hoc Report Card Steering Committee to guide the process of developing and producing the report. The steering committee invited a wide variety of community representatives from public and private agencies, health care providers, childcare and educational institutions, and other community organizations to a meeting to establish goals and set the agenda for development of the report card. Over 100 community leaders attended this initial meeting and established a plan to include a broad and diverse spectrum of interests and neighborhoods in discussions about the purpose and content of the report card. Over a period of several months, the coalition sponsored a series of 17 community meetings throughout Sacramento County. Over 380 people, including 100 teenagers, attended the meetings and identified factors that needed to be included in an assessment of the status of the county’s children and youth. Six different community groups representing various coalitions of organizations with particular expertise in issues facing children and families provided additional input during the process. Gaining input from a diverse cross section of the community was a priority for the steering committee. The steering committee analyzed the community input and identified five key result areas: family economics, education, health, safety, and social and emotional well-being. A subcommittee was formed for each result area, and everyone who had participated in the community meetings was invited to join one of the subcommittees. The committees were charged with selecting indicators that could serve as measurements of children’s status relative to their specific result area. The report card subcommittees consisted of people recruited because of their background and expertise in the issue area and at-large community participants who had a particular interest in the result area. The project appealed to a wide range of community leaders who volunteered their time and expertise to the effort. For instance, the family economics subcommittee was cochaired by the president of a group of child care centers and the executive director of the local family

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service agency, and the health subcommittee was cochaired by a University of California, Davis Medical Center pediatrician and a Sacramento County health and human services agency administrator. CSPC staff provided technical expertise in indicator collection and development to each of the subcommittees. Over a 6-month period, the subcommittees identified and analyzed hundreds of indicators of children’s status from a variety of sources, some suggested by the community at large, some from recent reports on children and youth, and some that came to light during the study process. The charge to each subcommittee was to analyze these indicators and to identify eight to ten for inclusion in the report card. Consideration was given to the following criteria in selecting appropriate indicators: 1. Provides a valid measurement of child status 2. Represents consistent and comparable data over time 3. Tells the story about child status that will resonate with the public The subcommittees also recognized that one or two indicators alone could not describe the condition of children relative to each result area. Therefore, they tried to develop a complementary group of indicators that taken as a whole presented a more comprehensive picture of the condition of the county’s children, youth, and families. The subcommittees presented their recommended lists of indicators to the steering committee, which consisted of representatives of the subcommittees and other community leaders. The steering committee selected 45 indicator categories for measuring the status of children, including four categories reflecting the demographics of children in Sacramento County. Concurrently, specific data sets were identified for each indicator category.

Report Card Content Indicator categories and specific indicators and their sources for the 2000 edition of the Sacramento County Children’s Report Card are listed below. Demographics 1. 2. 3. 4.

Population by groups Population diversity Family composition Children living in poverty

Family Economics 5. 6. 7. 8. 9. 10. 11. 12.

Availability of quality child care Availability of and access to out-of-school time programs Employment Living wage Housing affordability Affordability of child care Highway congestion Ridership of public transportation

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Education 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

School readiness Student and family support services School enrollment, public and private Classroom teachers’ credential and experience Test scores Academic performance index (API) growth Children who are not in school Graduation rates Post-secondary enrollment Per-pupil expenditures

Health 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33.

Health care access Sexually transmitted infections Prenatal care Breastfeeding Perinatal substance exposure Birth rate among teens Immunization by age 2 Dental health Air quality Children suffering from asthma Tobacco use and youth

Safety 34. 35. 36. 37. 38. 39. 40. 41.

Homeless children Child deaths Child abuse and neglect Domestic violence School violence and student crime rates Juvenile felony arrest rates Driving under the influence (DUI) Runaways

Social and Emotional Well-Being 42. 43. 44. 45.

Out-of-home placement Youth substance abuse Mental health services for children Youth involved in community service and volunteerism

In some instances, reliable data were not available for selected indicators. Committee members decided to keep the indicators without the data to emphasize the importance of the particular indicator in measuring the status of children and as a prod to encourage collection of data for these important indicators in the immediate future. In all such cases, a narrative description was included explain-

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ing the relevance of the issue to child health and well-being. For instance, data on access to health care were not available, but the Report Card Ad Hoc Committee deemed the issue of such importance that it was listed in the report card minus specific data but with an explanation of its importance and how lack of health insurance has a negative impact on children. In other instances, the subcommittees had to find surrogate data to make their point. In highlighting childhood poverty, U.S. Census data provided only part of the picture and the data were 5 and 10 years old. The committee selected an additional data set, the number of children receiving free or reduced priced lunches, which reflected children living at or near the poverty level and is reported annually by the California Department of Education. The following charts present the indicators by result areas and for each indicator list the measures (data sets) and their sources. The rationale for selection of particular indicators is included. The result areas and indicators have remained constant in all three published report cards. However, measures or data sets, in some instances, have changed or been expanded. The measure column of the charts contains a composite listing of the most significant and current data used for each indicator from all three published reports. For instance in the 2000 edition, no data were available on the number of homeless children. By the 2004 edition, local school districts had begun tracking the number of homeless children enrolled in local schools. This data source is listed in the chart, although it was not available for all editions of the report card.

Sacramento County Children’s Report Card Indicators

Demographics The demographics section describes children and youth, the population that is the focus of the report, including total population, family composition, age groups, ethnicity, and languages spoken. The community committees responsible for development of the first children’s report card in 2000 decided to place children in poverty as an indicator in the demographics section, because it crossed all issue areas. It has remained in this section in subsequent editions of the children’s report card.

Indicator

Measure

Source

Rationale

Population by groups

Annual population figures by age, gender, and race/ethnicity

1

Population diversity

Population by race/ethnicity; number of English learners (based on Home Language Survey and state-approved assessment tests)

2

Numbers and characteristics of the target population provide a foundation for analysis of other indicators. Data about diversity can inform design and targeting of programs, provide equitable distribution of resources, and improve access to services. (Continued)

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Measure

Family Number of children under composition 18 years of age living in families with their own parents by married-couple and single-parent (male- or female-headed households); children living with grandparents or nonfamily members Children Number and percentage of living in children living below poverty; poverty number and percentage of publicly enrolled K-12 students participating in the free and reduced-price meals program

Source Rationale 3

Family is the core element in a child’s life and development, and family composition can affect the resources available to raise a child.

4

Children growing up in poverty are more likely to lack health care and the basics of daily living (food, clothing, adequate housing), do poorly in school, and experience long-term poverty as an adult.

Sources: 1. California Department of Finance, Demographics Research Unit. 2. California Department of Education, Educational Demographics Unit, http://data1.cde.ca.gov/dataquest/ 3. U.S. Census Bureau, American Community Survey, www.census.gov 4. U.S. Census Bureau; Children Now—California Community Data Book,www.childrennow.org; California Department of Education; U.S. Department of Health and Human Services, Poverty Guidelines, http://aspe.hhs.gov/poverty/index.shtml

Family Economics The family economics section includes data sets that describe and assess family selfsufficiency. Employment, living wage, child care, transportation, and housing affordability are key components of self-sufficiency.

Indicator

Measure

Source

Rationale

Availability of quality child care

Total number of licensed child care slots available by child age groups and change over time Comprehensive source of data was not available at time of report

1

Children need adult supervision and quality care in a safe and nurturing environment. Out-of-school time programs offer positive youth development experiences.

Availability of and access to out-of-school time programs

2

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Employment

Living wage

Housing affordability

Annual averages (by number and percentage) of people employed within selected industry categories in the Sacramento Metropolitan Statistical Area (MSA); average unemployment rate for Sacramento County Two hypothetical family budgets: family of three, mother employed at $15.40/hr with two children aged 18 months and 7 years; family of four, father and mother work full-time in maintenance and child care, respectively, with annual income $38,750, and two children aged 18 months and 7 years Average fair market rental rates by number of bedrooms

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3

Employment of adults sup-porting a household raises the economic status of families.

4

Self-sufficiency is the income level at which a family can be sustained without relying on income supports or public assistance.

5

For low-income families, the cost of housing is a major portion of the family budget. Two-thirds of mothers are in the workforce, and child care is one of the largest family expenditures with full-time toddler care costing more than 50% of fair market rent for a two-bedroom apartment in nearly every California County. Commute time affects the quantity, and sometimes the quality, of time spent with one’s family; extended commute time can increase child care costs. Public transportation provides mobility for families that do not own cars and can affect an individual’s job opportunities.

Child care affordability

Child care costs compared to family-income figures

6

Highway congestion

Travel time to work by percentage of employed persons driving to work

7

Public transportation ridership

Total annual boardings and the 8 average weekday ridership

(Continued )

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Sources: 1. California Resource and Referral Network, www.rrnetwork.org 2. Sacramento County Office of Education, After-School Programs Center 3. California Employment Development Department, Labor Market Information, www.calmis.ca.gov 4. Occupational Outlook Training Directory for Sacramento/Yolo Counties (average wages), www.work-info.com; cost of HMO plans through Kaiser Permanente or Blue Cross (health coverage); Fair Market Rents, U.S. Department of Housing and Urban Development (rental costs), www.hud.gov; California Child Care Resource and Referral Network (child care costs), www.rrnetwork.org; U.S. Department of Agriculture (food budget), www.usda.gov; Sacramento Regional Transit (bus pass), www.sacrt.com; and Sacramento Municipal Utility District rates (utility costs), www.smud.com 5. U.S. Department of Housing and Urban Development (HUD) 6. Regional Market Rate Survey of California Child Care Providers (annual child care costs); California Department of Industrial Relations, Industrial Welfare Commission (annual minimum wage); U.S. Census Bureau, American Community Survey (annual median income); U.S. HUD (annual fair market rent); California Department of Education (entry-level public school teacher salary) 7. Western Economic Research 8. Sacramento Regional Transit

Education The education section examines school readiness and the educational performance of children as well as educational supports provided by the school system.

Indicator

Measure

School readiness

Measures of school readiness 1 were not available at the time of the report but are currently being developed by a community coalition led by the Sacramento County First 5 Commission, which funds services for children 0 to 5 years of age Counselor/student ratio and 2 nurse/student Ratio

Student and family support services

Source Rationale Current research indicates that the emotional, physical, and intellectual environment that a child is exposed to in the early years of life has a profound impact on brain development. Academic success is not a product of instruction alone and is enhanced by a system of learning support services related to intellectual, physical, and emotional development.

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School enrollment, public and private Classroom teachers’ credential and experience

Number of students enrolled in public and private schools

3

Percentage of teachers in public schools by credential type and teachers that are first-year and second-year teachers

4

Test scores

Math and reading scores by grade for Sacramento County and California

5

Academic performance index (API) growth

API is a numeric index (or score) that reflects a school’s or school district’s performance on statewide student assessments.

6

Children who are not in school

Currently there are no centralized and consistent data being collected

None

Graduation rates

Percentage of students graduating from public schools who entered the ninth grade 4 years earlier

7

Postsecondary enrollment

Number of 12th grade graduates completing courses required for admission to the University of California and California State University systems

8

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Schools prepare students for full civic participation, employment, and higher education. Professionally trained teachers are generally better equipped to help students succeed; lowperforming schools have disproportionate numbers of teachers not fully credentialed or qualified to teach mathematics, science, and special education. Standardized testing helps educators, parents, and employers understand the progress students are making in meeting established standards of learning. Individual schools are measured by how much their students improve overall from year to year and how much ethnic and socioeconomically disadvantaged groups improve, key data for evaluating educational equity and effectiveness. Children not in school are deprived of the education they need to lead successful and fulfilled lives. High school graduates are more likely to earn a living wage and to increase their employability through technical training or college. The job market is increasingly competitive, and the more educated a person is, the more opportunities there are for finding satisfying, productive employment. (Continued )

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Indicator

Measure

Source Rationale

Per-pupil expenditures

Cost per student is the direct cost of education services divided by student average daily attendance

9

The current cost of education is a method to compare effectiveness of educational dollars spent and can be compared over time and among schools, districts, and counties.

Sources: 1. Sacramento County First 5 Commission, http://sackids.saccounty.net/schoolreadiness.html 2., 3., 4., 5., 6., 7. California Department of Education, http://data1.cde.ca.gov/ dataquest/, http://api.cde.ca.gov 8. California Department of Education; California Postsecondary Education Commission 9. California Department of Education, School Fiscal Services Division

Health The health section includes key measures of physical wellness, spanning all age groups from prenatal to youth.

Indicator

Measure

Source Rationale

Health care access

Medi-Cal enrollment, children without health insurance coverage

1

Sexually transmitted infections (STIs)

Rates of gonorrhea and chlamydia by age

2

Prenatal care

Percentage of live births for which prenatal care was received during the first trimester of pregnancy

3

Children without preventive and ongoing health care are more likely to suffer chronic health conditions and are less likely to succeed in school. STIs can have serious and long-term, even permanent, consequences, including infertility, chronic pelvic pain, poor pregnancy outcomes, and death. STI’s and vaginal infections can result in adverse pregnancy outcomes. Mothers who obtain prenatal care generally have better birth outcomes.

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Breastfeeding

Perinatal substance exposure

Birth rates among teens Immunization by age two

Dental health

Air quality

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Number and percentage 4 Scientific research indicates of mothers by that breastfeeding fosters race/ethnicity who initiate greater health for the child. exclusive breastfeeding Mothers who breastfeed show and combination a lower incidence of abusing breastfeeding/formula at or abandoning their children. the time of discharge from the hospital No local data are None The use of alcohol, tobacco, and available. Hospitals other drugs during pregnancy is have discretion in one of the leading preventable reporting tochild factors contributing to infant protective services mortality. Babies born exposed mothers with positive to drugs before births have a screens for drugs. higher risk of birth defects, brain and heart damage, and behavioral problems in childhood. Number and percentage 5 Numerous risk factors link of teen births by age early childbearing with poor and ethnicity health outcomes for both teen mother and child. Percentage of children 6 Many diseases are preventable by fully immunized by by vaccination, and children second birthday who are not immunized are at risk for contracting those diseases, many of which are serious and can be fatal. Because comprehensive 7 Oral disease is the most data are not available prevalent untreated disease to measure the extent nationwide. of dental disease among children, data from a smaller study of children enrolled in healthy start collaborative programs was used: Percentage of enrolled children with dental cavities or in need of immediate dental care (visual exam of 12,000 children) Number of days air quality 8 Chronic and acute exposures exceeded the 1-hour state to air pollution at levels above ozone standard; number state standards can cause or of days air quality exacerbate lung conditions like exceeded 1-hour and asthma, bronchitis, and 8-hour federal standards emphysema. (Continued)

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Measure

Source

Children suffering from asthma

Percentage of children diagnosed with asthma

9

Tobacco use and youth

Percentage of students 10 by grade level (7, 9, 11) who have smoked at least one cigarette in the last 30 days

Rationale Asthma is the leading serious chronic illness among children and the one that causes them to miss the most school. Cigarette smoking is a major cause of emphysema, chronic bronchitis, lung cancer, and coronary heart disease.

Sources: 1. California Department of Health Services; California Health Interview Survey 2. California Department of Health Services, Sexually Transmitted Disease Control Branch, www.dhs.ca.gov/ps/dede/STD/stdindex.htm; Sacramento County Department of Health and Human Services 3. California Department of Health Services, http://www.dhs.ca.gov/hisp/chs/ OHIR/vssdata/2002data/2002NcountyEX.htm 4. California Department of Health Services, Epidemiology and Evaluation. 5. Section, Maternal and Child Health Branch; additional information, www.fns.usda.gov.wie/ 6. California Department of Health Services; Rand California 7. California Department of Health Services, Immunization Branch, www.shots4tots.org, www.immunizationinfo.org 8. Sacramento District Dental Society and Sacramento County Healthy Start Collaborative, www.sdds.org 9. Sacramento Metropolitan Air Quality Management District, www.sparetheair.org 10. University of California, Los Angeles, Center for Health Policy Research, California Health Interview Survey, www.healthpolicy.ucla.edu, www.chis.ucla.edu 11. California Healthy Kids Survey, WestEd, www.wested.org/hks

Safety The safety section contains vulnerability indicators including crime, violence, neglect, and mortality.

Indicator

Measure

Source Rationale

Homeless children

Number of children identified and children estimated as homeless by individual school districts

1

Homelessness severely affects the health and well-being of all family members, and children often experience poor health, suffer from anxiety, depression, and

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exhibit behavioral problems that can lower educational achievement. Child deaths

Number of child deaths by natural causes and injuryrelated causes

2

Child death is an indicator of the effectiveness of public health and accident prevention programs and laws.

Child abuse and neglect

Number of reports of and responses to suspected child abuse cases, number of children in out-of-home placement, and types of substantiated maltreatment

3

Child abuse and neglect cross socioeconomic boundaries and have a profound effect on the safety and well-being of children.

Domestic violence

Number of domestic 4 violence–related calls received by law enforcement agencies

In homes where domestic violence occurs, children are physically abused and neglected at a rate 15 times higher than the national average for child abuse and neglect.

School violence and student crime rates

Number of criminal incidences on school campuses per 1000 students by type of crime

5

A safe school environment promotes learning and emotional well-being in students.

Juvenile felony arrest rates

Number of arrests per 1000 juveniles (aged 10–17)

6

Youth arrested for a felony, a crime punishable by death or imprisonment in a state prison if committed by an adult, are exhibiting selfdestructive and antisocial behavior and often continue a pattern of criminal behavior into adulthood.

Driving under the influence (DUI)

Number of felony and misdemeanor juvenile DUI arrests

7

Runaways

Number of juvenile missing 8 persons (youth under the age of 18 who are away from home at least one night without the permission of parents or guardians) reports filed in Sacramento County

Reckless and unsafe driving by youth under the influence of drugs or alcohol can cause injury and death to youth and others in the community. Runaway youth are at increased risk of sexual abuse and exploitation, drug and alcohol abuse, and becoming victims of violence.

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Sources: 1. Sacramento County Office of Education, Project TEACH, http://fmpro.scoe.net /programs 2. Sacramento County Child Death Review Team 3. Sacramento County Department of Health and Human Services, Child Protective Services, Quarterly Statistical Reports; additional information, http://cssr.berkeley.edu/cwscmsreports/ 4. California Department of Justice, Statistics Division, http://caag.state.ca.us/cjsc/ 5. California Department of Education, Safe Schools and Violence Prevention Office, California Safe Schools Assessment, http://www.cde.ca.gov /re/pn/fd/cssa9899-pdf.asp 6. California Department of Justice, Criminal Justice Statistics Center 7. California Department of Justice, Criminal Justice Statistics Center 8. Sacramento City Police Department; Sacramento County Sheriff’s Department

Social and Emotional well-being The social and emotional well-being section presents indicators from which information about children’s emotional health and stability may be derived.

Indicator Out-of-home placement

Measure

Source Rationale

Number of children 1 in child welfare– supervisedfoster care by placement type and age

Children require safe and stable families to thrive.

Youth substance Alcohol and drug usage abuse by 11th grade youth

2

Alcohol is a contributing factor in the three leading causes of death among 12–18-year-olds (accidents, homicide, and suicide).

Mental health services for children

3

Access to mental health services ensures that children have the treatment they need for positive emotional growth. Studies report the positive relationship between service learning and development of personal and social responsibility and leadership skills in youth.

Number of youth receiving publicly funded mental health services by age group Youth involved No comprehensive in community data available service and volunteerism

None

Sources: 1. Center for Social Services Research, University of California Berkeley, School of Social Welfare, http://cssr.berkeley.edu; Sacramento County Department of Health and Human Services, Research and Evaluation Division.

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2. California Healthy Kids Survey, WestEd, www.wested.org/hks 3. Sacramento County Department of Health and Human Services, Research and Evaluation Division.

Report Card Format and Presentation The report card was meant to be both an educational vehicle and a call to action. Because its proponents wanted not only to increase public understanding of issues affecting children and youth but also to set the stage for measuring progress in improving child health and welfare in Sacramento, they recognized quickly that data and numbers alone could not tell the whole story. They needed to put the indicators in context in order to capture the attention of the public and spark civic action. To put the indicators in context, the report card featured narrative about the data selected as a measurement for the selected indicator in addition to a chart or graphic displaying the data. The narrative included three sections: 1. How was this (indicator) measured? 2. Why is this (indicator) important? 3. How are we doing? For example in the education section, the indicator, classroom teacher’s credential and experience, is described through a pie chart depicting data from the California Department of Education comparing the percentage of credentialed and noncredentialed classroom teachers in Sacramento County to the percentage in California as a whole. Two sections explained the indicator and its relevance to students— How was this measured? Data were gathered on the numbers of teachers who are fully credentialed and the average number of years of experience in the classroom. Currently employed teachers who hold interim or emergency credentials, or for whom the requirement was waived, were considered not to be fully credentialed. Why is this important? There is concern on the part of experienced educators that inexperience and the absence of credential-level training of teachers have a negative impact on the overall quality of education. The third section of the indicator description, “How are we doing?” gave the context in which the indicator is played out in the community. In the case of credentialed teachers, the narrative explained that Sacramento’s rate of credentialed teachers has remained relatively the same in recent years but that new statemandated policies requiring lower class sizes in primary grades will increase the demand for more credentialed teachers who are currently in short supply. The narrative also introduced related data that could not be included in the tables or charts, such as the drop in years of experience for the average teacher and

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reports that schools in low-income areas tend to have a higher proportion of noncredentialed teachers.

Public Response The report card was published in September 2000. It was officially presented to the public at a press conference, which resulted in widespread coverage by both print and electronic media. It received additional public exposure through a workshop with the Sacramento County Board of Supervisors and other key county staff, presentations to local foundation officials, and a meeting with the editorial board of The Sacramento Bee, which resulted in an editorial promoting community investment in the welfare of Sacramento’s children. Copies of the report card also were distributed to city councils, school boards, community organizations, neighborhood associations, and children’s advocacy groups.

Children’s Summit: Results-Based Thinking and Action The report card development leaders made two strategic decisions that created interest in the report and contributed to its impact on local public policy and program planning. One was the decision to call the indicator categories “result areas” to help shape the public reaction to the report card. They wanted the report card to inspire action to achieve better “results” for children rather than become just another report on the status of children that is forgotten within months of publication. The second strategic decision was to schedule a community meeting featuring the report card. Next to publishing the children’s report card itself, the most significant aspect of the entire process was the 2-day children’s summit that followed the publication of the report card. With a focus on the result areas, the summit challenged the community to think about new ways of achieving positive outcomes for children. Results-based thinking and action depends on a foundation of credible indicators from which to measure progress and measure the effectiveness of strategies and programs aimed at improving the QOL in communities, and specifically in Sacramento’s case, the well-being of children. The report card steering committee was astute in understanding that it was not enough to publish a list of indicators and expect community action. They understood that indicators not only needed to “tell the story” and resonate with the public but also had to create an environment in which the community could use the indicators to take effective action and monitor the results of their actions over time through the analysis and continuous updating of the indicators.

Turning the Curve Prior to publication of the report card, Mark Friedman of the Fiscal Studies Policy Institute and an advocate for results-based thinking had conducted a series of training seminars for children’s services organizations in the Sacramento area to

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help them understand how to use data to evaluate and develop strategies to “turn the curve” on trends affecting children and their families. Whether it was turning the curve upward on the number of students graduating from high school or turning the curve downward on teen pregnancy rates, children’s advocates learned how to use the data to develop real outcomes, changes in behavior and conditions that could improve the status of children in Sacramento. Friedman also emphasized the need to “tell the story behind the data” to capture the hearts and minds of people and generate a climate for change. His push for results-based accountability required use of indicators to measure results and progress toward long-term outcomes rather than the traditional evaluation based on number of clients helped or units of service completed. The movement to change from measuring outputs, units of service, to outcomes, changes in individual, group, and community behavior and attitudes, depended on the establishment of a credible set of indicators from which to measure progress and evaluate results. Friedman was invited to lead off the summit with a training session focused on results-based accountability. He presented a ten-step community action plan format for addressing community issues using indicators. The first five steps, (1) adopt a vision, (2) establish broad-based community involvement, (3) reach consensus on outcomes/indicators, (4) collect data, and (5) publish the report, had already been accomplished by the assembled group. Steps six and seven, (6) analyze implications and (7) develop agenda for action, constituted the agenda for the following day of the summit. The remaining steps, (8) take action, (9) identify and support what works, and (10) use data to monitor progress and improve service, would be carried out as a result of the summit (Figure 1). According to the summit report, “Children’s Summit, Forming Action Plans to Turn the Curve,” Friedman advised the following: To guide strategy, keep asking what impact our efforts are having on the lives of children. To achieve results, focus on creating the movement (turning the curve) on three or four indicators, not 45.

Use data to monitor progress and improve service Identify and support what works

1 Vision 2

10

Establish broad-based community involvement Consensus on outcomes/indicators

3 9

Take action

4

8

Develop agenda for action

7

5

Collect data

Publish the report

6 Analyze implications

Fig. 1. Community action plan steps.

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Look for what works and do more of it. Everyone wants a silver-bullet, singleapproach solution. But what most often works is a mix of separate actions, including some low- or no-cost solutions. The two ingredients needed to bring partners together and turn the curve are passion and discipline. People accomplish the most when they coalesce around the issues and indicators that they feel passionate about and then bring discipline to their approach in planning actions together. On day two of the summit, over 175 participants considered Friedman’s advice and pared the indicators for priority action down to ten, two for each result area. They were: Family economics—availability of child care and availability and access to nonschool-hour programs Education—school readiness and pupil support services Health—sexually transmitted diseases and access to health care Safety—child deaths and homeless children Social and emotional well-being—out-of-home placement and youth substance abuse Action teams were formed to identify and implement strategies to “turn the curve” for the priority indicators selected by the group. An organization was identified to serve as the results area “champion” and keep the action team on track. After publication of each of the two subsequent editions of the report card, the action teams have reconvened at subsequent children’s summits to assess progress in “turning the curve” and adjust community strategies as needed.

The ABC’s of the Action Plan Process in Sacramento Pre-summit No.

Step

1

Adopt a vision

Action ●

●

2

Establish broadbased community involvement

●

●

Children’s coalition adopted a purpose statement: “committed to enriching the lives of children in our community by keeping them safe, healthy, nurtured, educated, and happy.” The coalition agreed on strategy to engage the public in dialogue about children’s welfare—the development of a “report card” on child health and well-being in Sacramento County, and created a report card steering committee to plan and carry out the work. The coalition and the committee obtained input and endorsement of key elected officials and other decisionmakers and kept them informed during the process. The report card steering committee involved over 380 individuals, including youth, in the process.

USING COMMUNITY INDICATORS TO IMPROVE THE QUALITY

3

4

Reach consensus on outcomes/indicators Collect data

●

●

●

5

Publish report

●

●

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Individuals, organizations, and coalitions participated in an extensive community review and input process climaxing in the selection five key “result areas.” CSPC, a community-based agency experienced in QOL indicators work, provided expertise and support to the project. CSPC, community volunteers. and the report card steering committee analyzed data for relevancy and ability to “tell the story” in a way that would resonate with the public. The children’s coalition published first children’s report card containing data, charts, pictures, and narratives to “tell the story” of status of Sacramento’s children. The coalition distributed report card widely to decisionmakers, media, community-based agencies, and children’s advocates.

Summit No.

Step

Action

6

Analyze implications

●

●

7

Develop agenda for action

●

●

●

●

Over 175 community activists and decision-makers engaged in in extensive discussion and analysis of data and the report at a 2-day “summit.” Summit attendees were trained in how to use the data and the report to effect change and participated in a process to identify priority issues and indicators. Summit participants selected ten indicators, two for each result area, for priority action. Individuals and agencies volunteered for action teams to plan and execute action plans to “turn the curve” on selected indicators. Action team “champions” were identified to drive the implementation process. Action plans were developed for each result area with desired outcomes established for each indicator.

Post-summit No. Step

Action

8

●

Take action

●

Action teams developed work plans and set time lines and due dates for check-in on progress and to evaluate activities and results. Sacramento County Children’s Coalition provided a framework for monitoring progress and communicating results to those involved. (Continued )

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No. Step

Action

9

●

Identify and support what works

●

10

Use data to monitor progress and improve service

●

●

●

●

Action teams have reported back to the community at the summits following the publication of the 2002 and 2004 report cards. The results of each summit, including progress made and new goals established, have been published and distributed to the community. At each subsequent summit, data from the most current report card are analyzed and activities are reviewed for effectiveness. Sacramento County Department of Health and Human Services has distributed the report card to all departments and uses the information to identify policies, programs, and practices needing improvement. Sacramento County children’s coalition reviews quarterly reports from each action team. Children’s report card has been updated every 18–24 months since 2000 (the next edition will be published in 2006).

An Action Team Works for Results Result Area—Health, Indicator: Access to Health Care Turning the Curve: Increase the Number of Children with Health Care Insurance (Measurement) At the summit following publication of the first edition of the report card, the health action team identified a desired result, “increase the percentage of families accessing quality health and dental care.” They selected three of the best ideas generated at the summit for “turning the curve” as objectives for future action: (1) provide enrollment services onsite at schools; (2) simplify enrollment procedures; and (3) teach people how to navigate the system and educate them about preventive health care. The publication of the children’s report card and the action team’s adopted goal provided a public boost to the nascent effort of the City of Sacramento Mayor’s Commission on Children’s Health to get more uninsured children health care coverage by enrolling them in the California Healthy Families Program. Working with the mayor’s commission and others, including Sacramento’s four hospital systems, county health department, and foundations, the action team set up subcommittees to achieve its goals. Some activities, such as simplifying enrollment procedures required work with state officials and other coalitions throughout California. Soon the mayor’s commission became the Regional Children’s Health Project, which expanded the initiative to other counties in the greater Sacramento area.

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The action team and regional health project continued their efforts to increase enrollment with the objectives of maximizing funding, focusing on education and outreach, and working toward a one-stop system for service. Recruiting new partners to the effort was also a priority. Just as the action team, children’s coalition and regional children’s health project were about to announce the formation of Cover the Kids by 2006, a new initiative with the goal of 100% health coverage for all children by 2006, California health officials proposed capping the number of children who could be served in the healthy families program as a cost-cutting measure for the state. Cover the Kids seized the initiative and set a new goal of enrolling 4000 children in the program before adoption of the new state budget. Although the California Legislature never enacted the caps, the Cover the Kids campaign was successful in enrolling over 4000 new children. Combining the work of Cover the Kids and the regional children’s health project, over 15,000 children have been enrolled in health care since 2000. The Cover the Kids by 2006 initiative received a 3-year, $10-million commitment from the Sacramento County First 5 Commission, a body set up to distribute cigarette surtax funds to programs supporting children 0–5 years of age. The commission also funds the children’s report card and children’s summit, and the commission uses data from the report card in its planning and deliberations regarding priority issues for funding and support. The First 5 funding is being used to underwrite the cost of insurance coverage for uninsured children who do not qualify for public programs. With this type of commitment, other foundations, businesses, and United Way have joined in with contributions to increase health care access for children. As the children’s coalition’s report card steering committee gears up to research and publish the 2006 edition, health care access remains a critical issue. Using indicators of health care access and other health-related indicators from the 2006 report card, Sacramento public officials and child advocates will be able to evaluate the effectiveness of their efforts since the first report card was published. The health care action team will use the results to assess progress toward their stated objectives and determine the kinds of changes that need to be made to continue to turn the curve to improve children’s health.

The Children’s Report Card: An Evolutionary Process for Data Experts and Community Alike For the second edition of the Sacramento County children’s report card in 2002, the process was more structured. The result area committees only met three times and the meetings had specific agendas. The committees chose two indicators in each result area for more in-depth analysis. Each of the selected indicators were presented on two full pages, including narrative and numerous charts and graphs. The expanded coverage was due in part to feedback from people using the first edition who reported that one page of narrative and charts was not enough to tell the whole story of the indicator.

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The 2002 committees determined that some of the data used to measure the indicator in the 2000 report card was not useful. For example, highway congestion in 2000 was measured by two data sets from the California Department of Transportation, daily vehicle hours of delay and congested directional miles. The 2002 committee felt this was confusing and too difficult to understand so in 2002, highway congestion was measured simply by travel time to work, which committee members believed was easier to understand. Unfortunately in 2004 fewer dollars were available for research and publication. This factor affected the format, and to some degree, the content of the third edition. Due to the reduced production budget, data staff recommended an update of the data, printing a simple report with only the charts and no narrative that explained the meaning of the data or captured what was happening in the community. This proposal was rejected by the community committee, however, which wanted a report card like the more expansive 2002 edition. A compromise was reached. The priority indicators got full-page coverage and the others got half a page. Data were updated for all 45 indicators, and narrative was added to explain the data and its community context. The challenge for data staff and committee members was that some indicators that had two full pages for charts and narrative in 2002 were reduced to a mere half a page in 2004. Child abuse and neglect, for example, had two full pages with five charts and extensive narrative in 2002 but was reduced to one chart and two paragraphs of narrative in 2004.

Challenges The major challenge with the first report card was setting limits on the number of indicators and related data sets without stifling the ideas and commitment of the volunteers. With so many people involved in the process, staff had to deal with a seemingly insatiable desire for more and more data. Staff continually reminded volunteers that the desired outcome was a useful indicator report, not a data encyclopedia. A particular challenge for data staff was the direction from the volunteer leaders developing the report card that the document should not be “data driven” but rather issue-driven based on input and discussion among the experts, professionals, and community members participating in the process. However, experience showed that the volunteers could not make decisions about which indicators to highlight and related data sets for measurement without knowing all the options available. Committee volunteers had little idea of what data were available or even what the data really measured. In some instances, committee members were convinced that data existed for a specific topic when they did not. Staff spent a great deal of time educating committee volunteers about indicators, their value and limitations, and the most effective means of communicating the meaning of the indicators. Helping the committees evaluate the vast amount of data that had been compiled for each issue area was indeed a daunting task.

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Another challenge was trying to describe a particular indicator influenced by many economic and social conditions, like living wages, with one or two data sets. To address this dilemma, report card staff used a variety of data sources to develop a living wage budget for a single working mother and two children. The budget told the story of the working poor much more vividly than charts or graphs could. The budget is one of the most quoted and most used sections of the report card. Since the first edition of the report card in 2000, the indicators have remained the same. Unfortunately, some data sets selected to measure results have been changed at the data source, making comparison over time difficult. For instance, school testing data has changed as a result of policy changes at the California Department of Education and the performance of local schools can be compared to the state and other jurisdictions at a particular point in time but progress over time cannot be captured. A particularly frustrating challenge for the committee was identifying key indicators of children’s health and welfare and finding no consistent, credible data to support the indicator. In the first report card, staff could find no reliable data for some indicators of great importance to the community members in monitoring child welfare, such as availability and access to non-school-hour programs, access to health care, childhood asthma, school readiness, and homeless children. The report card steering committee decided to include these indicators without data in order to highlight the importance of the issue and to encourage data sources to begin collecting data for these community priorities. This strategy has resulted in some positive results, for instance, data on homeless children are now being collected and tracked by school districts and the California Health Interview Survey is now providing better data for children suffering from asthma. The action teams have also experienced challenges. Team “champions” have changed over the years, leaving some result areas with inconsistent leadership. These areas have tended to be less effective in driving activities to “turn the curve” on their particular indicators than other areas with steady leadership. The breadth and scope of the report card also poses problems in implementation. Even paring down the indicators to ten in five result areas presents a coordination challenge. While all the issues continue to be addressed and reported on at some level, broad-based, concerted community action has been concentrated annually on one or two high-priority indicators identified by the coalition and community partners, such as children’s access to health care insurance and support for emancipated foster youth.

Results The children’s report card has proved to be a valuable tool for many sectors of the community concerned with the well-being of children. Public agencies use it to track the effectiveness of their policies and services for children; nonprofit agencies use it for program planning and obtaining grants for priority issues identified in the report card; and children’s advocates use it to urge program and policy changes and create community initiatives to improve the lives of children.

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Jim Hunt, the director of Sacramento County’s health and human services department, has long been a supporter of the children’s report card and distributes the report card to staff within his department. According to Hunt, indicators in the report card “bring focus to an issue” and put public and private agencies on notice when indicators reveal poor outcomes for children. Hunt says that “what gets measured gets attention,” and he sees the report card indicators not only as a barometer of children’s status but also as a tool for county government to measure its effectiveness in making the lives of children better. The director of a large child care support agency who is also a member of the children’s coalition reported that her agency had received a $4.5 million grant which she attributed in large part to the agency’s ability to cite data from the report card relating to children’s needs. She emphasized that the true value of the report card in this particular instance was the fact that various indicators could be cited with supporting evidence of their interrelatedness. For instance, not only could the agency use data on the lack of available child care but also could couple these data with data on housing affordability and the living wage budget, thereby increasing the impact of each data set and telling the child care story in a more comprehensive way. The director thought the real value of the report card was its “accessibility” to the general public. She added that the report card has had impact because it presents indicators in a community context, displays data in an easy-to-understand format, and uses examples, like the living wage budget, that resonate with the public. A member of the county board of supervisors credited the 2002 report card and the following children’s summit for the development of a key initiative to increase children’s access to health care, Cover the Kids by 2006. The first report card identified access to health care as a key indicator even though reliable data on the extent of the problem was not available. By the second edition in 2002, some data had been identified and reported, spurring community action. The Cover the Kids by 2006 campaign continues to cite indicators from the children’s report card as an impetus for the initiative and uses these data to determine the progress the initiative is making in “turning the curve” and meeting its goal of 100% coverage.

For Sacramento’s Children, the Science and Art of Indicators The Sacramento County children’s report card has been published three times since 2000. The next edition will be completed in 2006. The report card project is part of a larger strategy to educate the public about children’s issues and engage more people in action to improve the status of the county’s children, youth, and families. Several factors have contributed to the ongoing effectiveness of the report card project: broad community participation, skilled data staff who approach the project from a community-development perspective, and a strategic plan for coalescing community action on issues raised by the report card. A central tenet of the project has been the inclusion of many diverse voices in the development and production of the report card, a process that has created a great sense of ownership

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227

among participants with the attendant commitment to work collaboratively to “turn the curve” on the issues identified by the QOL indicators. Another factor in the success of the project is the expertise of the data staff and their ability to take input from the committees and conscientiously strive to find the best data sets to measure the selected indicators, knowing that the ultimate goal is to find indicators that tell a story and resonate with the public. The children’s summits following publication of each edition of the report card have focused attention on desired community outcomes for the community’s children, but, more importantly, these meetings have spurred the community to action using the indicators as a guide for change. The Sacramento community like many others is awash in information and data about children, which are too often quickly forgotten. The children’s report card gives life and context to the data—the QOL indicators—by presenting the data in a way that is easily accessible and understandable to the general public. The report card represents the marriage of the science and art of indicators. The report card “tells the story” of children in a powerful way that influences and directs change.

NANCY M. FINDEISEN, President and Chief Executive Officer, Community Services Planning Council Inc. [email protected]

Living in a Post-Apartheid City: A Baseline Survey of Quality of Life in Buffalo City ROBIN RICHARDS1 AND ELLEN KAMMAN2 1

Researcher, Community Agency for Social Enquiry (CASE), Johannesburg Researcher, Fort Hare Institute of Social and Economic Research (FHISER), University of Fort Hare, East London

2

Introduction Community quality of life (QOL) is an elusive concept to define. Its meaning depends on where you live, where you work (if you work), and who you are (for example, your gender, class, and culture). This view of QOL is supported by other researchers like Proshansky and Fabian (1986). Like other cities and towns in South Africa, the legacy of apartheid not only left deep physical and psychological scars but also resulted in huge data gaps in Buffalo City for proper city planning. The 2001 QOL collected a spectrum of social data for Buffalo City, including community indicators of development at the level of smaller towns and suburbs. The survey had a number of important specific objectives, the main ones being: filling large socioeconomic data gaps to facilitate the completion of the municipality’s first strategic plan—in South African city planning parlance, these are also referred to as Integrated Development Plans (IDPs); facilitating economic development of the city; quantifying development needs and prioritizing development initiatives; and providing baseline data for the monitoring of service delivery backlogs (Buffalo City Municipality Integrated Development Plan, 2002). The survey also set up a vehicle through which Buffalo City residents were able to participate in city planning by identifying their own development needs.

The Significance of the Survey The Buffalo City 2001 QOL survey has for the first time provided up-to-date socioeconomic indicators on the material living conditions of all its residents. This study has enabled city planners to quantify and spatially locate backlogs in social and infrastructural services and to identify which services are perceived by residents to be most important to them. City planners and policy researchers can therefore correlate actual living conditions of residents with the way they perceive these conditions. The 2001 QOL survey findings provide baseline data that will enable planners and policymakers to monitor the impact of future development initiatives to ensure that development programs meet the needs of citizens they are designed for.

229 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 229–248. © 2006 Springer. Printed in The Netherlands.

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Findings from this survey have been used by Buffalo City in the development of its 2003 IDP.

The City Under Study Buffalo City is one of the nine largest cities1 in South Africa. It is located on the southeast coast of South Africa and is the home of South Africa’s only commercial river port, situated on the banks of the Buffalo River. Buffalo City comprises a grouping of towns2, each of which are surrounded by rural hinterlands. Figure 1 shows a map of Buffalo City with the main study areas reported on in this chapter. The city covers roughly 2500 square kilometers. It is made up of 45 electoral wards and according to the Buffalo City Integrated Development Plan 2002), it has an estimated total population of around 880,000 people: 85% of residents are African, 8% white, 6% colored, and 1% Asian (Stats SA, from Census 2001). The city is well placed for international trade, connecting with the global markets of Asia, America, and Europe. The port also serves as a linkage between other parts of Africa and their overseas markets. The electrical, food, and motor industry are key components of the East London economy. The motor industry, underpinned by Daimler Chrysler, dominates Buffalo City’s economic output. Buffalo City’s main town, East London, is the marketing and distributing center for the eastern part of the Eastern Cape Province and is a major wood-shipping port. Important industries include food processing (Nestle), automobile assembly (Daimler Chrysler), and the manufacture of furniture, footwear, pharmaceuticals, and textiles. The first known specimen of a coelacanth, a fish thought to have been extinct for several million years, was caught in 1938 near East London and is housed in the city museum. King Williams Town, another major town in Buffalo City, is situated on the banks of the upper reaches of the Buffalo River. It has a significant industrial and commercial base that includes textile manufacturing, leather tanning, footwear, and clothing, as well as the production of soap, candles, and cartons.

Objectives Although progress has been made with respect to the delivery of basic services to the poor in Buffalo City, efforts at improving their material living conditions are at the beginning stage. The main features of the apartheid city3 therefore remain in place with little evidence of residential mixing amongst different ethnic groups. The urban poor are overwhelmingly African and continue to live on the periphery of the city, furthest from work opportunities that the city offers. Findings from this survey offer valuable contemporary insights into the social and economic structure of the postapartheid city in South Africa. The chapter focuses on four localities in Buffalo City (case study areas) covered by the QOL survey. The case studies highlight what some commentators refer to as ‘deracialized apartheid’4 to describe the continuing racially fragmented nature of a

Buffalo City quality-of-life survey map

10 Macleantown

7

16

9

11 KWT Bisho

Newlands

Belin

13

Kwelera

42

34 15

44

Legend

41 393745 36 40 38 B 33 30 35 43Mdantsane

Needs Camp

Towns Roads National roads Trunk roads Case studies

3

18

17

14

20

19

12

31 24

21

A

32 29 B 2726 252823 D 22

4

A

A

5 6 East London

2

Case A

Beacon Bay Gonubie Vincent

Winterstrand

Case B

Kidd's Beach

Mdantsane

N

Case C

Gunubie

LIVING IN A POST-APARTHEID CITY

Dimbaza 8

Cuncan Village Case D

1 Kayser's Beach

Buffalo flats Parkridge Parkside Pefferville No Wards

W

E S

Hamburg

231

Fig. 1. Map of study area.

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ROBIN RICHARDS AND ELLEN KAMMAN

contemporary South African city. The case study areas show that there are great differences in wealth, living conditions, and perceptions of QOL amongst residential groupings in different localities in Buffalo City. These differences are textured by an overlay of race and class.

The Buffalo City Survey Sample Methodology Key Definitions Households were defined as all persons eating from the same kitchen and who received their post from the same address. Where more than one household was located on a plot, a sampling grid was used to randomly select the household. Households were therefore allocated a number before the selection process. Respondents (interviewees above 18 years of age) were selected randomly from households using a sampling grid.

The Sampling Strategy A proportional stratified sampling method was applied in the survey. Households were the primary sampling unit. Financial resources available determined the number of interviews that were conducted in the survey. In Buffalo City, it was decided that a sampling error of 0.02 was acceptable, and this sampling error requires a sample size of 2477 interviewees, which was affordable. This was likely to be a one-off large baseline survey, with any possible future work being small scale and spatially limited.

Method for Determining Sample Size The following formula was used to calculate sample size (Israel, 1992): n=

N , 1 + N(e)2

where n = sample size, N = population size (total number of households), e = level of precision, with assumed confidence level of 95% and population variability of 0.5. The local government elections before the survey had established 45 newly demarcated wards. The 2477 interviewees were distributed proportionally, according to the percentage of total households per ward. The sample was then stratified proportionally by housing type and population group using Census 1996 data. All 45 wards within Buffalo City were sampled. In wards where minority ethnic groups were required to be sampled but were not in ethnic dominance, the proportional sampling rule was not applied. The Buffalo City QOL sample design was based on the Census 1996 distributions of ethnic group and housing type. This sampling framework has provided Buffalo City with statistically reliable baseline data that can inform key municipal issues.

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The Survey Procedure The Buffalo City questionnaire was based on Durban’s QOL survey instrument, and was adapted for use in Buffalo City by the Institute of Social and Economic Research (ISER) with the assistance of specialist inputs from Statistics Sweden.5 Buffalo City service unit managers in the following departments were consulted: development planning; waste; electricity; and cleansing. Officials in these departments gave inputs into the questionnaire structure and design to ensure that the survey instrument covered issues relevant to Buffalo City and to adapt it to the local environment. The University of Michigan’s 2001 Detroit Area Study questionnaire provided practical examples for the design of some of the survey questions relating to subjective well-being. Interviews took place over a period of four weeks from August 18 to September 14, 2001. Interviews took between 35 minutes and an hour to complete.

A Description of the Main Case Study Areas This paper explores residents’ material living conditions and perceptions of QOL in specific case study areas. These areas were chosen because they comprise specific sectors of the Buffalo City population in respect of general ethnic and class divisions. In the text, case studies will be referred to as Cases A, B, C, and D. ●

● ● ●

Case A = Beacon Bay, Gonubie, and Vincent (previously white suburbs under the Group Areas Act) Case B = Mdantsane (formal African township) Case C = Duncan Village (informal African settlement) Case D = Parkside, Parkridge, Pefferville, and Buffalo Flats (previously colored suburbs under the Group Areas Act)

Case A: Beacon Bay, Gonubie, and Vincent Study area A includes: Beacon Bay, Gonubie, and Vincent. These areas were traditionally white middle-class suburbs in the old East London municipality. Table 1 shows that these areas are still predominantly white. Beacon Bay and Gonubie are on the eastern side of central East London, the latter is situated some 20 km from the city’s center. Both areas lie on the coastal strip. Vincent lies to the northeast of the city center. It is one of the older East London suburbs and was part of the independent municipality of Cambridge in Table 1. Population group (%).

Case A Case B Case C Case D

African

Asian

Colored

White

12.7 100.0 99.0 13.2

0.0 0.0 0.0 0.6

0.0 0.0 1.0 86.2

87.3 0.0 0.0 0.0

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1882 but later, in the 1940s, was absorbed into the city of East London (Watts and Agar-Hamilton, 1970).

Case B: Mdantsane This is the largest formal township in Buffalo City. Mdantsane (formerly known as Umdanzani) is situated some 12 km from East London. The township that lies inland in a northwesterly direction from the central city (see Figure 1) was planned in the late 1950s as a separate ‘city’ with its own infrastructure, and town council, in the former ‘Bantu homeland’ of Ciskei. Mdantsane was built to deal with the increasing influx of African people from the rural hinterland into East London and to relocate residents living in the overcrowded shanty areas of Duncan Village (Cook and Opland, 1980).

Case C: Duncan Village Duncan Village is predominantly an informal township lying on the northwest of the old East London city center. This is the city’s most congested residential area. In 1995, it was estimated to have a population of approximately 100,000 people. Between 1964 and 1979, Duncan Village was the target of massive forced removals. Under the apartheid policy of separate development, efforts were made to clear East London of its African population and remove them to the homeland of Ciskei, to be housed in the dormitory township of Mdantsane. Relocation completely transformed the makeup of Duncan Village, from the densely compact living conditions in the 1950s and the mix of urban migrants and permanent residents to a tightly controlled dormitory township where movement of Africans in and out of the areas was carefully monitored (Bank, 1996). In the 1980s, Duncan Village was controlled by a new black urban local government structure and was managed in the same way as other townships in South Africa. These newly created structures were eventually toppled and replaced with a civic structure controlled at the street level. There were few formal residential developments in Duncan Village in the mid-1980s and residential densities in the township started to rise. It now consists mainly of informal settlements.

Case D: Parkside, Parkridge, Pefferville, and Buffalo Flats Most of the colored population lives in these areas in Buffalo City (Table 1). In terms of their geographic position in the city, they are clustered together in neighboring areas and lie to the west of central East London and adjacent to Duncan Village as shown in Figure 1.

Demographic Differences in the Four Case Study Areas Household Size Cases B and D have the largest average household size (more than four persons per household). By contrast, Cases A and C have an average of some three persons per household (Table 2). Most female-headed households were in Case B (Table 3).

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Table 2. Household size (%).

1 2 3 4 5 6 >6 Average household size

Case A

Case B

Case C

Case D

6.3 26.8 19.7 31.0 9.9 3.5 2.8 3.35

7.9 15.8 19.8 17.6 12.7 8.9 17.2 4.32

29.6 23.0 14.3 14.8 5.6 9.2 3.6 2.88

2.9 14.4 19.0 22.4 19.0 9.8 12.6 4.37

Table 3. Gender of household head (%).

Male Female

Case A

Case B

Case C

Case D

81.1 18.9

50.9 49.1

57.0 43.0

64.5 35.5

Age Distribution Figure 2 shows that the biggest differences in age cohorts between the case study areas are to be found in the age group between 20 and 29 years. About 26% of Case C residents were in this age group as opposed to 10% of residents in Case A.

Adult Education Levels Table 4 shows that 51% of residents in Case A obtained some form of tertiary education, as opposed to less than 10% of residents in other areas. Almost 40% of residents of Case C did not attend secondary schooling.

50% 40%

Case A Case B Case C Case D

30% 20% 10% 0% 0–19 20–29 30–39 40–49 50–59 60–69 70+

Fig. 2. Age distribution.

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Table 4. Adult education levels (%). Case A

Case B

Case C

Case D

0.0 0.0 4.3 45.3 50.5

4.6 0.0 21.7 64.3 9.5

6.7 0.0 32.9 58.6 1.7

3.4 0.0 20.8 68.1 7.8

No education Preschool Grade 1–7 Grade 8–12 Postmatric

Material Living Conditions Income Figure 3 and Table 5 show the extreme wealth differences in Buffalo City. Wealthiest areas are located in the formerly white suburbs (Case A). Poorest residents live in Cases B and C. Figure 3 shows that 10% of residents in Case C have no household income whereas 14% of residents in Case A have household incomes ranging between R16,001 and R30,000 per month. For Case C residents, the largest share of the population (25%) had a monthly household income of R1–R200 per month. The largest share of Case B residents (28%) had incomes of R501–R800 per month, whereas the largest share of Case A residents (22%) had monthly household incomes ranging between R11,001 and R16,000.

Employment Status Unemployment is highest in Case B (32%), Case C (28%), and Case D (16%)— Table 6. In Case A, unemployment is lowest (2.5%).About 43% of residents in Case A were either formally employed or self-employed. This was in contrast to the poorest case study area, Case C, where there were roughly equal numbers of people employed in the formal and informal sectors (14% in each sector). 30% 25% Case A

20%

Case B

15%

Case C

10%

Case D

5%

Fig. 3. Income distribution.

R30001+

R16001 – R30000

R11001 – R16000

R8001 – R11000

R6001 – R8000

R4501 – R6000

R3501 – R4500

R2501 – R3500

R1501 – R2500

R801 – R1500

R501 – R800

R201 – R500

R1– R200

No Income

0%

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Table 5. Income distribution (%).

No income R1–R200 R201–R500 R501–R800 R801–R1500 R1501–R2500 R2501–R3500 R3501–R4500 R4501–R6000 R6001–R8000 R8001–R11000 R11001–R16000 R16001–R30000 R30001+ Average

Case A

Case B

Case C

Case D

0.0 0.0 0.0 1.8 5.4 2.7 4.5 6.3 8.0 13.4 18.8 22.3 14.3 2.7 R10,754.04

9.2 5.7 6.7 28.5 24.3 13.8 6.9 2.5 1.9 0.2 0.2 0.2 0.0 0.0 R1,238.39

10.3 25.4 24.6 22.2 11.9 3.2 1.6 0.8 0.0 0.0 0.0 0.0 0.0 0.0 R535.71

0.6 3.8 3.8 19.6 21.5 18.4 12.0 7.0 6.3 1.3 3.8 1.3 0.0 0.6 R2,540.83

Table 6. Employment status (%).

Missing Self-employed Employed part time in the formal sector Employed full time in the formal sector Work full time in informal sector Work part time in informal sector Pensioner (age/retired/sick/disabled, etc.) Housewife Student/scholar/child Unemployed, not looking for work Unemployed, looking for work Base

Case A

Case B

Case C

0.6 10.8 1.5 30.6 0.8 0.0 15.2 4.6 33.3 0.0 2.5 474.0

0.2 2.0 1.3 10.8 0.6 1.3 10.3 1.3 40.5 2.0 29.8 2242.0

2.6 5.8 0.5 8.0 7.0 7.3 3.0 2.1 36.0 0.9 26.9 573.0

Case D 9.5 1.8 4.0 17.2 0.4 0.3 12.4 3.4 35.5 0.8 14.7 767.0

Employment Blockages Residents living in highest unemployment areas (Cases B and C) perceived the major employment blockages to employment as: not enough jobs available; need of higher qualifications, further skills training, and more work experience—Table 7.

Work-Seeking Strategies Table 8 shows that the major work-seeking strategies are: hearing about jobs from friends and family. For residents of Case B, reading the newspaper was their second most used strategy for finding employment, whereas residents from Case C said waiting for work on the roadside for work was their second most used workseeking strategy.

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Table 7. Employment blockages (%).

Not enough resources to respond Not enough jobs available Live too far from job opportunities Care for the household Not enough experience Need further skills training Need higher qualifications Total number

Case A

Case B

Case C

Case D

4.4 43.5 4.4 39.1 13.0 17.4 17.4 23.0

52.8 72.5 52.8 22.3 58.6 61.2 61.9 273.0

20.7 41.3 16.7 12.7 30.7 41.3 38.7 150.0

36.8 64.9 36.8 50.9 36.8 50.9 49.1 57.0

Table 8. Work-seeking strategies (%). Case A

Case B

Case C

Case D

0.0 0.0 16.3 2.0 4.1 0.0 61.2 18.4 49.0

0.0 14.5 22.3 36.8 7.1 1.2 27.0 20.5 337.0

0.0 11.5 12.5 55.8 25.0 0.0 7.7 9.6 104.0

5.2 7.8 15.6 13.0 7.8 0.0 51.9 9.1 77.0

Refuse to answer Department of Labor Job Centers Reading newspaper advertisements Hear about jobs from friends and family Wait for work on the roadside Wait at gates of businesses Not looking for work No strategy Base

Dependency Ratio Table 9 shows that average dependency ratios6 were highest in Cases B, C, and D and lowest in Case A, indicating that households in predominantly white areas have fewer dependents to income earners.

Transport Mode of transport as well as time taken to travel to work/place of study indicates that the main features of the apartheid city are still evident in Buffalo City. Poorest residents in the city are worst off with respect to the type of transport they

Table 9. Dependency ratios. Case study area Case A Case B Case C Case D

Average dependency ratio 0.41 0.64 0.52 0.52

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use and are furthest away from places of work or study. The main mode of transport for residents in Cases B and C is walking followed by traveling in minibus taxis. Some 85% of residents in Case A travel to work or place of study by car (Table 10). While 25% of residents living in Case A take more than 15 minutes to get to work or place of study, 32% of residents living in Case B take more than 15 minutes. Some 60% of residents living in Case C take this length of time to travel to work (Table 11).

Type of Tenure and Housing A majority of residents in Cases A and B live in a formal house on a separate stand—Table 12. About half of the residents from Case D lived in a house on a separate stand and one-third lived in either semidetached/townhouses/simplexes or duplexes.The majority of residents in Duncan Village (Case C) lived in informal/shack dwellings. With respect to type of tenure, a majority of residents in formal areas (Cases A and B) either owned their own land or were paying it off—Table 13. Some residents, particularly those living in Case B had acquired their house using a government subsidy (16%). One quarter of residents in this area and just under one-third of residents in Case D were renting either through a private rental/housing

Table 10. Transport mode (%).

Missing Walk Motorbike/bike Bus Train Minibus taxi Motorcar Lift club Work at home Do not work/study

Case A

Case B

Case C

Case D

0.0 3.8 0.8 0.4 0.0 0.6 84.8 1.9 1.3 6.3

1.7 33.3 0.2 0.2 1.2 29.8 1.9 0.1 0.4 31.2

1.6 35.1 0.0 0.0 0.0 22.3 0.2 0.7 2.1 38.1

2.6 20.3 0.8 0.8 0.0 37.7 13.3 1.4 0.0 23.1

Table 11. Duration of trip (%).

None <15 min 15–30 min 30–60 min 1–1.5 h 1,5–2 h >2 h

Case A

Case B

Case C

Case D

47.8 27.5 19.6 2.9 0.7 0.7 0.7

64.1 4.3 13.3 15.8 1.8 0.2 0.4

34.8 5.4 49.5 8.2 2.2 0.0 0.0

56.4 6.7 25.2 9.8 1.2 0.0 0.6

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association or through a public rental. The majority of residents in Case C were living informally and not paying rent.

Access to Basic Household Services Majority of residents (between 95% and 100%) in all the formal housing Cases (A, B, and D) have access to the optimum range of the following basic household services: full waterborne flush toilets; and refuse removed by the local authority once a week (Table 14). Residents with the best access to piped water from full pressure pipes (between 74% and 96%) were those in Cases A, B, and D, respectively. Majority of residents in Cases A, B, and D (90–100%) used electricity for lighting. While majority of residents from Cases A and D (between 90% and 100%) used electricity for cooking, some 67% of residents in Case B used electricity for Table 12. Housing type (%).

Missing House or formal structure on a separate stand Traditional dwelling/hut/structure made of traditional materials Flat in a block of flats Town/cluster/semidetached house (simplex/duplex or triplex) Unit in retirement village House/flat/room, in backyard Informal dwelling/shack, not in backyard Informal dwelling/shack, in the backyard Room/flatlet in main dwelling

Case A

Case B

Case C

Case D

0.0 89.4

1.2 93.7

0.0 0.5

0.0 52.3

0.0 0.7

3.4 0.0

0.0 0.0

0.0 8.1

9.2 0.0 0.0 0.0 0.0 0.7

0.2 0.2 0.2 0.6 0.6 0.0

0.0 0.0 0.0 98.5 1.0 0.0

31.0 0.6 2.3 0.6 5.2 0.0

Table 13. Type of tenure (%).

Purchased, fully paid off Purchasing, paying off a bond Acquired via government subsidy Private rental/housing association Public rental Subtenant Rent free Informal, paying rent Informal, not paying rent Tribal tenure House sitting Acquired via government subsidy and own contribution

Case A

Case B

Case C

Case D

38.7 44.4 7.0 4.9 0.7 0.0 2.1 0.0 0.0 0.0 0.0 2.1

30.1 16.2 16.2 9.5 16.4 1.6 4.6 0.2 0.0 3.6 0.8 0.8

0.5 0.0 0.0 0.0 0.0 0.5 0.5 0.5 98.0 0.0 0.0 0.0

42.5 17.2 0.0 16.7 15.5 2.9 3.5 0.0 0.6 0.0 0.0 1.2

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Table 14. Basic services (%).

Full waterborne flush toilet (off-site disposal) Refuse bags removed from the house by local authority at least once a week Piped water in dwelling from full pressure pipes Electricity for cooking Electricity for lighting Electricity supply

Case A

Case B

Case C

Case D

100.0

93.5

41.3

95.4

97.9 96.5 100.0 100.0 99.3

94.9 92.9 67.7 91.1 96.2

96.9 3.1 4.1 4.6 4.6

95.4 74.1 92.0 92.0 93.1

cooking. This perhaps suggests that residents in these areas may prefer other sources of power for cooking (such as paraffin and gas). With the exception of access to refuse-removal services, residents in Case C are worst off with respect to access other basic household services and less than 5% of residents have access to electricity and piped water with full pressure. While most residents in Case A had access to electricity via a conventional meter system, residents in the other case study areas accessed electricity mainly through the prepaid-card system (Table 15).

Access to Community Services Table 16 shows differences in access to community services across the case study areas. It is clear that residents in Case A are best off with respect to access to most community services and have between 95% and 100% access to many of these services. About 10% or less of residents from Case C have access to the following services: low-cost housing; electricity supply; parks and open spaces; bus transport; and train service. Residents in Case B had poor access to the following community services: housing (high and low cost) and signposting of roads and pavements.

Perceptions of Quality of Life Domain Satisfactions Table 17 shows that the majority of residents in Case A were satisfied with most aspects of their neighborhoods. The shortage of community services in Cases B and C is reflected in the low satisfaction ratings they gave to various aspects of

Table 15. Type of electrical supply (%).

Conventional meter Prepaid meter

Case A

Case B

Case C

Case D

79.9 20.1

3.1 96.9

11.1 88.9

26.3 73.8

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Table 16. Access to community services (%).

Public telephones Postal deliveries Post office Police services Hospital Clinic Ambulance Fire department New low-cost housing New high-cost housing Water supply Electricity supply Street lighting Road surfaces Traffic flow Stormwater drains Signposting of roads Pedestrian safety Pavements Parks/open spaces Sports facilities Libraries Public schools Community halls Bus transport Train service Minibus taxis Refuse removal Sanitation Crèches Pension payout

Case A

Case B

Case C

Case D

100.0 100.0 100.0 100.0 99.3 99.3 97.9 95.1 9.2 25.4 98.6 99.3 100.0 100.0 100.0 100.0 99.3 100.0 97.9 69.7 65.5 99.3 98.6 96.5 69.7 40.1 88.0 99.3 100.0 99.3 38.7

87.5 97.6 76.6 75.5 71.5 95.6 74.7 55.3 21.2 14.9 97.4 97.8 81.6 68.9 67.5 43.0 27.1 38.0 29.5 8.1 39.2 45.4 97.4 55.8 35.8 48.9 98.4 95.5 92.9 83.4 67.7

34.2 52.0 74.0 96.9 98.5 99.5 95.9 93.4 10.2 2.6 70.4 10.7 53.6 87.2 90.8 38.3 80.6 85.7 54.1 4.1 93.4 99.0 100.0 99.0 3.1 1.5 96.9 96.9 63.8 94.4 95.4

85.6 96.6 75.3 68.4 76.4 79.9 83.9 76.4 68.4 58.1 95.4 94.3 98.9 98.3 97.7 97.1 93.1 87.9 86.8 48.3 68.4 86.2 97.1 90.2 30.5 23.6 96.0 99.4 97.1 85.1 81.6

Table 17. Rating of community features (% satisfied and very satisfied). Case A Case B Case C Case D Buffalo City Attractive neighborhood Neighborhood cleanliness Safety Employment opportunities Acceptably serviced housing Standard of living in neighborhood Community/suburb pride

93.0 90.1 78.0 43.0 89.4 92.2 89.3

58.7 51.3 19.8 1.5 28.1 22.9 51.3

13.4 9.3 2.1 3.2 0.0 0.5 5.2

68.0 59.8 35.8 4.3 48.2 53.9 61.2

58.5 49.9 32.5 8.5 31.7 35.1 54.0

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their neighborhoods. For example, in Case C fewer than 5% of residents were satisfied with safety issues, community/suburb pride, and housing service levels; less than 10% were satisfied with neighborhood cleanliness; and only 13% were satisfied with neighborhood attractiveness.

Perceptions of Safety All the case study areas perceived that the crime situation in Buffalo City had worsened. Case study areas B, C, and D were most pessimistic about the crime situation (Figure 4). Residents from Cases B and C have been most affected by violent and nonviolent crimes as shown in Table 18. It is not surprising to find these residents to be most pessimistic about the crime situation. Differences in daytime and nighttime safety in the four case study areas also probably reflected the incidence of crime in the four areas. The highest crime areas (B and C) were also those areas where residents felt least safe during the day or night as shown in Figure 5.

Benefits of Living in Buffalo City and Perceptions of Community Improvement/Deterioration The most materially disadvantaged residents in Buffalo City, those living in Case C, were the least optimistic about perceived benefits of being part of the new municipal entity (Table 19). Just 6% of residents from this area believed they

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

86.2%

65.9% 58.5%

52.9%

26.1% 16.4% 9.1%

6.3%

Case A

Case B

23.0% 5.6% 0.5%

Case C

Better Same Worse

4.6%

Case D

Fig. 4. Perceptions on crime situation.

Table 18. Victims of violent/nonviolent crime (%).

Violent Nonviolent

Case A

Case B

Case C

Case D

12.6 41.3

23.9 37.0

22.9 50.8

8.1 13.8

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0% Case A

82.2%

Daytime safety Nighttime safety

Case C

30.5%

80.4% Case B

31.6% 1.5%

20%

10.9%

40%

48.6%

60%

95.8%

80%

Case D

Fig. 5. Perceptions on daytime/nighttime safety. Table 19. Benefits of living in Buffalo City (%).

Don’t know Yes No

Case A

Case B

Case C

Case D

11.3 26.8 62.0

35.3 22.6 42.2

27.0 5.6 67.4

24.7 42.5 32.8

would derive benefits. Residents from this area are the least skilled (40% obtained no more than primary education) and they may feel that changes to the municipal structure7 will not influence their development prospects as long as they do not have the skills to take up the employment opportunities, which the new municipality may facilitate and encourage. Residents in Case D were most optimistic about the perceived benefits of living in Buffalo City. The higher income areas (Case A) were the most pessimistic with slightly less than two-thirds believing they would not derive any benefits from the new municipality. It may be that residents from these areas perceive that any future development will be toward the disadvantaged communities in the city and therefore cannot perceive any direct and immediate benefits for themselves. The high percentage of residents who indicated that they did not know whether they would derive any benefits of living in Buffalo City, particularly those in Cases B and C, may indicate that these residents were not even aware that a new municipality had been established. Consequently, they may not have thought about possible benefits of living in Buffalo City. About 47% of residents were not aware that Buffalo City was the newly established municipality at the time of the survey. With respect to perceptions of community improvement/deterioration, residents in all case study areas were pessimistic. Majorities in all areas felt that there had been no change (negative or positive) to their communities. Those residents most disadvantaged under the apartheid system were the most negative, particularly residents in Duncan Village. An overwhelming majority (98%) felt there had been no change (negative or positive) or that their area had actually deteriorated (Table 20).

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Table 20. Community improvement/deterioration (%).

Improvement No change Deterioration

Case A

Case B

Case C

Case D

29.6 53.5 16.9

21.8 63.6 14.5

2.0 83.2 14.8

7.5 69.0 20.1

Global Satisfaction with Life Table 21 and Figure 6 show that Duncan Village and Mdantsane residents (59% and 55%, respectively) are most dissatisfied with life as a whole. People living in these areas are worst off across the entire spectrum of indicators of material living conditions, which is likely to have had a negative impact on their overall life satisfaction.

Conclusion The 2001 baseline QOL survey in Buffalo City shows that the apartheid legacy of poverty and inequality continues to shape the form and social structure of the postapartheid city. Buffalo City is a fragmented city across race and class. African residents remain in spatially marginalized areas of the city and are worst off in terms of material living conditions. Residents living in the poorest areas of the city, such as Mdantsane and Duncan Village, were found to be least satisfied with their neighborhoods and overall QOL. In spite of the prevailing inequalities in the city, African residents were the most optimistic that life in the new municipality would improve and felt that there would be improved employment opportunities in the future. The Buffalo City survey provides the opportunity for city planners to measure how successfully inequalities in the city are being addressed. For this reason, it will be important to repeat the survey at regular intervals, perhaps targeting specific areas in the city or beneficiaries of particular city development projects. The time line provided by repeat surveys will give a true picture of the changes that are taking place, and most importantly, whether or not the city is able to increase the QOL of all its people. Table 21. Life satisfaction (%).

Missing Very satisfied Satisfied Neither/nor Dissatisfied Very dissatisfied

Case A

Case B

Case C

Case D

0.0 40.9 46.5 9.2 3.5 0.0

0.8 5.9 17.2 21.4 43.8 10.9

1.0 1.0 6.6 32.7 31.1 27.6

9.8 12.1 41.4 13.8 16.7 6.3

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ROBIN RICHARDS AND ELLEN KAMMAN 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0%

Very satisfied Satisfied Neither/nor Dissatisfied Very dissatisfied

Case A

Case B

Case C

Case D

Fig. 6. Life satisfaction.

Notes 1.

The others being being:; Cape Town, Ekurhuleni (East Rand), eThekwini (Durban), Johannesburg, Mangaung (Bloemfontein), Msunduzi (Pietermaritzbug), Nelson Mandela Metropole (Port Elizabeth), and Tshwane (Pretoria). 2. Main towns in Buffalo City being: East London, King Williams Town, Berlin, and Bisho. 3. The 1950 Group Areas Act had its greatest impact in the 1960s and 1970s after the act was amended. The apartheid city was characterized by an exclusively white CBD, surrounded by white residential areas. African, Indian, and colored townships were located on the periphery, furthest from work opportunities, and hostels for migrant workers were relocated from areas close to places of employment to African townships (Lemon, 1991). 4. David Smith (2003). Confronting fragmentation: housing and urban development in a democratic society. 5. The researchers wish to thank Swedish International Development Cooperation Agency (Sida) for the financial support and for the expertise they provided. The City of Durban’s Corporate Policy Unit is also thanked for the support role it played in the study’s implementation. 6. The dependency ratio is calculated by dividing the total number of nonincome earners by the total number of household members. 7. The local government elections in South Africa in 2000 marked the final phase in local government restructuring with the merging of smaller municipal structures into larger ones, which were deemed to be better able to address problems of poverty and development in surrounding communities. Buffalo City was the result of a merger between two major towns: East London and King Williams Town.

References Buffalo City Municipality Integrated Development Plan (2002). Bank, L. (1996). Poverty in Duncan Village, East London: A Qualitative Perspective. Report Prepared for the World Bank’s Qualitative Poverty Assessment in South Africa. Grahamstown: Institute of Social and Economic Research, Rhodes University.

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Cook, G. and Opland, J. (1980). Mdantsane Transitional City. Occasional Paper Number Twenty-Five. Grahamstown: Institute of Social and Economic Research, Rhodes University. Israel, D. (1992). Determining Sample Size. Fact Sheet PEOD-6. University of Florida. Lemon, A. (1991). The Apartheid City, in Homes Apart: South Africa’s Segregated Cities. Bloomington, IN: Indiana University Press. Proshansky, H.M. and Fabian, A.K. (1986). Psychological Aspects of Quality of Urban Life. In Frick, D. (ed.), The Quality of Urban Life. New York: Walter de Gruyter, pp. 19-29, cited in Sirgy, M.J., Rahtz, D.R., Cicic, M., and Underwood, R. (eds.), A method of assessing residents’ satisfaction with community-based services: a quality of life perspective. Social Indicators Research, 49:279–316. Smith, D.M. (2003). Urban fragmentation, inequality and social justice: ethical perspectives. In Harrison, P., Huchzermeyer, M., and Mayekiso, M. (eds.), Confronting Fragmentation: Housing and Urban Development in a Democratic Society. Cape Town: University of Cape Town Press. Stats SA, Census 2001 Watts, H.L. and Agar-Hamilton, J.A.I. (1970). Border Port: A study of East London, South Africa, with Special Reference to the White Population. Occasional Paper Number Thirteen. Grahamstown: Institute of Social and Economic Research, Rhodes University.

ROBIN RICHARDS, Researcher, Community Agency for Social Enquiry (CASE), Johannesburg [email protected]

ELLEN KAMMAN, Researcher, Fort Hare Institute of Social and Economic Research (FHISER), University of Fort Hare, East London [email protected]

Making Community Indicators Accessible Through the Census Information Center: Howard University, Portals to the Community, and the New American University RODNEY D. GREEN,1 MAYBELLE TAYLOR BENNETT,2 HAYDAR KURBAN,3 LORENZO MORRIS,4 AND CHARLES C. VERHAREN5 1

Executive Director, Center for Urban Progress, Howard University 2 Director, Howard University Community Association 3 Assistant Professor of Economics, Howard University 4 Professor and Chair, Political Science Department, Howard University 5 Professor, Philosophy Department, Howard University

The New American College, as a connected institution, would be committed to improving, in a very intentional way, the human condition . . . a new model of excellence in higher education would emerge, one that would enrich the campus, renew communities, and give new dignity and status to the scholarship of service. [We need] a new paradigm of scholarship, one that not only promotes the scholarship of discovering knowledge but also celebrates the scholarship of integrating knowledge, of communicating knowledge, and of applying knowledge through professional service. Ernest Boyer, President, Carnegie Foundation (1994)

Discussions about community indicators often focus more on the discovery about knowledge and less on the integration, communication, and application of the knowledge embodied in community indicators. Yet such indicators are intended to inform practitioners at every level of the community, and cannot be effectively implemented without the other three components to which Boyer alludes. This chapter presents a model for better integrating such knowledge and making it available to universities and community groups. It is linked Historically Black Colleges and Universities (HBCUs) and their Census Information Centers (CICs). The model also provides for a fuller application of information gained from community indicators, as well as other sources, to pressing community concerns. The university–community partnership implied in Boyer’s New American College works for HBCUs and for higher education writ large. The site of the model discussed in this chapter—Howard University, a research and doctoral/research extended institution (as opposed to a “college”)—indicates both the potential availability of a very broad range of resources for such a partnership process and the greater internal tension over mission. It is traditional institutional tension that characterizes major American universities, one of community engagement versus scholarly detachment.

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To set the context for the model, the historical roots of community engagement of both public and private institutions of higher education are reviewed, followed first by a discussion of the vision for HBCUs held by W. E. B. Du Bois and then by a review of recent relevant HBCU accomplishments that are in line with that vision. A brief examination of another model of engagement known as the Dutch Science Shop experiment follows. This broad contextual review is then augmented by a review of university–community partnership developments in the since 1994 at Howard University, which were sparked by emergence of two key university units: the Howard University Center for Urban Progress (HUCUP) and the Howard University Community Association (HUCA). These two groups link the university and community in multiple ways. The Howard University Census Information Center (HUCIC) is an extension of the university’s evolving university–community partnership process led by these two units. It integrates and links the resources of the university to community partners to assist in meeting their defined research and analysis needs. The HUCIC model may indicate pathways to translate new knowledge developed through community indicators research into more useful and applicable knowledge for community-based development.

American Colleges and Universities in Historical Perspective The academy is often considered a place for detached scholarly pursuits with little direct relationship to the broader society. The modern American research university, with roots in the 19th-century German research university, has largely devalued broad sympathetic scholarship that could provide general education to the next generation and encourage service to surrounding communities. This narrow conception of the university’s social role is at odds with the earlier formal missions of major universities.1 Historically black colleges have more consistently maintained a broader social role by nurturing “broad sympathy,” as Du Bois called it. The black college, in Du Bois’s view, was and should always be a place where the interface of social responsibility and scholarship would find its fullest expression (Du Bois, 1990 [orig. 1903]). Many 19th-century university presidents strove to use their institutions to meet the needs of the changing society around them (Diner, 1980). The tradition of academically-informed service and service-informed scholarship is found in the earlyhistory of leading urban higher educational institutions that, today, ironically, are thought of as traditional research universities. Consider the early history of Johns Hopkins University, which today is a leading American research university facing challenging relationships with its surrounding community. Ira Harkavy, one of today’s leading advocates of the responsible university, comments on the late 19th-century period: John Glenn, chair of the executive committee of [the Charity Organization Society] COS, remarked in 1888 that Hopkins was the first university where social welfare work was “almost a part of the curriculum.” . . . Hopkins’ president, Daniel Coit Gilman, . . . was the guiding force behind

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the organization of the COS. An organization designed to provide a scientific approach to helping Baltimore’s poor, COS, among other things, studied the causes of poverty, collected useful data, and worked to get at the root causes of destitution. Moreover, a number of Gilman’s leading faculty members such as Herbert Baxter Adams and Richard Ely had close ties to Levering Hall, the campus YMCA, which was deeply engaged in work with Baltimore’s poor. Students in Adam’s and Ely’s Department of History, Political Economy and Political Science worked through Levering Hall “to use the city as a laboratory for economic study.”2

This model in which social science experts at the university provide service to the passive poor is, by today’s standards, elitist and counterproductive to healthy partnerships; still, in comparison to today’s research university model, it has a progressive flavor. These faculty, administrators, and students were discovering, integrating, communicating, and applying knowledge that was generated through a university–community connection. Other university leaders of the late 19th and early 20th century appeared even more unified with the surrounding community than Johns Hopkins. Harkavy (1992) notes that: Seth Low, president of Columbia from 1890 through 1901, argued that “the city may be made to a considerable extent, a part of the university.” Columbia was also to be part of the city, resulting in a democratic, mutually beneficial relationship between town and gown. In an article, “The University and the Workingman,” Low wrote that the “workingmen of America . . . [should know] that at Columbia College” . . . the disposition exists to teach the truth . . . without fear or favor, and we ask their aid to enable us to see the truth as it appears to them. (Bender, 1987, pp. 282–3).

The University of Chicago, while not committed at the highest levels to a partnership process, is nevertheless famed for the scholarly university–community partnership work associated with Jane Addams’ Hull House. Addams combined social, educational, humanitarian, and civic projects. These included engagement in labor union issues, ongoing forums for social reform, and social science research. Addams noted that “the settlements antedated by three years the first sociology departments in universities and by ten years the establishment of the first foundations for social research.”3 Sociologists at the University of Chicago associated with Hull House acknowledged that “Addams and Hull House . . . were the leader and leading institution in Chicago in the 1890s, not the University of Chicago.” Hull House Maps and Papers “established the major substantive interests and methodological technique of Chicago Sociology that would define the School for the next forty years” (Degan, 1988, pp. 5, 24). In the early years of the Chicago School, no invidious distinctions were made between the applied sociology pursued by Jane Addams and the Hull House residents and the academic research of the early University of Chicago sociologists. Like the women of Hull House, the Chicago sociologists were “social activists and social scientists” (Fitzpatrick, 1990, p. 33). But after 1915, Chicago sociology under the leadership of Burgess and Park adopted a detached model of analysis

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abjuring direct intervention in the community as part of the process of knowledge development (Bulmer, 1984). The engagement of major private universities with their surrounding communities was not without its own dangers, especially as the fear of radicalism bolstered by the Russian Revolution led universities to self-police and find safety in separation from the community by the creation of cloistered ivory towers. Yet the precedent for engagement, in which knowledge is integrated and applied through community–university collaboration, still resonates from these early years.

Historically Black Colleges and Universities and W.E.B Du Bois The creation of private and later public black colleges and universities occurred in a world apart from the white mainstream institutions. The heads of the latter were part of the leadership of the nation; HBCUs, on the other hand, emerged from a complex mix of missionary-guided liberal arts pedagogy and work-oriented “self-help” industrial education. The primary model of industrial education was Tuskegee Institute under the iron leadership of Booker T. Washington. This model was adopted by Hampton Institute and many other HBCUs. The liberal arts orientation was reflected in Du Bois’s alma mater, Fisk University, as well as in Howard University, which was and is in a class by itself in terms of resources and diversity of programs. Many HBCUs originated as “normal schools”—essentially technical high schools—and rarely gained adequate levels of resources to become major educational centers. Throughout the South, small liberal arts schools (such as Rust College and North Carolina Central University) and larger agricultural and mechanical (or technical) schools (such as North Carolina Agricultural and Technical State University) dotted the landscape. Despite their diversity in funding and orientation, all of these clusters of HBCUs produced black leaders. Their graduates constituted the “talented tenth” that many thought would lead the black race to equality, and surely provided the professionals (doctors, nurses, ministers, teachers, undertakers, and other similar professions) necessary for the geographically and socially segregated African American population. Their service was often a practical service more than a problem-solving service of the sort proposed by the major white private universities.4 This limited early role for HBCUs was challenged by Du Bois, who argued that one of the “great limitations of the older Negro college was that they came up with the idea of detachment from the town, city, and state where they were.” The initial cause of this detachment was “slavery and its consequences” with the effect that “an intellectual class was trained which had no organic connection with the community around it.” Du Bois advocated a college that is “an integral part of the community, of the colored community, of course, first; but also and just as needfully of the white community, so that in all its work and thinking ... the community and college should be one and inseparable....”5 Du Bois argued that black progress would be led by the talented tenth, whose members would be socially responsible, integrated with the rest of the community, and personally nonmaterialistic. The college, in his view, would thus lead its community and offer “outreach” programs to its neighboring communities, with the assumption that the college and its talented tenth had knowledge that it should

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share with the community.6 This view is consistent with those of the early leaders of Hopkins, Columbia, and Chicago. In today’s more enlightened, revised model of the engaged university, the university and the community reach out to one another, without a presupposition of a knowledge hierarchy. Yet the knowledge must be integrated and communicated among the partners if the application of this knowledge is to prove fruitful. This revised model has three primary objectives: (1) to strengthen the bonds between colleges and universities and their surrounding communities by furnishing direct access to college and university research capacities; (2) to help minority communities solve problems in unprecedented ways through access to those same research capacities; and (3) to give a more democratic orientation to research conducted at the nation’s colleges and universities. This model can advance Du Bois’s greatest dream for HBCUs: “Today there is but one rivalry between ... college training and trade and professional training, and that is the rivalry of Time. Some day every human being will have college training.”7 HBCUs continue to play a major role in African American education and hence in the education of the nation. HBCUs enroll 14% of all African American students in higher education, even though they constitute only 3% of America’s 4,084 institutions of higher education. In 1999, these institutions matriculated 24% of all African American students enrolled in 4-year colleges, awarded master’s degrees and first-professional degrees to about one-six of the African Americans men and women, and awarded 24% of all baccalaureate degrees earned by African Americans nationwide. There are 40 public 4-year, 11 public 2-year, 49 private 4-year, and 5 private 2-year institutions. Many of these institutions have accepted Du Bois’s challenge of engaging communities in their missions and programs. Howard University has been one of the leaders in this effort, as discussed below, but many other HBCUs have profound relationships with their communities. Engagement has occurred through service-learning connections between students and community, direct social services, public education leadership, direct “brick-and-mortar” collaborations, and applied, community-based, research (PDR, 2003). Several HBCUs created their own community development corporations (CDCs) to focus their revitalization efforts in their nearby communities. Mississippi’s Alcorn State University was instrumental in launching the Traceway CDC, providing affordable housing and business support to its two adjacent counties in southwest Mississippi (PDR, 2003, p. 46), while Jackson State University’s affiliation with the West Jackson CDC has brought about substantial revitalization in the distressed neighborhoods surrounding its campus. Langston University in Oklahoma similarly created its own CDC to build a fire station and a small retail mall for the Town of Langston on university property. Kentucky State University has likewise partnered with its neighboring Frankfort community to build affordable housing, a community center, and various other revitalization amenities (PDR, 2003, p. 227). In areas of service, Johnson C. Smith University has operated Project Excel in Charlotte, North Carolina, to provide intensive tutoring and mentoring to public school students, while Delaware State operates a similar program that supports Wilmington’s Howard Public High School of Technology (PDR, 2003, p. 63).8

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Norfolk State University provides leadership training to Virginia Beach residents, and partners extensively in community-oriented real estate development in the neighborhoods surrounding its campus; nearby Hampton University provides a strong entrepreneurship program for its surrounding communities (PDR, 2003, pp. 21, 72). Bennett College in North Carolina has created and staffed classrooms directly in public housing at four sites in Greensboro, North Carolina (PDR, 2003, p. 51), while Clark Atlanta University’s partners in a planned community program have, since 1991, similarly brought educational strengths to youth in public housing near the university (PDR, 2003, p. 58). Finally, Stillman College in Tuscaloosa, Alabama, has projected its resources into a diverse array of educational, youth leadership, and workforce development efforts (PDR, 2003, p. 229). These examples reflect the larger reality of the potential for HBCUs of all types to lead the national effort to link universities and communities.

Another Precedent: The Dutch Science Shop An enlightening experiment in the Netherlands can perhaps add value to the existing models of HBCU engagement. This model established a physical, bridging, presence of the university in the community. Universities were required by federal law to dedicate a percentage of their budgets to staffing storefronts with university personnel. Each storefront provided community residents with access to the research capacity of its associated university. Such storefronts were called “Dutch Science Shops.” Protocols between the university and the federal government established the nature and extent of the research that universities could perform for neighborhood residents. Community residents were encouraged to walk into the “science shops” to present their unsolved problems to staff. Many times, such problems could be addressed through previously established pathways, and the science shop staff merely served as a referral center. Residents with legal or medical problems, for example, were directed to university clinics for help. In cases where residents presented problems that did not yet have good solutions, the staff contacted one of the university’s research arms in order to set up a team to work on those problems. These interdisciplinary teams enriched the research dialogue in the universities themselves while contributing to social improvement. The Dutch science shop model had two primary objectives: (1) to give citizens direct access to research services that are funded in large measure by federal taxes and (2) to give a more democratic orientation to research otherwise predominantly controlled by federal and corporate funding.9 The outcome of these two objectives would be fuller integration of the university with community life. The emerging university–community partnership model at Howard University is similar to the Dutch science shop model. Howard University’s neighbors need research support (often interdisciplinary in character) from the many disciplines that comprise Howard University’s problem-solving power, including its social scientists and urban planners, its artists and humanists, as well as its natural scientists.

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Historically Black Colleges and Universities, Howard University, and the Broader Partnership Universities tend to be inward looking despite their formal service missions. Historically, HBCUs have a history of a closer connection with the African American community both socially and geographically than do other schools with their communities, but HBCUs face many obstacles in fulfilling community development goals. The literature related to community development for HBCUs is surprisingly sparse. A considerable amount of work has been done evaluating the role of major non-HBCU schools such as Johns Hopkins University, Columbia College, the University of Chicago, and the University of Wisconsin in community development.10 Visionary ambitions by university leaders as well as by enterprising groups of faculty as they seek to improve to surrounding communities have been told in a stirring manner.11 However, the stories of HBCUs in this area have only begun to be told, in part because of attitudes by social scientists (including some of those at HBCUs), who have been reluctant to study these histories. This neglect may be due, in part, to the fact that the HBCU histories of community development are often relatively modest, at least until recent years. After all, HBCUs have experienced catastrophic financial problems since the turn of the 20th century severely limiting their capacity to fulfill even basic educational functions, let alone major service and development missions.12 At the same time, the legacy of slavery, sharecropping, segregation, and continuing racism has imbued HBCUs with an urgent mission of outreach and uplift.13 The community service mission had, in the period of de jure segregation, been fulfilled via the production of professionals to serve an underserved community, whether they were teachers, preachers, health professionals, or business people. With the civil rights breakthroughs of the 1950s–1970s, however, the services provided by such graduates extended beyond the previously isolated black communities. Today, many HBCUs are located in communities that have ironically been weakened by the abolition of segregation. The deliberate neglect of communities by local, state, and federal governments has combined with the exodus of substantial numbers of stable middle-income black families to create distressed communities in the inner cities.14 Although HBCUs continue to produce large numbers of well-educated graduates and practitioners of many professions, many of these individuals now avail themselves of new opportunities throughout the nation and the world, rather than focus their careers on inner-city African American communities. This outcome reflects the partial democratization of the labor market through desegregation. This change carries with it the irony that highly trained degree recipients can now participate in a national/international labor market, while lower-skilled individuals remain limited to the local labor market. This unevenness in access to labor markets had led to the hollowing out of the skill level of residents in distressed urban communities. Perhaps as a result of this broadening of opportunity for African American professionals, HBCUs in recent years have focused their urban missions on local revitalization efforts in their challenged communities. They have rehabilitated

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housing and commercial areas, improved infrastructure, and extended service activities in health, education, welfare, and training.15 Howard University, in particular, has maintained and expanded its national presence in the political, social, and scientific research arenas while putting increasing attention to the community revitalization needs of its neighbors.16

Howard University’s Recent Community Development Initiatives Howard University has a long tradition of community involvement, development, and outreach. In the 1930s and 1940s, for example, Howard University was an important center of black political activism, providing the launching pad, for example, for the National Negro Congress in 1935 under the auspices of several prominent Howard faculty, and contributing important scholarship to egalitarian projects, such as Ralph Bunche’s contributions to Gunnar Myrdal’s pathbreaking An American Dilemma.17 In the 1950s, Howard University (especially its Law School faculty) was in the forefront of the civil rights movement, playing a major role in the Brown vs. Board of Education case and related litigation. And many community outreach service activities have blossomed at Howard University in the health, training, and welfare areas. Howard University’s contributions in recent decades have tended to be on the public service or behavioral side. A few examples demonstrate the scope of these initiatives. Psychologist Hope Hill, for example, gained national recognition for her community-based work throughout Washington, DC, in violence prevention and conflict resolution. The center for research on the education of students placed at risk (CRESPAR) program, under the leadership of Wade Boykin and including the late Sylvia Johnson, Gerunda Hughes, and many other research faculty, has done an enormous amount of work on reforming teaching styles of public school faculty to meet diverse learning styles of students in at-risk situations. The late Mary Hoover created a dedicated cadre of “tutor warriors” to provide services to low-income families in Washington, DC. The art department has, in the past years, conducted community art clinics and led community artists in developing murals, while the former School of Architecture and Design had a similar history of community-based studios and charrettes. The Institute for Urban Affairs and Research, under the leadership of Lawrence Gary for many years, addressed important urban research questions, including housing and mental health issues as well. Building on this tradition, HUCUP was launched in 1995 as an interdisciplinary center of faculty-based initiatives to comprehensively address, through scholarship and practice, burgeoning distress in inner-city communities. These initiatives, led by the HUCUP executive director Rodney Green, have often been conducted in partnership with HUCA, a component of the Office of the President and directed by Maybelle Taylor Bennett. In recent years, Howard University has added to the array of community development activities by adding in physical development projects as well as human development activities. During the earlier 20-year term of President Cheek (1969–1989), the university’s community relations function was conceived as a bridge to the

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community, presenting a favorable public relations face to the public, and extending opportunities to selected community interlocutors to participate in the cultural and intellectual activities occurring on the campus. Although Reflecting this rather limited engagement, the community relations office was located in a relatively prosperous neighborhood physically distant from the distressed communities adjacent to the main campus. In 1989, a different path for community relations emerged, sparked by controversy over the university’s plans for expansion.18 The resolution of this problem reflected the new approach to community development by the University. It also demonstrated the diversity of the university–community partnership process, and the pathways through which knowledge discovery, integration, communication, and application can proceed with great benefit to the community development process.

The Challenge of University Expansion The construction and expansion of the Howard University Hospital involved mixed blessings. During the 1950s through the 1980s, Howard University acquired and demolished Griffith Stadium, previously home to both Negro League and Major League Baseball, and built the Howard University Hospital, the College of Medicine, and the College of Dentistry. Then, during the 1980s Howard University built a parking garage for hospital employees, and over a period of decades acquired 45 single-family homes and/or vacant lots with an eye toward further expansion. Long-time community residents watched for decades as the university ate away at the residential housing stock of the neighborhood. Residents appreciated modern and local health facilities, but were disturbed by the loss of housing and by the land-banking practices of the university, which simply boarded up its acquired properties for decades, leading to significant deterioration of the neighborhood. Ultimately, the changes in the nation’s health care system with the advent of health maintenance organizations reduced the university’s interest in hospital expansion. Twenty-five years of land banking turned out to have been ill advised, and the crumbling structures that the university owned constituted a blight on the neighborhood. President Franklyn Jenifer, encouraged by the opening of two new subway stations in 1991, “the Clinton Walk”19 on Georgia Avenue, and affirmative gestures from DC’s Department of Housing and Community Development, initiated community revitalization efforts that failed to come to fruition. But a new dynamic had begun. Prospective community partners were interested in a big vision for the deteriorated neighborhoods, which included the historic Howard and Dunbar theaters, as well as some potentially lucrative investment opportunities associated with better access by the new subway stops. A new collaboration developed, which included the Peoples Involvement Corporation (a CDC), Manna Inc. (a nonprofit affordable housing developer), the DC Department of Housing and Community Development, and Howard University, with a focus on the area near a new subway stop in close proximity to the university. The Georgia Avenue Community

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Renaissance Initiative (GACRI), a collaboration of partners, was formed in 1994, and Howard University began a new stage in its community relations and its own community development activities. GACRI held two community meetings with a broad invitation to civic associations, advisory neighborhood commissions (ANCs), and the combined mailing lists of the GACRI organizations. GACRI indicated that it had come together to follow up the Clinton Walk and to foster community-sensitive development at the Metro station, followed by even bigger development plans. The Walk symbolized renewed public commitment to black small business development. Although the community residents were interested in the big Georgia Avenue plans of the GACRI members, they emphasized the need to “clean up Howard’s backyard” first. So GACRI shifted its attention to the boarded and vacant houses owned by Howard University. The CDC partners were to be players in the rehabilitation process. The new Howard University president, H. Patrick Swygert, met with GACRI members in 1997 and indicated that the university had indeed decided to focus its attention on the neighborhoods near the campus, but preferred a single, rapid, 45 property rehabilitation/new construction plan rather than the gradualist GACRI plan of rehabbing five houses per year. The Fannie Mae Corporation and several other major private corporations joined with Howard University to make the plan happen. The university launched the LeDroit Park Initiative and completed its first phase in 2002. Grant funding (largely from the U.S. Department of Housing and Urban Development) was obtained by Howard University for specific projects in the community in partnership with the CDCs, as the collaboration added an additional 30 housing units in the same neighborhood through this process. Thus, the university has augmented its social research, social service, legal outreach, and political activism by undertaking physical rehabilitation and revitalization of its surrounding communities in partnerships with community-based organizations as well as major institutional players like Fannie Mae and major banks. Since the early 1990s Howard University has invigorated its community relations mission to embrace an engaged, partnership approach to a range of community needs, from “brick-and-mortar”, real estate development questions to workforce and business development, to determined efforts to bridge the digital divide facing the African American and Latino communities in the university’s vicinity. The signature project of this activity was the LeDroit Park Initiative.20 Service corps programs that operate out of HUCA in partnership with HUCUP and other university units have placed students in schools and other human service agencies such as low-income health clinics, senior’s service agencies, and CDCs. These placements complement the physical redevelopment activities and are generally concentrated in the same 150-block LeDroit Park Initiative impact area. In addition, over 3000 Howard University students have, through service-learning courses, engaged in similar community activities between 1998 and 2005. Direct service programs through HUCUP’s Community Technology Center have trained over 220 community residents in Microsoft Office, leading to promotions and job placements for over two-thirds of these participants, while small business support has been provided in the community to over 2,500 aspiring

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entrepreneurs and current small business owners. Intensive internship placements in CDCs for 40 undergraduate students minoring in community development has similarly fostered this partnership and complemented the brick-and-mortar activities, while approximately 100 families have been assisted in literacy, job-skill acquisition, and family strengthening through the Even Start Family Literacy Program. Yet these activities have only begun to tap the wealth of faculty and student resources, as well as the leveraging capability of the university as a major corporation, to enhance the university–community partnership. To more fully implement the knowledge development, integration, communication, and application process, a portal linking many facets of the university’s intellectual resources to the community was needed. The Howard University Community Technology Center is working through its CIC to achieve that end. While still in its infancy, this initiative shows great promise to complement the many historic and current community programs with a portal leading into the core strengths of the university.

The Howard University Community Technology Center The digital divide emerged in the 1990s as a major social issue. Access to information technology (IT) was clearly lacking in minority communities, creating a major disparity as the society computerized many forms of information and services. Many federal, state, local, and private programs were undertaken to establish community technology centers, most prominently through the U.S. Department of Education but supported as well by other federal agencies and by many selfinterested IT firms. Such centers were only marginally effective in solving the digital divide problem, since access alone turned out to be merely the opening challenge. Convenience of in-house computers vs. laboratories (even in the community), and orientation, instruction, and maintenance turned out to be larger problems. Staffing of computer laboratories remains thin, and in many cases equipment is present but virtually nonoperational. Among the important early steps toward realizing a Du Bois/Dutch science shop model for university–community relations at Howard was the establishment of the Howard University Community Technology Center in 1998. It offered computer instructions to residents of Howard’s neighboring communities. The laboratories have been operated by full-time staff complemented by student volunteers and part-time tech workers, including student participants from the engineering school’s TORCH program. Such computer literacy is an important first step on the path to helping Howard’s neighbors carry out their own research to solve their problems. The Howard University Community Technology Center has two main community-based computer laboratories and several other minor laboratories.21 Users include workforce development participants seeking to improve their basic computer skills for job advancement, elders seeking means of better communication with their families and methods for finding credible medical information in a private setting, and youth engaged in website design and academic reinforcement programs.

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The Howard University Census Information Center (HUCIC) The HUCIC, sponsored by the Census Bureau (Census), is a particularly useful research component of the CTC for the embrace of community partners. The Census has a history of challenged relationships with minority communities, in terms of both its recruitment of personnel and its relationship to the user community. The Census created minority advisory panels and convened them regularly, but often did not respond to their recommendations in a way that the advisory committee members and leaders found to be effective. Howard University has also had awkward and unproductive experiences with the agency as well.22 The bureau nevertheless has continued to engage minority communities, in part because maximum support of such communities is vital to the ability of the Census to secure an accurate population count in the decennial census, and in part because Census leaders believe it is the right thing to do. An important step in this process occurred with the development of the Census information Centers (CIC) program. This program represented an effort to channel important census data to communities of color that did not have good access to the Census’s state data centers. Howard University was pleased to join this group, and placed its CIC in HUCUP’s Community Technology Center. Yet, the process of joining the CIC network demanded some persistence and insistence on the part of the HUCUP. Initially, the Census opened these centers only to a selected group of civic and community service associations and excluded universities, even HBCUs. Although university professors were substantially engaged in the advisory process from the start, the inclusion of academic organizations was seen as a valuable asset only after an initial phase. Now, of course, the mutual benefits are clear for both higher education partners and the Census. The approach of the HUCIC is to make available, in readily usable form, census data and products to the network of partnerships that has emerged through the last decade of Howard University’s community engagement. The Census provides a wide range of data for public use, but for many prospective users they are inaccessible. A user has to learn census terminology, such as consolidated metropolitan statistical area (CMSA), metropolitan statistical area (MSA), incorporated places, Census designated places (CDP), Census tracts, block groups, and blocks. Some of these geographic definitions change from one Census to another. For instance, recently the Census replaced primary statistical area (PMSA) and CMSA with core-based statistical area (CBSA). Many geographic units are defined by their economic fuctions, i.e labor markets, housing markets, population aggregates, and population densities. CBSA, MSA, PMSA, and CBSA are created to address such economic functions. The census bureau also defines some geographic units called places, which are related to political definitions of geography; places cover municipalities, for instance. Similarly, certain census indices and variables are designed to address different concerns or issues raised by social scientists of different disciplines. These data go far beyond the original mandate of the census to count the population to define congressional district boundaries. Understanding this bewildering array of data requires both community translation and Census literacy. The simple version of addressing this problem is to have a community-accessible workstation with part-time staffing for community uses. One of the first major projects conducted by the Howard University CIC was a

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baseline evaluation of a program with youth centers in five cities, including the District of Columbia.23 Although this project engaged university researchers with key community residents, it did not achieve the goal of making census data more available for the use of the community. Accordingly, the HUCIC developed a multistage process to improve this capacity. The first step was to engage students in service-learning projects in courses that can use census data. In the course The Economics of Black Community Development, for example, each student prepared a paper relevant to a particular city that included common tables on racial disparities, as evidenced by cited census documents. These reports were then compiled into a notebook on racial disparities for community use at the HUCIC. Similarly, three instructional modules to teach spatial analysis and visualization of quantitative data using geographic information systems (GIS) were developed for both students and community members, allowing them to learn how to map these data as well. Participants learned to perform the following tasks by downloading the modules and following the step-bystep instructions to complete each one using Arc view®GIS software: ● ●

● ●

Creating maps by using the existing data sets Creating data sets for Arc view® by downloading shape files from the census bureau website and connecting them with other census data, mainly drawn from Summary File 3 Geocoding, i.e., representing addresses as points on the maps Creating maps with more than two variables or data layers.

Equipped with modern spatial analysis tools, students and community members can use public and private data sources more effectively in analysis and advocacy efforts. Participant evaluations have indicated that the modules provided a good understanding of data sources, Arc view®GIS software, and methods of using both for exploratory research purposes in identifying local needs and challenges. Political science courses also use the HUCIC to study electoral redistricting issues. Political science students are encouraged to examine the neighborhood impact of national and local policy initiatives using the American Community Survey data. The HUCIC staff guide students and community partners through the Census’s American FactFinder database as part of these endeavors. All of these projects, while using very simple census tabulations and basic GIS, are intended to whet the appetite of students and community partners for comprehensive data analysis of their communities. In addition to the national census-based products and the products that the HUCIC develops itself, additional databases are made available through the HUCIC to community partners. These databases include such resources as the Annie E. Casey Foundation’s 10-indicator-based Kids Count database at (www.kidscount.org); the NeighborhoodInfo DC website maintained by the Urban Institute and Washington, DC LISC (originally developed by now-defunct DC Agenda), which contains community indicators related to population, housing, race, poverty, gender, and youth at the ward, neighborhood, and tract level (www.NeighborhoodInfoDC.org); and the National Center for Healthy Housing’s Lead Safe Homes site (www.leadsafe homes.info). Virtually all of these research organizations use census data, shape files, and geographic boundary definitions for their own data so that a reasonable mapping

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solution can be found for most tabulations. This multifaceted approach of blending Howard University students and faculty with the staff of the CTC which houses the HUCIC allows the university–community partners to fulfill the CIC mission, and to integrate, communicate, and apply knowledge including community indicators to address community challenges.

Conclusion The HUCUP and its Census Information Center are taking important steps in achieving the goals of university–community partnership that harken back to Seth Low of Columbia and W.E.B Du Bois. Universities increasingly are taking on the partnership role through service learning and community-based research at the student and faculty levels, and direct partnership at the administrative levels. With support from federal, state, and municipal agencies, the New American University of Ernest Boyer, where knowledge is not only discovered but also integrated, communicated, and applied, can be achieved, and the dreams of Du Bois—that HBCUs can become centers of education and uplift for the entire community—can be fulfilled. The model proposed in this chapter requires a broad university partnership as its foundation with substantial trust developed over many years. Building this foundation and then creating a physical portal to university research resources can augment the educational and development missions of both universities and their surrounding communities.

Notes 1. For discussion of these trends, see Harkavy and Puckett (1995, pp. 299–321) and Harkavy (1992, pp. 1–9, 17–19). 2. See Elfenbein (1996). The quoted phrases are from the Christian Advocate (1889) and a letter, Glenn to Gilman (1888). 3. Harkavy and Puckett (1995, pp. 299–321); Addams (1930, p. 405), cited in Costin (1983, p. 45). 4. For a fuller exposition of the diversity, challenges, and social commitment of HBCUs, see Thompson (1973) and Bullock (1967). 5. See Du Bois (1990 [orig. 1903]) and Du Bois ((1973 [orig. 1946]), pp. 139–148). 6. In contrast, at Howard University, the university’s approach to the community has been egalitarian, cooperative, and two-way, recognizing the wisdom that resides in the community’s own experience. Howard University’s Senior Vice President for government affairs, Dr. Hassan Minor; has suggested that the exchange of information between university and community should be two-way rather than one-way (Minor to Verharen (2000). 7. See Du Bois (1990 [orig. 1903]) and Du Bois ((1973 [orig. 1946]), pp. 139–148). 8. PDR (1999, p. 14). 9. See Kleinman (1997), Roush (1996), Sclove (1997), and Von Schomberg (1998). 10. Harkavy (1992) contains the fullest review of these efforts. For more information on such efforts, see PDR (1996) and PDR (1998). 11. See Harkavy and Puckett (1995), for a discussion of the initiatives of Jane Addams and her colleagues at the University of Chicago. 12. Harris (1971) presents this general case for a limited outreach and development role for HBCUs, asserting that HBCUs have done far less than white schools in serving community needs. Booker T. Washington decried the strapped financial conditions of

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HBCUs in 1911 (1995, pp. 434–435) while Daniel Thompson presented essentially the same detailed complaint over 60 years later (1972, pp. 245–254). Similar debates over the resource challenges for HBCUs are found in Butler (1997), Jencks and Reisman (1967), Jones (1971) long (1972), McGrath (1965), Moton 1983, Bowles and De Costa (1971) and, most recently, Roach (1999) and SEEDCO (2001). See, for example, Fleming (1978) and Morris (1979). The interconnection of phenomena creating and reinforcing urban black poverty is quite complex and beyond the scope of this research project. For some useful comments on these areas, see Teitz and Chapple (1998); the essays in Boston and Ross (1997); Halpern (1995); Green and Reidy (1992); and Green and James (1993). The data on these efforts remains sketchy, although some compiled information may be gleaned from CPD (1996) and SEEDCO (1996). Anecdotal evidence abounds; see, for example, Stanley (2001). Two efforts to gather existing data on community development activities of HBCUs include CAPD (1999), which has a broad-spectrum goal, and Roper (2001), which focuses on community development training programs. Universities also impact the local communities around them by creating demand for local goods and services and by hiring locally. For example, University of Illinois at Chicago is the largest employer in the city, and Howard University is among the top employers in Washington, DC. One way that community-conscious universities have tried to positively affect their local communities is through preferential contracting arrangements with local firms and encouraging local businesses in other ways. Such programs are beyond the scope of the present reflection. Myrdal’s work was heavily informed by Howard University scholars including Ralph Bunche and E. Franklin Frazier. The urgency of this new path was brought home to the new special assistant to the president, Dr. Hassan Minor, shortly after his arrival. ACORN staged a sit-in at his office demanding that the university take the boards off its residential properties and return them to the community, while community meetings at the Florida Avenue Baptist Church and the Bruce Monroe Elementary School similarly reminded the Howard administration of the seriousness of the town/gown division. No amount of recalling past glories in the civil rights movement could counteract the anger of neighborhood residents denouncing “you people on the hill” as their neighborhood suffered from the impact of deteriorated, vacant, university-owned housing in their midst. The Clinton Walk occurred in 1992, shortly before President Bill Clinton’s inauguration. Clinton toured the distressed neighborhoods on George Avenue near Howard University; this symbolic action was thought to be a harbinger of revitalization, in parallel to the Kennedy Walk on Pennsylvania Avenue in the early 1960s. The Kennedy Walk was followed by the creation of the Pennsylvania Avenue Development Corporation, which remade Pennsylvania Avenue in line with Kennedy’s vision. The LeDroit Park Initiative is a program of redevelopment for a 150-block area surrounding the central campus of Howard University in Washington, DC. With the work of Fannie Mae, the initiative began with the rehabilitation of 28 existing vacant residential properties and the in-fill new construction of an additional 12 units, all of which were owned by the university and sold to its employees and members of the communityat-large. A housing assistance program was developed that made down payment and closing cost assistance available to university employees and community members. Infrastructure improvements involving street resurfacing, lighting, planting, and trafficcalming measures are taking place in partnership with the DC Department of Public Works, based on a streetscape redesign sponsored by the Fannie Mae Foundation. Using funding from the HBCU program of the U.S. Department of Housing and Urban Development, HUCUP and HUCA worked in partnership with two area CDCs to

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rehabilitate another 30 units of housing in the same neighborhood. The initiative is now expanding to include an additional 300 units of market rate housing; the development of a grocery outlet; and the provision of a parking facility for 400–500 cars. These developments will take place across the street from the Howard University Hospital. In addition, the initiative envisions the development of a cultural district that will be anchored by a mixed use development which could include a cultural/art use. At the southern end of its campus near the historic Howard Theater, a national historic landmark that would be restored and preserved. This area is also the eastern end of the city’s Uptown Arts District, once known as the old Black Broadway. 21. A related step toward realizing the Howard University model was the establishment of the Howard University Mini Medical School (HUMMS). The HUMMS offers seven lectures per semester to community members interested in consumer health care information. The lectures have been offered at the Louis Stokes Health Sciences Library and the Howard University Center for Continuing Education in Silver Spring via teleconference. HUMMS started in the Fall 2003 and all the lectures are archived on the HUMMS website: www.minimed.howard.edu. This project is linked to the CTC as well. HUMMS participants are offered the opportunity to take basic and advanced computer instruction at the Howard University Community Technology Center in order to help them use the Internet for additional self-directed health care information. HUMMS plans include teleconferencing the lectures to HBCU medical schools including Drew and Meharry as well as undergraduate schools including Xavier University in New Orleans, teleconferencing with universities in South Africa and Ghana and developing a mini medical school program tailored for District of Columbia high schools. Its objective is to provide consumer health care information to District students and to encourage them to consider careers as health care professionals. 22. Howard University succeeded in breaking into the inner circle of research contractors for the 2000 census in 1996 in the areas of Statistical Analysis and Minorities and Special Populations, based on an open competition. Task orders were to be issued to the members of the successful circle of contractors at the discretion of individual offices within the Census. After the competition, the census changed contracting rules by requiring that each task order be competed, putting the university into competition with major consulting firms with resource levels much higher than that of the university, guaranteeing that Howard University would only rarely be able to compete effectively despite its designation as a fully competent agency to conduct research for the Census. As of 2005, Howard University received only one minor task order (which no other contractor desired) despite numerous quality responses. 23. For a description of these activities, see Green and Daniel (2001) and Rolark (2003, pp. 10–14).

References Addams, J. (1930). The Second Twenty Years at Hull House: September 1909 to September 1929, with a Record of a Growing World Consciousness. New York: Macmillan. Bender, T. (1987). The New York Intellect: A History of Intellectual Life in New York City, from 1750 to the Beginnings of our Time. Baltimore, MD: Johns Hopkins Press. Boston, T.D. and Ross, C.L. (1997). The Inner City: Urban Poverty and Economic Development in the Next Century. New Brunswick, NJ: Transaction Publishers. Bowles, F. and De Costa, F.A. (1971). Between Two Worlds: A Profile of Negro Higher Education. New York: McGraw-Hill. Boyer, E. (1994). Creating the new American college. Chronicle of Higher Education, March 9, A48.

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Bullock, H.A. (1967). A History of Negro Education in the South. Cambridge, MA: Harvard University Press. Bulmer, M. (1984). The Chicago School: Institutionalization, Diversity, and the Rise of Sociological Research. Chicago, IL: University of Chicago Press. Butler, A. (1977). The Distinctive Black College: Talledega, Tuskegee, and Morehouse. Metuchen, NJ: Scarecrow Press. Center for Assessment and Policy Development (CAPD) (1999). Building the Knowledge Base on HBCU/Community Partnerships: A Concept Paper. Bala Cynwyd, PA: CAPD. Christian Advocate, New York, April 18, 1889. Community Planning and Development, U.S. HUD (CPD) (1996). Expanding the Role of Historically Black Colleges and Universities in Community and Economic Development. Conference Package. Atlanta, GA: Clark Atlanta University. Costin, L.B. (1983). Two Sisters for Social Justice: A Biography of Grace and Edith Abbott. Urbana, IL: University of Illinois Press. Degan, M.J. (1988). Jane Addams and the Men of the Chicago school, 1892–1908. New Brunswick, NJ: Transaction Publishers. Diner, S.J. (1980). A City and Its Universities: Public Policy on Chicago, 1892–1919. Chapel Hill, NC: University of North Carolina Press. Du Bois, W.E.B. (1990 [orig. 1903]). The Souls of Black Folk. New York: Vintage Books. Du Bois, W.E.B. (1973 [orig. 1946]). The Function and Future of the Private Negro College. In Aptheker, H. (ed.), The Education of Black People: Ten Critiques, 1906–1960. New York: Monthly Review Press. Elfenbein, J. (1996). To “fit them for their fight with the world”: the Baltimore YMCA and the making of a modern city, 1852–1932. Ph.D. dissertation, University of Delaware UMI #9703949. Ann Arbor, MI: UMI. Fitzpatrick, E. (1990). Endless Crusade: Women Social Scientists and Progressive Reform. New York: Oxford University Press. Fleming, J. (1978). The Lengthening Shadow of Slavery: A Historical Justification for Affirmative Action for Blacks in Higher Education. Washington, DC: Howard University Press. Glenn, J. to Gilman, D.C. (1888). Gilman Papers, MS. 1 Ferdinand Hamburger, Jr. Archives. Baltimore, MD: Johns Hopkins University, 13 July. Green, R.D. and Daniel, J. (2001). The 2001 Baseline Assessment of the Violence-Free Zone Initiative. Washington, DC: National Center for Neighborhood Enterprise. Green, R.D. and James, D.M. (1993). Is job accessibility a serious problem for AfricanAmericans? Review of Radical Political Economics, 25(3):78–89. Green, R.D. and Reidy, J.P. (1992). Accumulation, urban segregation, and the Black role in the U.S. economy: A stylized history. Review of Radical Political Economics, 24(2):83–90. Halpern, R. (1995). Rebuilding the Inner City. New York: Columbia University Press. Harris, P.R. (1971). The Negro college and its community. Daedalus, 100(3):720–731. Harkavy, I. (1992). The university and social sciences in the social order: An historical overview and “where do we go from here?” Virginia Social Science Journal, 27:1–25. Harkavy, I. and Puckett, J.P. (1995). Lessons from Hull House for the contemporary urban university. Social Science Review, 68:299–321. Jencks, C. and Reisman, D. (1967). The American Negro college. Harvard Educational Review, 37(1):3–60. Jones, M.H. (1971). The responsibility of the Black college to the Black community. Daedalus, 100(3):732–744. Kleinman, D.L. (ed.) (1997). Science, Technology and Democracy. Cambridge, MA: MIT Press. Long, H. (1972). The future of private black colleges. The Enquirer, February 5. Philadelphia, PA.

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McGrath, E.J. (1965). The Predominantly Negro Colleges and Universities in Transition. New York: Bureau of Publications, Columbia University. Minor, H. to Verharen, C. (2000). Personal communication. June 16. Morris, L. (1979). Elusive Equality. Washington, DC: Howard University Press. Moton, C.L. (1983). Public service activities of predominantly black colleges and universities. Ph.D. dissertation. UMI No. 8321453. Ann Arbor, MI: UMI. Policy Development and Research (PDR), U.S. HUD (1996). University–Community Partnerships: Current Practices, Volume II. Rockville, MD: HUD USER. Policy Development and Research (PDR) (1998). Colleges and Communities: Partners in Urban Revitalization. Rockville, MD: HUD USER. Policy Development and Research (PDR) (1999). University–Community Partnerships in America: Current Practices, Volume III. Rockville, MD: HUD USER. Policy Development and Research (PDR) (2003). Minority-Serving Institutions of Higher Education: Developing Partnerships to Revitalize Communities. Washington, DC: U.S. Department of Housing and Urban Development. Roach, R. (1999). Black college enterprise. Black Issues in Higher Education, 16(8):22–27. Rolark, S.J. (2003). Using Census Data to Help Local Communities: Census Information Centers at Work. Washington, DC: U.S. Department of Commerce, U.S. Census Bureau. Roper, R. (2001). An Overview of Community Development leadership Training Programs and Lessons Learned from selected collage and Universities. NY: SEEDCO. Roush, W. (1996). U.S. joins a “science shop” movement. Science, 273(2):572–573. Sclove, R.E. (1997). Democracy and Technology. New York: Penguin Books. Structured Employment Economic Development Corporation (SEEDCO) (1996). Request for Proposals to Establish Community Development Leadership Programs at HBCUs. New York: SEEDCO. Structured Employment Economic Development Corporation (SEEDCO) (2001). Reflections on HBCU-Led Community Development. New York: SEEDCO. Stanley, F. (2001). Town and gown: LeDroit Park and Howard University. Marketwise No.1 Richmond, VA: Federal Reserve Bank. Teitz, M.B. and Chapple, K. (1998). The causes of inner-city poverty: Eight hypotheses in search of reality. Cityscape, 3(3):33–70. Thompson, D.C. (1973). Private Black Colleges at the Crossroads. Westport, CT: Greenwood Press. Von Schomberg, R. (ed.) (1998). Democratising Technology: Theory and Practice of a Deliberative Technology Policy. New York: Free Press. Washington, B.T. (1995 [orig. 1911]). The mistakes and the future of Negro education. In Brotz, H. (ed.), African American Social and Political Thought, 1850–1920. New Brunswick, NJ: Transaction Publishers.

RODNEY D. GREEN, Executive Director, Center for Urban Progress, Howard University, [email protected] MAYBELLE TAYLOR BENNETT, Director, Howard University Community Association HAYDAR KURBAN, Assistant Professor of Economics, Howard University LORENZO MORRIS, Professor and Chair, Political Science Department, Howard University CHARLES C. VERHAREN, Professor, Philosophy Department, Howard University

Quality Indicators for Progress: A Guide to Community Quality-of-Life Assessments1 MARIAN CHAMBERS1 AND DAVID SWAIN2 1

Executive Director, Jacksonville Community Council Inc. Professional Staff, Jacksonville Community Council Inc.

2

Interpretive Introduction by David Swain By 1993, 8 years after the Jacksonville Community Council Inc. (JCCI) had begun its community quality-of-life (QOL) indicators project, the project staff was regularly receiving requests for information and guidance from those seeking to develop similar projects in other communities. Jacksonville’s pioneering efforts were rapidly becoming recognized and respected around the United States and the world as an exemplary model for others to follow. In response to a perceived need as well as opportunity, JCCI staff set about writing a how-to manual suitable for use by other communities seeking to emulate the Jacksonville model. The primary author was Marian Chambers, JCCI’s executive director, assisted by community planner David Swain and communications director Barbara Wainwright. The result was a loose-leaf, tabbed document, copyrighted in 1994, designed for active use by community groups involved in planning their own indicators projects. To recover its substantial up-front costs, JCCI charged a hefty price for what it marketed as a “replication kit.” Initially, the kit sold well, but, over the years, demand waned as other similar manuals became available, reflecting the remarkable growth of the community indicators “movement.” JCCI’s manual was never reprinted and was largely forgotten outside of Jacksonville. By 2004, the burgeoning movement had spawned an Internet-based international learning network called the Community Indicators Consortium (CIC). Its education and training committee has refocused attention on the need for both best-practice examples and how-to manual information, and is working toward compiling a critical mass of such examples and information for open-access use via the CIC website (visit the CIC website at www.communityindicators.net). To support this effort, JCCI agreed to relinquish the copyright on its 1994 manual so it could be made available in the public domain, with the stipulation that any use of the contents be accompanied by a full source reference. This action by JCCI has made it possible for the manual to be published in this book. This is not the one and only, end-all manual on how to conduct a community indicators project. More than 20 years after it was written, which represents an aeon in the development of community indicators practice and research, it clearly contains both strengths and weaknesses. Because it describes a pioneering effort, it reflects the absence of other models for the authors to emulate or adapt. Thus, it

267 M. J. Sirgy, D. Rahtz and D. Swain (eds.), Community Quality-of-Life Indicators: Best Cases II, 267–322. © 2006 Springer. Printed in The Netherlands.

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describes the Jacksonville model as “the” way to go rather than one choice among several available alternatives. Clearly the situation is far different today. This does not mean that the manual advocates plug-in adoption of the Jacksonville model by other communities. Rather, it insists that each community engage in creative adaptation, making decisions that mold the model to fit the unique circumstances of each community’s civic culture and QOL values. This remains sage advice today. In hindsight, the JCCI manual’s greatest strength appears to be its steady focus on the people process of creating and managing a community indicators project, with special emphasis on inclusive and active citizen participation. As a generic guide, JCCI’s insights about this people process remain fresh, relevant, and essential after 20 years. Many of its suggestions concerning data collection and management and publication of reports also remain useful, but many others have been overtaken by rapid changes in the computer and telecommunications technology available to support indicators work. Technological capacity itself is a subject barely touched on in the manual. Also lacking is much information about how to use indicators to instigate positive change in the larger context of a community’s QOL improvement process. Finally, many of the specific references and examples throughout the manual have clearly become at least dated and perhaps obsolete. Publishing this manual in this book promises multiple benefits. For some communities, it may still be useful as an overall how-to guide for a specific project. For practitioners and consultants searching comparatively for promising approaches and practical suggestions, it may provide many kernels of useful insight and how-to knowledge. And for researchers, it may provide a clear statement, for use in both applied and theoretical research, of one vision and approach toward how community indicators work can best be accomplished. To learn more about JCCI and its projects, and to peruse its latest annual indicators update report, visit www.jcci.org. Note: The editor has substantially reformatted the manual from its original printed form for presentation here. The how-to content, however, remains the same, nor has it been updated. The most profound politics is that which changes the pictures in our heads, our definitions of the situation. (Walter Lippman)

Introduction Possible Motivations So you would like to monitor and improve the QOL in your community. Perhaps your overall goal is sustainability—the idea that you will ensure that your children and grandchildren will enjoy a QOL at least equal to yours. If this is to occur, you and your generation will have to watch carefully the use of irreplaceable resources. Perhaps you simply want to produce an annual report card that will give you an

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overview of progress. Or perhaps you want the citizens of your community to decide what progress is, and how to achieve it. Maybe your goal is to keep government accountable. Whatever your reasons for undertaking this project, you will need a method for accomplishing your purpose. This manual is designed to help communities adopt a QOL model, and to develop a system for enhancing community progress by monitoring the QOL on an annual basis.

Defining the Quality of Life What, indeed, is the QOL? The phrase has become a cliché that frequently appears in speeches and publications. What exactly does it refer to? Although it is difficult to define, QOL refers to certain accepted standards of human development and progress and our satisfaction with those standards as they affect us. The QOL is comprised of factors that are important to all of us—our family life, the air we breathe, and the satisfaction of basic needs, physiological, psychological, sociological, and political. When we say that we have a good QOL, we mean that we have the opportunity to fulfill most of our basic needs and to reach our full potential as human beings. And, in looking to the future, we may infer the sustainability of this QOL for future generations. QOL can be very subjective and personal. For many of us, the most important part of our QOL is the nature and success of close interpersonal relationships. A honeymoon or a fight with a spouse has a strong influence on our feelings and outlook. Similarly, health is extremely important on a personal level. For example, if you have just suffered an accident that has put you in the hospital, your QOL has probably declined rapidly and dramatically. A loss of a job is equally traumatic. And yet, these examples, which have affected you personally, have not affected the community QOL. What do we mean by the community QOL? When we speak of a “community” QOL, we are speaking of those factors that affect everyone in the community in a general way. Each factor may have a differing degree of impact on each of us, yet most would agree that these factors are important and that the community has a role in maintaining these factors. In examining the QOL from a community perspective, we have to agree at the outset that we will not be able to fully acknowledge the wide range of individual differences.

Quality-of-Life Components Some components of a good QOL may be taken for granted by Americans. Freedom from war has an important impact on our QOL. As such, this is an important factor at the national and international level. A nation at peace sets the stage for stable family life. Other personal freedoms are also an integral part of our life in a democracy. We accept these as “givens.” When these freedoms are not granted equally to all persons, we call this discrimination. At a community level, discrimination can have a strong influence on the QOL. The various parts of the community QOL are interwoven and interdependent. Our country, however, has come to rely almost exclusively on economic indicators

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as measures of human progress. We hear a lot about the gross national product (GNP), as if it were the ultimate measure of progress. In actuality, it is only an economic indicator, and a very blunt instrument at that. The GNP is a measure of development based on per-capita production. Unfortunately, it counts as “progress” such things as the production of guns and weapons, the sales of alcoholic beverages and tobacco, and pollution clean-up efforts while completely overlooking the unpaid labor of housewives, the value of natural resources, and infrastructure. Perhaps our emphasis on economic indicators is related to their ease of development. Economists are used to numbers and measures. Measuring other aspects of human development and behavior is more difficult. No matter how difficult, we need to expand our horizons beyond economics in our consideration of the QOL. The central question should be, how are our people and their environment faring? It is time to look at all of the components of progress and their interrelationships. Our relationships with each other and with the earth profoundly affect our future. Once we have identified the important components of QOL, we can use them to guide our political, social, and business decisions.

Policy-Planning Tool Since a QOL assessment is a policy-planning tool, it makes no sense to measure things we cannot change, like the climate. We are concerned with community progress, in improving our community’s QOL. We are primarily interested in measuring, monitoring, and fostering progress in our community over time, rather than making comparisons with other communities. So this project is different from a comparison of many communities, such as the Places Rated Almanac, where the goal might be to select the most desirable place to live in America. In this project, community values are brought to the table as we decide collectively what constitutes progress. These values add subjectivity and relevance to our numbers and measures. The resulting tool thus uniquely belongs to our community.

How a Quality-of-Life Report Can be Done An annual QOL report contains a collection of indicators of progress within nine categories of the QOL. The product results from a combination of credible research skills and the art of effective citizen participation. Collaboration in a cooperative way between paid staff and volunteers makes this possible. 1. Once a source of funding and an organizational sponsor are identified, agreement is reached about the various elements that make up the community QOL. 2. The JCCI model includes nine elements; indicators, or measures, are selected to cover the major dimensions of each element: (i) Economy (ii) Education (iii) Public safety

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Health Natural environment Social environment Politics/government Mobility Culture/recreation

These indicators are compiled every year to show trends. 3. The annual report card demonstrates community progress as well as problems that need attention. 4. A refinement of this report card adds targets for each indicator for a future year. Thus the community decides where it wants to be, how high it can aspire. This addition helps to put the trends into perspective. However, the selection of targets can best be accomplished after 6–8 years or 6 years of annual reports. 5. In another refinement of the basic report card, citizens establish priorities among the indicators and elements of the QOL. They select the most important indicator within each element or category, and finally, they rank the elements themselves. Priorities help a community to decide how to focus its energies and resources.

Summary of Activities Involved in Conducting a Quality-of-Life Project 1. Hold a feasibility meeting with a broad range of representatives of community groups and leaders. 2. Find an organizational sponsor and funding source. 3. Select a chairperson and a steering committee. The steering committee will guide the process. Each member of the steering committee will chair one of the nine task forces for each element of the QOL. 4. Hold four to five meetings of the steering committee to make key early decisions. 5. Recruit task force members. Members of the nine task forces will select indicators for a particular element and will choose a top priority indicator for that element. 6. Convene task forces to select indicators and establish priorities. Each task force will hold four meetings. 7. Steering committee accepts and coordinates task force reports. 8. Steering committee and task forces set overall priorities. 9. Conduct telephone survey (optional). 10. Staff gathers data and compiles indicators. 11. Publish and distribute report. 12. Stimulate use of report and citizen action. 13. Plan for annual compilation of data and review process. You can’t hit a home run unless you step up to the plate. You can’t catch fish unless you put your line in the waters. You can’t reach your goals if you don’t try. (Kathy Seligman)

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Getting Started: Finding a Sponsoring Organization and Funding Sources One way to get started is to hold a feasibility meeting with community leaders from the public, private, and voluntary sectors. Ask a prominent local leader to conduct the meeting. Explain the QOL project and why it is important for your community. Ask for reactions from those present. Such a meeting will help you to identify sources of support and enthusiasm for the project. It may also make you aware of other community efforts that might in some way conflict with this project. You will be more likely to have success if you present the project in a way that does not threaten existing community values. Each community will be different in this regard, with some more progressive in their ideas than others. If you have already had a number of discussions with individuals and representatives of organizations, and have received positive reactions and substantial enthusiasm for the project, a feasibility meeting may not be needed. In that case, you may want to begin by looking for a sponsoring organization and funding sources. In your community, it is possible that the funding source and organizational sponsor may be one and the same.

Sponsoring Organization Every community will need an organizational sponsor. The sponsor will orchestrate and coordinate the project, administer the funds, and provide the staff support. Who can carry out this task for your community? You will need some sort of ongoing organization to help you. The organization should: ● ● ●

● ● ● ●

have a professional staff, skilled in research be stable and able to commit to performing on an annual basis be skilled in working with volunteers (or be able to partner with such an organization) be highly regarded as objective and fair be able to identify and recruit volunteers from all walks of life be able to commit a project coordinator and support staff to the project have a mission that is compatible with the project Here are some examples of organizations that might be well qualified:

●

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A local or regional planning council (This could be a government-sponsored council with primary interest in land-use planning or a private nonprofit council with primary interest in human services.) A citizens’ league (Citizens’ leagues, which operate in about two-dozen communities, are concerned with involving citizens in the public life of the community. Public policy issues comprise their agendas. Their membership is diverse.) A community college A public university, most particularly a department of urban studies The planning department of city or county government A chamber of commerce

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A newspaper A community foundation A hospital (particularly one that participates in the healthy communities program) A junior league A council of churches A research institute

Do not overlook the possibility of a joint venture between a research organization and a citizen-participation organization.

Funding Sources Who will fund such a project?Funding sources will vary in different communities. Since this is a community project, a diversity of funding sources is desirable. A partnership of multiple funders may work best in terms of buy-in as well as funding. Some organizations (foundations, for example) are well suited to start-up funding, while others prefer annual funding. Here is a list to draw upon: Local community foundation. Community foundations are governed by a community board. They are often skilled at convening diverse groups and certainly interested in the overall health of the community. Locally based private foundation. Private foundations are most likely to grant funds within their own geographical area. Often they are interested in providing start-up funds for 1–3 years, with plans for the community to take over the funding after that. City, county, or state government. Government often has an interest in measuring progress. Government officials are in an optimum position to make use of an instrument of progress, as they develop budgets and priorities. Chamber of Commerce. Chambers of Commerce have a primary interest in economic development. Today most chambers recognize that economic development cannot succeed without other QOL factors. Recently, Standard & Poor’s and Moodys have added QOL factors to their bond ratings. Newspaper. Newspapers have an interest in community progress. A QOL assessment would be a widely used reference for reporters and a source of many news stories. Private for-profit corporation. With an interest in the QOL. High-tech companies. They are usually very sensitive to QOL issues. Junior League. Local United Way. Although most united ways limit their areas of fund distribution to human services, they often produce environmental scans as the first step in a strategic planning process. At least two united ways have recently provided funding for QOL projects. Hospitals, health-planning councils, or other health consortia. In the last few years, many in the health professions have recognized the concept of health as more than physical and mental health, and inclusive of other QOL aspects. Thus, the environment, economics, family life, housing, and other factors can be seen as an integral part of community health. In recognition of this concept, the

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National Civic League and the U.S. Public Health Service have been working with a number of communities to develop a “healthy communities” approach. The Health Care Forum, a California-based foundation, is encouraging a systems approach and plans to apply its approach soon in five communities. The QOL-monitoring tool provides a useful way of measuring progress in communities involved in such efforts. If your city has been involved in the healthy communities project, you may find that the local group will be interested in your project, and possibly be of great help. It is also possible that they may already have developed a similar project of their own. In-kind contributions. Although you may find one or two main funding sources, you may also find it possible to fund separate pieces of the project separately, such as a telephone survey, printing, or loaned staff. A telephone survey. If you have difficulty in finding indicators for some of the important aspects of QOL, you may wish to collect information on citizen perceptions, knowledge, or reported behaviors via a telephone survey. If so, you will also want to seek possible sources of funding for the survey work, such as: ● ● ●

Marketing research companies Telephone companies Universities or colleges

Stability over the years is important here. You will want to ensure that the basic research methodology remains the same. Printing. Often an in-kind donation of printing can be obtained from private companies. Try to identify those companies that traditionally provide such services for nonprofit organizations. You will often see acknowledgments of such printing on the back of newsletters or other publications. This kind of recognition can be a motivator for providing the funding. Loaned staff. Perhaps a local college or university will be able to lend a staff member to the project. Other possibilities are corporations that may have a slack period in the year. Once you have identified the organization(s) that will conduct this process, and probable funding source(s), you are ready to begin.

Early Decisions and Options*** In the planning stages of your QOL project, a number of key decisions will have to be made. Therefore, it is a good idea to assemble a leadership group, known as a steering committee, to guide the process from beginning to end. Assembling the steering committee is one of several topics covered under the section “Citizen Participation.” Early decisions for the steering committee include: Finding an organization that will conduct the process Identifying and securing funding sources

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Adopting a QOL model Deciding on geographical boundaries Adopting criteria for the selection of indicators Determining the optimal number of indicators Considering a telephone survey of the public Establishing priorities Setting targets Developing a budget If you have not yet identified the organization(s) that will conduct this process and probable funding sources, these tasks should be the first consideration of the steering committee.

Adopting a Quality-of-Life Model Should you copy the overall JCCI model of the QOL with nine elements or develop your own? The JCCI model identified nine elements of the QOL: 1. 2. 3. 4. 5. 6. 7. 8. 9.

Education Economy Public safety Health Social environment Natural environment Government/politics Recreation/culture Mobility

As more and more communities assess their QOL, it will be interesting to trade comparable data. If comparisons are appropriate, they can lend greater perspective to the work. For this reason, it makes sense to stick with the nine elements of the Jacksonville model. Yet this is a question your group must consider, in light of your uniqueness. Your steering committee and, ultimately, your community must buy into your design if it is to be effective. Clearly, there are many ways of arranging the same material and none are either right or wrong. Some communities may feel that housing merits a separate category, while others will be content to include housing issues under the economic environment or the social environment. Many communities have developed vision statements or goals. In some communities where growth management plans are mandated, required elements are listed. A review of many of these plans and visions demonstrates more commonalities than differences. In Phoenix, for example, the elements that were derived from a community vision process were: 1. Community 2. Education 3. Economy

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Basic human needs Natural environment and resources Urban form Transportation and communication Arts, culture, and recreation Governance

Social Indicators III, published by the Bureau of the Census in 1980, divides its concerns into 11 sections: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

Population and the family Health and nutrition Housing and the environment Transportation Public Safety Education and training Work Social Security and welfare Income and productivity Social participation Culture, leisure, and use of time

Use your own best judgment. You may either start with the Jacksonville elements and model or you may wish to develop your own. If you wish to start from scratch, you can obtain citizen input in many ways— responses to public service announcements, responses to newspaper survey questions, focus groups, etc. Perhaps a vision statement or goals already developed by your community can give you some ideas.

Deciding on Geographical Boundaries What geographical area do you plan to cover? The answer may be partially dictated by the sponsoring organization and its mandates, or by various funders and their constraints. In general, however, your project will be more easily accomplished if you limit your geographical coverage, for several reasons. The “average” problem. One problem in doing a community QOL assessment is that gathering data at a large community or regional level tends to mask neighborhood-level differences, many of which are significant. For example, air pollution may be at an acceptable level at the monitoring stations, but may be unacceptable in a low-income part of the community. Averages, by definition, mask differences. As the story goes, you can have one foot in ice water that is freezing and the other in boiling water that is scalding you—yet on the average the water temperature is comfortable. So, as you move in size from town to city to county to region, this “average” problem will only get worse. Availability of data. You may find that most of the data you will be seeking is compiled at the city level. If you extend your boundaries to the county, you will have to collect the data from each town and city within the county. Not only does

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this make extra work and therefore extra costs for you—you may also find that the data are not available from small towns within the county, or that the collection and compilation methods vary, making it very difficult to obtain comparable data. If you collect data for one indicator from a number of sources, you will have decisions to make in compiling it. Can you average it all together? Will some sort of weighting be necessary? Meaningful impact. Residents tend to identify most strongly with the smallest unit of government. They feel that therein lies their best chance for making a difference. So citizen involvement may be easier to achieve if you “think small.” Remember, the ultimate outcome of a QOL assessment is improving your community.

Adopting Criteria for the Selection of Indicators A decision on criteria will have to be made early in the project and will apply to indicators for all elements. Suggested criteria are listed and discussed under the section “Selecting Indicators”.

Determining the Optimal Number of Indicators Within each element or category of your QOL model, you must identify a number of measures that can be expressed in numbers. These statistics are called indicators. Indicators are pieces of information that reflect the status of important problems or issues. By looking at a small piece of the picture, an indicator, you may get a better glimpse of the big picture. Tracking indicators over time is one way of measuring progress. Remember that indicators are just that—signals, signposts that tell you something important, but not everything that you would like to know. How many indicators should you have? There is a trade-off in limiting the number of indicators. Too many indicators may be bewildering and confusing to comprehend. Yet too few indicators may fail to give you a representative picture of the element. Since few indicators will perfectly fit all your criteria, you will find a tendency to expand the number of indicators, hoping that the various biases and caveats will balance each other. Remember, however, that as you expand the number of indicators that you are going to track, you also expand the costs and time involved. In the JCCI model, participants agreed to limit indicators to a maximum of ten for each element. You will find that it will be easier to generate indicators for some elements. For example, in Florida, education will produce many indicators because school districts are usually required to collect substantial statistical data for reports to the state. Measurements for the arts, by contrast, may be much harder to find. At any rate, you should design a balanced product with relatively equal numbers of indicators for each element.

Considering a Telephone Survey of the Public The major reason for doing a telephone survey is to provide data for indicators that you consider important and for which no other source is available. The telephone survey gives you the opportunity to ask questions about perceptions, behaviors, or events.

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Telephone surveys are expensive, however, and require a certain technical expertise. Unless your sponsoring organization has the expertise, funding, and ability to perform a telephone survey, you will have to seek other sources. If you are fortunate enough to obtain an in-kind contribution of this service, the survey can be invaluable in filling out some gaps in your indicators. Since people are growing more and more reluctant to respond to surveys, you should strive to keep your survey short and to the point. Be miserly, and use survey questions to develop indicators only when no other source is available and only when the indicator or what you want to measure is very important. One method of limiting the number of survey questions is to allow only one survey question for each element of the QOL. Although the use of a telephone survey should be discussed in the planning stages of the project, because of its impact on the budget, you may delay a decision until the search for indicators is well under way.

Establishing Priorities Although all elements of the QOL are important, not all can be addressed effectively at the same time. Some will be seen as more important than others. A citizen consensus of the relative importance of the elements will be helpful when hard community choices have to be made about the allocation of limited resources. Similarly, within each element, not all indicators will be viewed as equal in importance. By selecting and highlighting the most important indicator, citizens may help to focus community action. Perhaps your community has recently developed a community vision or set community goals. In that case, you may wish to use those existing priorities. If several years have elapsed, however, this priority exercise could be a useful reality check. If you have already established broad community goals, you may want to find indicators related to each goal, insofar as is possible.

Setting Targets At JCCI, we set targets for each indicator 6 years after the inception of our project. We did this in an effort to improve our product. Since we had decided not to compare ourselves with others, we had to find a way of putting the data into perspective. Yes, a reader could see that if the infant mortality dropped from ten to eight, this was a progress. But what should the rate of progress be? What should the infant mortality rate be? Setting a target for each indicator meant quantifying citizen aspirations of progress by the year 2000. Although targets could be chosen in the first year of a QOL project, it would be very difficult. For many of the indicators, trends and history form the major basis for selection of the target. So if you have little trend information, you may have no basis for the target. Therefore, we recommend that you wait until you have published at least six annual reports before setting targets. Regardless of what you decide, you must decide it before the citizen task forces begin their work. Setting targets will lengthen the time line considerably and increase the budget.

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Developing a Budget You can expect to spend between $25,000 and $50,000 on the first year of your project. The number of citizen participants will directly influence the costs of copying materials and the costs of meetings. After the first year, the citizen-participation part will be limited to a brief review process by a small committee. At that point, the major costs will be that of staff time in collecting, compiling, and presenting the data, as well as printing costs. Here are the basic items to be included in a first-year budget: Income Major funding sources In-kind printing In-kind telephone survey Expenditures Staff salaries and benefits Overhead (occupancy, telephone, computers, equipment) Copying costs, printing Staff salaries and benefits will be your major cost. It will be difficult to reduce these costs except through the use of loaned staff or student interns. As discussed earlier, a telephone survey will add a substantial amount to your costs, unless an in-kind donation is obtained. Overhead costs will vary according to the sponsoring organization. Printing costs will vary, depending on the kinds of documents to be published, the numbers printed, the quality of the printing and paper, the length of the documents, and again, the availability of in-kind contributions. JCCI publishes two documents each year, one for the general public and one for planners and researchers. We reasoned that the public simply wants a quick overview, whereas planners and researchers want the back-up information, such as the source of each indicator and the mathematics performed. Since the reference document is necessarily large, we felt that we could not afford to print many of them, nor would the average reader be likely to pick one up. If you find that you can publish only one document, we would recommend the one for the general public. You can keep the information contained in the larger document in your files, to be supplied on an ad hoc basis in response to requests. Although a decision on document number, size, and quality does not have to be made early in the life of the project, it will affect the budget. Tell me, I’ll forget. Show me, I may remember, But involve me, and I’ll understand. (Old Chinese proverb)

Citizen Participation: A Critical Element The Need for Citizen Participation A credible research institute could develop a fine QOL model, select indicators, and publish a document. So why is citizen involvement so important? This is a community project, one which measures progress as defined by the members of

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the community. It is a unique opportunity for members of a community to decide what is important to them and how to achieve progress. Therefore, its usefulness will be a direct reflection of the amount and nature of community involvement in the planning. A major principle of good planning is this: if you want citizen help in implementation, you had better get them involved in the planning process.

How to Plan for Citizen Participation in Your Project Citizen involvement works best under certain conditions, including a clear structure and charge, a flexible time frame, a judicious mix of paid staff and volunteers, and effective meetings. Effective citizen participation requires a good clear structure. Although at first blush it may seem more democratic to let the group decide just about everything, this is definitely not a good idea. Freedom does not result from the absence of all structure, but rather from the presence of a general structure and guidelines, which enable people to work creatively and productively. If people understand initially the boundaries, limitations, and ground rules by which they are operating, their work will be effective and stimulating. Without an adequate structure, groups tend to flounder unproductively and many conclude that they are wasting their time. They may spend their time arguing about what their task really is rather than accomplishing the task. So do not be afraid to start with some givens and guidelines, leaving room for some flexibility as the project proceeds. For example, your group might be asked to consider using the Jacksonville model of nine elements. If the group wants to look at other models or make their own suggestions, then the model can be changed. It could also happen that far into the process the group might want to change one of the elements or combine two. There is no reason why such a request should not receive careful consideration. By proposing a model initially, you will have saved time and helped the group to solidify their thinking. If, on the other hand, you simply asked the group to develop their own model, the lack of clarity and concreteness would cause people to drift and wander. Usually it works best if committees are presented with a draft proposal of a model, no matter how rough or tentative. As long as the leadership makes it clear that the guidelines are flexible, and the group is willing to listen to different points of view, groups usually welcome the structure. The charge to each group or task force should be specific and clear. Each person should understand at the outset what their group is to accomplish, to whom their product is to be delivered, and by what time. A time frame with some flexibility is important. Citizens will want to know how long the project will last. How many meetings will they be expected to attend? What will be expected of them between meetings? Will it be acceptable if they must miss a meeting? What background or skills will they need to bring to the project? How will meetings be conducted? How long will they last? How will decisions be made? Who will compile and distribute meeting summaries? The world must be kept safe for differences. (Clyde Kuckholn)

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Effective Meetings Since much of the planning and original work for this project will be accomplished with the help of volunteer committees, effective meetings are essential. The ingredients of effective meetings include the planning for each meeting, conducting each meeting, group decision-making, and evaluating the meeting. Planning a meeting. In planning a meeting, keep these points in mind: 1. Plan the meeting carefully, with a clear concept of why you are meeting and what goals you want to reach. 2. Remember that the meeting’s membership should be those who can contribute something to the meeting as well as those who can derive something from it. For this project, volunteers usually see the reward as doing something positive for the community, something that will actually make a difference for years to come. Their contributions will vary, from expertise in some of the elements of the model to knowledge of the community and its resources, to research skills, to group process skills. What they will contribute is not as important as their feeling that they are contributing. This feeling must be reinforced by the group climate, which is in large measure determined by the leader. 3. Anticipate hurdles and barriers in advance ... and think of ways to overcome them. 4. Make a checklist as a guide when special arrangements, facilities, audiovisual equipment, or other meeting aids are required. 5. Include information, attached to the agenda, and preferably mailed in advance, that helps members come to the meeting prepared to participate. 6. Plan the meeting schedule for each group at least a month in advance, so that members can clear their calendars and make a commitment to attend. Set a time for beginning and ending and follow those time frames. 7. Find the best meeting site possible. Of course, financial constraints may influence your choice. A meeting site should be centrally located, to be convenient to most participants. It should be easy to locate, with parking easily accessible and at no cost or low cost. If public transportation is widely used in your community, then the site should be close to transit stops. The facility should allow for flexible furniture arrangements, rather than a fixed classroom setting. If possible, arrange for people to sit around tables, so that they have a place to put their papers and refreshments, and can have face-to-face interaction. Always provide flip charts and magic markers. Be sure to send a map and thorough directions to each participant. 8. Try to have the meeting place for each task force remain the same throughout the project. Changing locations invariably leads to confusion and delays in starting times. 9. Assign roles to accomplish your goals. Assign a timekeeper to keep the group on track and to let the group know when it is exceeding its own time schedule.

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Assign someone the task of preparing meeting summaries immediately following the meeting and distributing them. This is preferably a staff role, but can be filled by a competent, willing volunteer, if necessary. Meeting summaries should include the decisions made and the rationale for these decisions plus action steps and assignments to be completed before the next meeting. Agendas. To keep the meeting on track, prepare an agenda, focused on achieving the expected outcomes. Whenever possible, the agenda should be distributed in advance to give committee members time for preparation. The group should give their assent to the agenda at the beginning of the meeting. Allow time to cover all topics. The number of topics should be tailored to fit the available time and they should be related to each other, if possible. The agenda should tell members what is being discussed, why it is being discussed, and what you expect to accomplish. Well-thought-out agendas: Help group members to prepare for the meeting Tend to reduce anxiety by letting members know what will happen Force the leader(s) to plan ahead of time Provide a tool for control of the meeting, in time and content. Conducting the meeting. The way the volunteer leader conducts group meetings has a dramatic impact on committee effectiveness. Steering committee or task force members will watch carefully how the leader operates and will take cues from the leader about the norms of participation within the group. The steering committee or task force chair should give precedence to the members’ ideas. If, as a chair, you begin by presenting your ideas, the committee’s sense of commitment will decrease, their willingness to speak up will decline, and the probability of a productive meeting will lessen. As a leader, you should listen carefully to the members. Permit each member to express any ideas he or she offers. Your aim is to understand that point of view. You may wish to paraphrase a member’s points to be sure that you do understand them and that the person is satisfied with your understanding. Although this sounds easy, in reality it is difficult. You may find yourself distracted by your own thoughts, making judgments, and otherwise failing to comprehend fully what the speaker is saying. The participants should believe that it is your job as leader to understand what they have in mind and to help their thought along. As a leader, you should not allow anyone to be put on the defensive; always assume there is value in any notion a member offers. You should search out the value, no matter how wild or irrelevant the statement may first appear. Try to create an opportunity for involvement by every group member. Groups usually have both talkative and quiet members. You must take care to seek out the ideas of the quiet ones. Through eye contact, polling, and other techniques, encourage the quiet members to participate. Special considerations for the first meeting of a group. At the first meeting of a group, a number of procedural issues should be included on the agenda:

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1. Review and acceptance of the charge or mission 2. Agreement on operating procedures for the group: ● ● ● ● ● ●

● ● ●

● ●

Timing of meetings—begin and end on time Written agendas—who sets, when published, etc. Good participation How decisions will be made Prepare for meetings Attendance (excused absences, handling of latecomers, representative when absent) Minutes and reports Leader role Behavioral norms (listening, avoiding interruptions, giving and receiving feedback, practicing empathy) Guests—how invited, how excused Staff role

Role of staff versus volunteers. Your project is most likely to meet with success if the staff considers the volunteers on the steering committee and task forces as their customers. The staff should try in every way to please those customers. This means taking on all possible chores to take “the pain” out of volunteer jobs and to make participation a real pleasure. Although who does what is not terribly important, it is very important that the delineation of tasks between staff and volunteers is crystal clear. There is room for a lot of give-and-take to meet individual needs. Since volunteers are not paid for their work, they will get their rewards from group interaction, from the feeling that they have made a real contribution, and perhaps from recognition. They, not the staff, should make the major substantive decisions. Staff should be tuned into any perceived “put-downs,” hurt feelings, etc. With close communication between the chair and the staff, such problems can usually be alleviated. Typical staff tasks would be making meeting arrangements, planning an agenda with the chair, and preparing and distributing meeting summaries. Tent style nametags, placed on the tables in front of each participant, will help people to get to know each other. A major staff role in this QOL project is that of compiling the indicators after selection by the task forces. Staff will attempt to collect several years of data, refine the wording of each indicator, and compile the document for a final review by volunteers. Evaluating the meeting: the group process check. The effectiveness of meetings can be measured and improved. We suggest the use of a group process check at the end of every meeting. (A sample of the JCCI group process check is shown in Figure 1.) In this way, you will receive instant feedback from the group on a number of measures of meeting effectiveness: staying on track, participation, listening, leadership, decision quality, and satisfaction. If the group is small (ten or lesser), the scores can be tallied in a few minutes and then discussed. Just make a horizontal mark for each person’s response for

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Circle the number on each dimension which reflects your rating of the group process. 1 2 3 4 5 6 7 8 9 10 ON TRACK NO AGENDA OR

FOLLOWED THE AGENDA

DID NOT

NO DIGRESSIONS

FOLLOW THE AGENDA

COMMENTS: 1 2 3 4 5 6 7 8 9 10 PARTICIPATION A FEW KEY MEMBERS

EVERYONE CONTRIBUTES

DOMINATING AND

AND IS INVOLVED IN

SOME MEMBERS NOT

TEAM DECISIONS

PARTICIPATING

COMMENTS: 1 2 3 4 5 6 7 8 9 10 LISTENING MORE THAN ONE

ONE PERSON TALKS

PERSON TALKS AT A

AT A TIME: CLARIFYING

TIME: REPETITIONS

AND BUILDING OF IDEAS

INTERRUPTIONS, AND SIDE CONVERSATIONS

COMMENTS: 1 2 3 4 5 6 7 8 9 10 LEADERSHIP NO ATTEMPTS TO

CHAIR AND GROUP

BRING THE GROUP

MEMBERS INTERVENE TO

BACK ON TRACK AND

KEEP THE GROUP ON

ENCOURAGE

TRACK AND ACTIVELY

EQUAL PARTICIPATION

MANAGE EQUAL PARTICIPATION

COMMENTS: 1 2 3 4 5 6 7 8 9 10 DECISION QUALITY GROUP DECISIONS

GROUP EXPERTISE AND

WERE INFERIOR TO

DECISIONS WERE

INDIVIDUAL

SUPERIOR TO INDIVIDUAL

ASSESSMENTS

JUDGEMENTS

COMMENTS: 1 2 3 4 5 6 7 8 9 10 SATISFACTION LITTLE SATISFACTION

HIGHLY SATISFYING

ACHIEVED: BORING

AND REWARDING

AND NON-PRODUCTIVE

MEETING

MEETING

COMMENTS:

Fig. 1. Group process check.

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each dimension on a blank group process check sheet. A pattern of frequency distribution will result. From this you can easily calculate the average and the range. The chairman should display the results, and should seek to draw out more information where necessary. This should be done in a nonthreatening way, so that people who do not wish to explain their “vote” will feel secure and will continue to fill out the forms honestly. This feedback and the discussion enables the leadership and the full membership to make changes at the next meeting. It encourages the group members to take responsibility for the meetings and to assist the chair in enabling the meetings to be productive and satisfying. In general, a score of 5 is considered an average score.

Group Decision-Making Many types of decisions will need to be made during a group project. Decisions can be made in a number of ways, ranging from an autocratic style, with the leader unilaterally deciding, to that of group consensus. The four main types of decisionmaking include: 1. Decision by the group leader without receiving input from the group 2. Decision by the group leader, after seeking and taking into account the suggestions of group members 3. Decision by majority vote of the members 4. Decision by consensus Consensus. For citizen-participation projects, consensus is the preferred way for making important decisions that require a high level of commitment and an investment in the outcome. Consensus occurs when each person in the group can say that he or she has had a chance to speak, has spoken, and has been genuinely heard. Consequently, each person has either persuaded the group to his or her way of thinking or has not persuaded the group. Either way, the group’s decision is accepted, possibly with reservation, but always with commitment to the decision, and the implementation of it. Consensus does not equal 100% agreement. One hundred percent agreement is next to impossible, particularly in a community context, given the diversity of backgrounds, cultures, occupations, and viewpoints. However, consensus does equal 100% commitment to decisions. Reaching consensus generally requires devoting more time up front. Each member must actively participate, and the group must give a fair hearing to all major issues raised before making a decision. Consensus decisions inevitably produce a more enthusiastic group effort, and these successful events build trust and goodwill, which sustains the group when difficulties arise. Guidelines for working toward consensus. 1. As a leader, make sure that each person understands and accepts the consensus process. 2. As a group member, present your perspective as lucidly and logically as possible, but listen to the other person’s reactions and consider them carefully before you press your point.

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3. When discussion reaches a stalemate, do not assume that someone must win and someone must lose. Instead look for creative alternatives. 4. Do not change your mind simply in an effort to avoid conflict and to reach agreement. If agreement seems to come too quickly in a diverse group, be suspicious. Authentic agreements result from a full understanding and discussion of various points of view. 5. Avoid simplistic techniques such as majority vote, average, coin-flips, and bargaining. However, particularly in a large group, a straw vote can be an effective way to gauge the sense of the group. That is, the leader may ask for a show of hands in support of a proposal. Following the straw vote, continue the discussion so that all have a chance to state their point of view and to try to persuade the others. 6. When dissenting members finally alter their positions, do not feel that they must be rewarded by having their own way on some later point. 7. Expect and encourage differences of opinion to occur in any diverse group. Disagreements and conflicts can improve the group’s decision. With a wide range of information and opinions, there is a greater chance that the decision will be a good one.

Time Line Your project should take no longer than 1 year from inception to publication date. Allow 2–3 months for obtaining funding and a sponsor, recruiting a chair and a steering committee. Allow a month for the steering committee to make initial decisions and to recruit members of task forces. With nine or more task forces requiring at least four meetings each, at least 36 meetings will be required to accomplish the task of selecting indicators. Although this phase could be accomplished within 6 weeks, theoretically, in actual practice it will be difficult to arrange for good staffing in such a condensed time frame. It is more realistic to allow 3 months for this phase. Each task force should meet biweekly, but the meetings can be staggered. When the work of the task forces is complete, each task force must report back to the steering committee. This can be accomplished in five weekly meetings. Finally, a presentation should be made to the entire group, task forces and steering committee. If you have decided to include priority setting and target setting, the time frame will be much longer (Figure 2).

Organizational Structure A chairperson, a steering committee, a task force for each element of your QOL model, and staff support will be the main actors in your project. Of course, the funding sources and governing body of the sponsoring organization will also play roles (Figure 3). The chairperson will be responsible for the entire project. His or her first task will be that of recruiting members of the steering committee. He or she will chair

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JAN

FEB

MAR

APRIL

MAY

JUNE

JULY

AUG

SEPT

OCT

NOV

DEC

Find a funding source Secure sponsor organization Recruit Chair Steering Committee Recruit task forces Task forces meet Report to steering committee Collect data and prepare report Release report

Fig. 2. Time line for a project.

the meetings of the steering committee, will visit task force meetings as needed, and will chair meetings of task forces and steering committee combined. He or she will be the major spokesperson for the project. The steering committee will be responsible for coordinating the entire project and for recruiting task force members. Each steering committee member will also serve as chair or cochair of a task force. The steering committee will receive and approve the task force reports, and assure coordination of the work of the various task forces. Task force members will select the indicators associated with each element of the QOL. Each task force will decide on the most important indicator of those within the element. The task forces and steering committee together will select the most important element. Recruiting a chairperson. This can be done from many different approaches, depending upon the origins of your project. The chairperson must be someone who is widely respected in the community, someone who is viewed positively by the different ethnic and racial groups. The chairperson should possess good leadership skills and the ability to conduct effective meetings. Be sure that the chairperson understands the length of the commitment—9 months to a year, and the specific roles that he or she is to play. The chair will be expected to play a major role in recruiting the steering committee, attend and lead all (or most) of the meetings of the steering committee, to coordinate and check-in frequently with members of the steering committee, to attend at least several of the task force meetings, and to provide leadership in many other ways.

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Sponsording Organization*

Funding source(s)* •

•

Provides funding for the project

• •

Coordinates entire project Administers funds Provides staff support

Staff

∗ The same organization may both fund and sponsor the project.

•

Coordinates meetings • Prepares meeting summaries • Compiles Indicators

Chair •

Responsible for entire project Recruits steering committee • Serves as project spokerperson •

Steering Commitee •

Serves as chairs of the task forces • Recruits task force members • Reviews task force work One task force each element Task Force

Task Force

Task Force

Task Force

Task Force

Task Force

Task Force

•

Selects indicators Sets priorities among indicators • Sets priorities among elements •

Fig. 3. Organizational chart.

The steering committee Assembling the steering committee. Possible roles of the steering committee are to: Reach agreement on the overall mission of the project Identify funding sources and organizational sponsors, if this has not yet been accomplished Adopt a model of the QOL Decide on the optimal number of indicators

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Consider a telephone survey and the attendant costs Determine the geographic boundaries Adopt criteria for the selection of indicators Serve individually as chairs of the nine (or more) task forces Recruit volunteers for the task forces or determine a method for so doing Activate citizen interest by asking for ideas via the media Receive the task force reports and coordinate their works and results Decide on the format and number of reports Decide on distribution and publicity Composition of the steering committee. The steering committee should include people from a diversity of interests and backgrounds. It should include key community leaders, who are skilled in facilitating group interaction. They should have enthusiasm for the project and be willing to commit for a 9-month period. Gender, racial, and ethnic diversity of the steering committee should reflect the composition of your community. This in no way implies a quota system, but simply a consideration of diversity as an important factor in the make up of the steering committee and task forces. Certain skills and resources are key to the success of the steering committee. However, not every member will possess all of the following skills and abilities: Enthusiasm for the project and the motivation to see it through Leadership skills—the ability to facilitate group interaction and to help the group reach consensus An interest in statistics and general understanding of statistics Representation from the media Key business and education leaders Connections with funding sources Size of the steering committee. The steering committee should be large enough to provide chairs or cochairs for each task force. In the JCCI model, nine elements are included. It is unlikely that you will want more than ten elements, so 11 people for your steering committee should suffice. In some instances, you may find it necessary or desirable to use cochairs for some of the task forces. However, use of cochairs will make additional work for your staff. All decisions and discussions will have to be handled by at least two telephone conversations rather than one. After considering the advantages and disadvantages of cochairs, make your decisions. If cochairs are used, you will obviously need a larger steering committee. Meeting schedules and agendas for the steering committee. The steering committee should plan for at least three meetings before the task forces convene. The exact number of meetings required will depend on the decisions that have been made before the steering committee is assembled. If questions of funding and organizational sponsor have been settled, it should take no more than three meetings to set the stage for task force meetings. Meetings should last no more than an hour and a half. After that, people tire, and decisions are less thoughtful.

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Suggested topics for the first three meetings of the steering committee are given below. Actual agendas should have times assigned to each topic, and a presenter assigned to each topic. The fourth meeting assumes the presence of all task forces. Meeting one Introductions Review purpose of project Review models from other cities Develop a process for deciding on the elements to be used in the model Review time line for project Meeting two Adopt model for the QOL Select or volunteer task force chairs for each element Develop charges and time lines for each task force Develop criteria for task force membership and optimum size of each task force Develop plan for recruiting task force members Meeting three Receive progress reports on task force recruitment Receive reports on task force scheduling Adopt criteria for the selection of indicators Adopt policy on telephone survey Adopt policy on numbers of indicators under each element Meeting four—start-up meeting for all task forces Review purpose Review proposed time lines Review responsibilities of steering committee and charge to task forces Review proposed model Review criteria for selection of indicators Ask for input, ideas, and discussions on all of these Distribute meeting schedules for task forces When the task forces have completed their work, the steering committee will need to hold four to five meetings to receive and approve the indicators as well as provide the necessary coordination. The Task Forces Assembling the task forces. Task force members may be recruited in a variety of ways. If the steering committee has used the media to generate ideas for the project or to generate interest, potential task force members may have emerged from these efforts. If the sponsoring organization is a citizen-participation/ membership organization, it will have access to many volunteers. An open invitation to membership, coupled with selective recruitment, is probably the best approach. The open invitation will ensure that no one is excluded. Through selective recruitment, you may supplement the open enrollment to obtain the skills, expertise, and balance that you need. A request from your mayor or a leading public figure may be a powerful recruitment tool. Neighborhood civic

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associations and recommendations from elected officials about people in their districts can be helpful. Composition of the task forces. When the task force seems to be full, take another look at its composition for balance. It will not be possible to achieve perfect balance in each group. Again, diversity is important. Familiarity and comfort with numbers and statistics can be very helpful. Familiarity with the particular element of the QOL, which that task force will address, is often useful. However, be careful about recruiting the people who are your likely sources of data. They may well have a slanted point of view or a tendency to lead you to indicators that may make their agency or department look good, or that may further a personal agenda. If you believe that this could be a problem, consider inviting these people to make presentations at your meetings as resource persons, rather than as a member of the task-force group. Always strive for a balance between any competing interests of which you are aware. For example, in the task force addressing the economy, you should have not only a business point of view but also that of a homeowner or ordinary citizen. Size of the task forces. There is no magic number. However, 8–15 people make for a good-sized group for discussions and decision-making, assuming the diversity mentioned above. Fewer than eight will not give you the breadth of ideas you seek. A larger group makes for a longer discussion, more difficult decisions, and higher costs for administration. Remember that at any particular meeting you are likely to have 75% attendance and plan accordingly. As an example, if you want a working group of eight, your task force should contain 12 members. You will find that some elements of the QOL will be more popular than others. Task force sign-ups will partially reflect the priorities of your community. You may want to ask people to indicate a first and second choice, so that you can allocate the numbers of participants evenly among the task forces. Meeting schedules and agendas for the task forces. Each task force should plan on four meetings to accomplish the task of selecting indicators. If your steering committee has decided to establish priorities, an additional meeting may be required for each task force to select by consensus the most important indicator under its particular element. Setting targets will require several additional meetings. These meetings are not detailed here, because targets are not recommended for the first year of a project. Meeting one Introductions Overall review of project Review of criteria for selection of indicators Distribute indicators from other places Brainstorming indicators Meeting two Continue brainstorming Evaluate list with a validity check for each possible indicator Discuss possible variations and the best wording for each remaining indicator

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Discuss possible sources of data. If many of the indicators come from one source, the group may want to invite a representative to attend your next meeting as a resource person. Assign a volunteer for each indicator to contact possible sources and bring back information to the next meeting Meeting three Presentations from resource persons Report from volunteers Discussion of approved indicators and those remaining Discussion of need for survey questions Meeting four Review of tentatively approved indicators with a 5-year review of data, if obtainable Review of survey questions, if desired Check all indicators against criteria Select by consensus the most important indicator within the group Each task force will next meet with the steering committee, presenting their indicators. The steering committee should be satisfied that the indicators selected essentially meet the criteria for selection, that the number of indicators presented is acceptable, that the indicators logically fit best under that particular element, and that telephone survey questions (if applicable) meet the guidelines or limits previously set by the steering committee. The steering committee should be able to review two elements at each meeting, for a total of five meetings. Meeting of task forces and steering committee to establish overall priorities Achieving consensus in a large group is not easy. To facilitate consensus around priorities, JCCI used the following techniques before the meeting. Three weeks before the meeting, all participants were sent a ballot. The ballot listed all nine elements and the most important indicator in each element, as selected by each task force. Participants indicated their first, second, and third choices on the ballot, mailing their responses. Votes were weighted to assure a clear distribution, with the number one choice = 3, number two choice = 2, and number three choice = 1. This method gave every participant an opportunity to influence the choices, even if he or she could not attend the meeting. Agenda Three-minute presentation by each task force chair Presentation of results of preliminary ballot Dialogue—opportunity to persuade Final ballot Presentation of results Consensus on interpretation of results Final meeting of steering committee and task forces You may want to have one large celebration meeting, distributing a draft to all, and planning for the public release and distribution.

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She would rather light a candle than curse the darkness. (Spoken of Eleanor Roosevelt by Adlai Stevenson)

Selecting Indicators Within each element of your QOL model, you must identify a number of measures that can be expressed in numbers. These statistics are called indicators. Indicators are pieces of information that reflect the status of important problems or issues. By looking at a small piece of the picture, an indicator, you may better be able to glimpse the big picture. Indicators are one way of measuring whether or not we are making progress. Remember that indicators are just that—signals, signposts that tell you something important, but not everything that you would like to know.

Criteria for Indicators How will you be able to decide how to select the various indicators or measures under each element? How can you judge whether your indicator is a good one? The steering committee must establish criteria for the selection of indicators. After all, you want to be sure that the indicators bear a significant relationship to the QOL. You want to be sure that the data will be available annually. You want to be sure that the data are collected in the same way each year and in a way that makes sense. Since the QOL study is a planning tool, you want to include leading indicators whenever possible. A leading indicator will help you to anticipate a problem or alert you in the early stages of a problem, enabling you to be proactive rather than reactive. The rate of unexcused absences from school among ninth graders might be a leading indicator of the high school dropout rate. A lagging indicator, by contrast, will show up long after a problem has occurred. The suicide rate would be a lagging indicator of mental health. Usually mental health problems continue for some time before suicide occurs. Unfortunately, particularly in the health field, commonly available indicators are lagging indicators, often measured by deaths. Always you will want to search for the very best available indicators. The criteria for the selection of indicators used by the JCCI model and listed below have applicability to any community. Validity. Does the indicator measure a factor that is directly related to the QOL? If the indicator moved, would a diverse group of people agree on how that movement affected the QOL—that is, positively or negatively? If there is considerable disagreement about whether the effect is positive or negative, then you do not have a good indicator. As an example, most people would readily agree that as unemployment decreases, the QOL improves. Hence, this would be a valid indicator. On the other hand, regarding the price of a single-family home, some might argue that as the price goes up, the community is improved. Others might say that the increase in price detracts from the QOL by making homes unaffordable to many. So the price of a single-family home would not be a good indicator.

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In some cases, there seems to be an optimum level for an indicator. Once it moves beyond that level, the QOL no longer continues to improve. For example, in a rural community with a dearth of family care physicians, the number of family practice doctors per 1000 people might be a good indicator initially. However, there could come a time when the optimum number of physicians was reached. Adding more physicians would no longer have a positive impact on the QOL. With this situation, the annual review process should be used to consider carefully when the optimum is reached. At that point, the indicator should be discarded. In some situations, there will be uncertainty about the influence of an indicator. As an example, some of your task force members will probably suggest the divorce rate as an indicator within the social environment. Although a climbing divorce rate is usually considered bad, it is also possible that family life within troubled families might create problems worse than those caused by divorce. Again, if you cannot reach agreement within your diverse group, this is probably not a good indicator. Availability and timeliness. Is the indicator readily available on an annual basis? You will find that some of the indicators you would like to use are not available at all. Others, such as indicators of poverty, may be available only every 10 years via the census. Still others may be collected annually, but there may be a significant time lag before they are made available. Sometimes only provisional data can be included in the annual report, because of your deadlines. In such a case, you may have to include a footnote in the report indicating that the data are provisional, or seek another source, if available. Reliability and stability. Are the statistics compiled in a systematic and fair way that will be repeated every year? When you are collecting data compiled by a small organization, or data not required by an outside source, you might find that the method of collection varies from year to year. Unless the method is standardized and dependable, the indicator will not be a good one. To make a determination, you will have to investigate thoroughly how the data are collected and compiled. Responsiveness. Does the indicator respond quickly and noticeably to real changes? To determine this, you will have to look at historical data and note the trends. Common sense will help here. If you find that the indicator has remained flat over a period of 20 years, you will probably not find it to be useful. Understandability. Is the indicator simple enough to be interpreted readily by the public? Arcane formulae and wordy descriptions will elude and confuse the average reader. Keep it simple. Remember that you will have only a handful of words to describe the indicator, so the sense of it must be self-evident. In some cases, the theoretical foundation and measurement methodology of an indicator will be

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readily understood only by specialists, yet the general public will be able to interpret it. An example is the air quality index. Few citizens understand exactly how it is derived, but the number of days the air quality index is in the good range has meaning for most people. Policy relevance. Does the indicator have relevance for public policy decisions? If not, it is not a good indicator. The weather, average temperatures, or amount of rainfall, for example, are not amenable to human control. Remember that this assessment is a planning tool, designed to influence public policy and community change. Representativeness. Do the indicators as a group cover important dimensions of the element? Examine the entire element and consider at least the major dimensions within the element. For example, within the natural environment, air quality, water quality and quantity, green space, solid waste disposal, energy use, and species habitat are important dimensions of the element. Indicators should be selected for at least several of the important dimensions. Indicators of air quality alone would not be representative of the entire element.

Process for Selecting Indicators The selection of indicators is the most difficult part of this QOL project. You will find that many indicators that you would like to use are not currently being measured, or are not being compiled annually. Often you will find it difficult to persuade the data sources to supply you with the necessary data in a timely fashion. Since this project is longitudinal, you will want to use the same indicators each year, making a minimum number of changes. This fact makes the original selection of indicators of great importance. The process for identifying and selecting indicators consists of a number of steps (The order may vary; you will find your task force moving back and forth among the steps.): Brainstorming all possible ideas Performing an initial validity test on the list Determining availability and reliability and seeking trend information Reviewing indicators from other sources Consulting with local professionals Considering the use of survey questions for some indicators Reviewing all indicators collected and their relevance to the criteria Brainstorming all possible ideas. Task force members should be instructed to contribute any possible idea for an indicator, without prescreening or judging, or worrying about the exact words to use to describe it. The task force leader must ensure that the process is free flowing and creative, and must not allow criticisms, questions, or evaluations at this point. The purpose is to generate a large number of

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ideas. As the ideas are submitted, the leader or assistant should write them on a flip chart (without editing). Performing an initial validity test on the list. As each item is considered, task force members should decide whether, in fact, that indicator is directly related to the QOL. If the indicator moves up or down, would the group agree about the effect on the QOL? If the proposed indicator fails this test, it should be quickly eliminated. Determining availability and reliability, and seeking trend information. After the task force has agreed that the indicator or some variation of it has promise, a task force member or a staff person should agree to contact the likely sources before the next meeting, checking on whether and when the data are available and how they are compiled each year. The task force should be satisfied that the method of compilation is sound and that it will be performed in a consistent manner each year. If the data are available and reliable, the task force member should request data from a 5-year period to present to the committee. This will not be available frequently, but when it is, it provides valuable trend information. Reviewing indicators from other sources. Next the task force may want to review the indicators from Jacksonville and other cities. Again, those that show promise must be tested for validity. Do not, however, limit your choices to those made by others. They may have selected interesting indicators, only to find that no data were available locally. That data, however, may be available in your community. For example, JCCI volunteers wanted an indicator of alcoholism. They thought that they could find data about the consumption of alcoholic beverages. They consulted the state bureau of alcoholic beverage control, which levies taxes on all alcoholic beverages. Much to their disappointment, they found that the State of Florida compiles its data by regions and is not able to break out the figures by county. Eventually they settled on an indicator of the number of cases of cirrhosis of the liver, a disease often caused by alcoholism. However, the lag time between the onset of drinking and death from cirrhosis is so long that this is indeed a lagging indicator. Consulting with local professionals. Some members of the task force itself may be professionals in the field. Others may be invited to speak at a meeting of the task force. Or a member of the task force may a gree to contact professionals for their ideas and make a report back to the task force. A note of caution: A person who works in the area being measured may have some investment in wanting his or her area of work to “look good.” That desire may bias that person’s objectivity. Considering the use of survey questions. If key dimensions of the element have not been covered by the named indicators, task force members should consider whether a telephone survey question could supply a needed indicator. If a telephone survey will be used, then the task force should suggest the question and its

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phrasing. The steering committee or a special group should be assigned the task of coordinating all proposed telephone survey questions. Reviewing all indicators presented and their relevance to the criteria. When the above steps have been completed, the task force should examine all the remaining indicators that have passed the tests. They should consider whether most dimensions of the element have been covered, whether there is duplication, and whether the number of indicators selected is consistent with directions from the steering committee.

Role of Staff Versus Task Force Members Task force members may be assigned tasks outside of the meetings. This is a preferred method of working because it gets the members involved and fully understanding the indicators. In many cases they will find that the desired indicator is not available or not in the form or time frame desired. Although volunteers may become frustrated, by doing the work themselves, they will understand that this is not a matter of the staff always being negative and stating that things cannot be done. The reporting back to the task force by its own members will make the meetings more interesting and productive. Preparing and distributing meeting summaries is a role best undertaken by the staff. This must be accomplished immediately following the meeting and the staff should have the resources to accomplish the printing and mailing in a timely manner. Once the indicators have been selected, it will be the role of the staff to gather all the data and display it numerically and graphically to the task force. Task force members may be enlisted to provide the clout necessary to gain a quick response from the sources. Staff and the task force leader should work together on agendas.

Compiling Indicators As a staff person, once indicators have been selected, a number of major tasks lie ahead of you in compiling the indicators: Defining the method of calculation Determining the year for which data will be collected Finding and checking the data Calculating indicator numbers Addressing data gaps Doing these tasks properly during the initial year of the project is crucial for its ongoing credibility. In subsequent years, you will repeat these tasks annually to reveal QOL trends. If you perform them with clarity, accuracy, and full documentation the first time, the annual updates will be much easier. Continuity and consistency over the years is extremely important.

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Defining the Method of Calculation If the task of defining indicators has been done carefully and completely, the method of calculation for each indicator will have been detailed already. Before plunging into data collection, however, it is wise to review specifically what data are being sought and how they will be used to arrive at the indicator numbers. In particular, it is important to decide what annual figure you will use for each indicator. Choices include at least the following: The total number during the year (e.g., new housing starts) The total number per capita or per other unit of population (e.g., crime rate) The average of numbers throughout the year (e.g., student achievement test score) The number at a representative time during the year (e.g., commercial airline arrivals and departures) The percentage of frequency or occurrence during the year (e.g., percentage compliance with environmental surface-water standards or percentage of voters who vote) Many of the numbers may be raw figures; others may be dollars (e.g., per-capita spending on the arts); still others may be percentages of respondents to a survey question (e.g., percentage of people who report feeling that racism is a serious problem).

Determining the Year for Which Data will be Collected Even after you have clearly defined what numbers you will collect, you must determine the year period or periods for which you will collect them. Consistency is important here because you want, as much as possible, to report the QOL, as expressed by each indicator, for a single annual period. For most data, you may wish to select the calendar year or a particular time during a calendar year. For educational data, you will probably have to use the school year. For financial data, you may have to use fiscal years, which unfortunately may differ among agencies and organizations. You will never be able to collect truly current data, since you must wait for the end of whatever yearlong period(s) you choose. Select the most recent complete year for which data are available, and try to be as consistent among indicators as possible. If you are gathering data for the first time, you may be seeking data for previous years. Often this is difficult, because old numbers may be unavailable or they may be unreliable because of changes from year to year in collection or calculation methods. Check carefully for consistency in the numbers you receive. Do not include any that are not comparable.

Finding and Checking the Data Data may come from a variety of sources, including: Printed documents such as almanacs, yearbooks, census materials, government reports, and public financial statements

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Unpublished data from government agencies or private bodies such as boards of realtors, arts organizations, and human-service agencies Telephone surveys and polls (if indicators are selected that measure public opinions, perceptions, or reported behaviors) Printed documents. Obtaining data from printed documents is pretty straightforward. It is a mistake to assume, however, that the same numbers from the same document for different years are always comparable. Check the definition, method of calculation, and documentation for each number carefully, to make sure that you are getting comparable figures from year to year. It is amazing how frequently changes are made in the way numbers are calculated. For instance, if you are tracking dollars spent by your local government for human services, pay attention to how the government assigns programs to categories. You might find that one year a workforce program is included in the human-services category, but the next year it has been shifted to economic development, making the figures not comparable. You probably would not want to eliminate an indicator when you find such a change in figures, because pretty soon you might have few remaining indicators. But you do need to document each change for yourself and in the report you publish so that actual trends can be distinguished from those resulting from changes in what the indicator measures. You might also want to calculate what the new numbers would be if the old definition or calculating method were used. In the example above, you would want to calculate human services dollars, adding back in the workforce program. That will give you a comparable figure. Unpublished sources. Obtaining data from unpublished sources is more interesting but also more complicated than looking up numbers in the library. The keys to success here are finding the person who actually generates the data you need (not a secretary, supervisor, executive, or public relations person) and establishing a friendly but businesslike working relationship with that person. Your best approach is to share with the number cruncher your understanding of how important his or her numbers are and how interested you are in them. If you are lucky, the same person will still be there—and remember you—the following year when you write or call (or both) seeking the same numbers as last year. Although the personal contacts are valuable, it is equally important to get your figures in writing. The U.S. mail is still quite adequate, but these days faxing is easier and faster, if you have that capability. If you do receive figures by telephone, document the results of the phone call carefully and accurately on paper, including the source and date as well as the numbers. As with document data, it is wise during your personal contacts to make sure the method of calculation has not been changed. If it has, get specific documentation of the change. A particular pitfall in the use of unpublished (and even some published) data is that in some cases they are first released in provisional form and then reissued in corrected, final form, perhaps a year or more later. Examples include vital statistics, such as death rates, and labor-force statistics. To avoid the pitfall of provisional data, you first need to know when you have provisional figures. That requires receiving complete and accurate documentation

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from your source person. Then you need to remember each year to seek corrected, final figures for previous years, at the same time that you are obtaining a provisional figure for the most recent year. Survey data. Obtaining telephone survey data requires lots of money, a generous donation by a marketing research company, or some real expertise in house. In most cases, you would want to consider telephone surveying; it is probably the most cost-effective and accurate way of reaching a random sample of a large community’s population. Survey research is not easy to do well; if important indicators require survey responses, it makes no sense to rely on unreliable or invalid surveying. Careful sampling is crucial. Telephone surveying suffers from a major drawback in this regard—It cannot reach anyone who has no phone. Because of this built-in bias, you should consider using a carefully stratified sample designed to minimize the effect of the bias. This may require ensuring a certain proportion of responses from low-income and perhaps minority populations. If you do not know how to structure a stratified sample, you need to find some expertise to help you with the surveying. Like other kinds of data, you want survey data to be comparable from year to year so that trend lines can be observed. Therefore, it is important to ask the same questions in the same format each year, and to conduct the survey at about the same time of year annually with basically the same methodology. If you decide to use a survey, you should include demographic questions so that you can evaluate responses for differing demographic segments. At a minimum, you may wish to ask about race, gender, age, income, and educational level. Presenting telephone survey indicators creates some confusion with dates. For most number-based indicators, you will be reporting data over a year old. For telephone survey indicators, you may be presenting information obtained quite recently. The only solution to this confusion is to present the dates of all indicators very clearly. Refer to the section “Designing and Using a Telephone Survey,” for additional information on telephone surveys. Even if you check data carefully as you collect it, you may find that further data checking is required. If you have several years of data for an indicator, you may sometimes discover what appears to be an anomaly in the trend line. Do not ignore any such anomaly. It might hint at an inaccurate figure that needs correction or a change in the way a number is being calculated by your source. More importantly, there might be an important and interesting explanation for positive— or negative—shift in a trend line. It is worth contacting your data source, if possible, seeking an explanation that could be included in your published document. Some volunteer participation can be helpful with data checking before you go public with your numbers. An annual QOL review committee can save you from serious embarrassment by perusing the indicators with a fresh eye. It is amazing what anomalies—and sometimes, even errors—they will find that you never saw. You will want to select committee members with care, including not only broad citizen representation but also expertise, especially in data analysis and economics.

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Calculating Indicator Numbers For many indicators, the numbers presented may not be the raw data you have collected; they may consist of calculated figures derived from your data. Two common kinds of calculated indicator numbers are: Numbers presented in relation to population so as to eliminate the effects of population growth (e.g., packs of cigarettes sold per capita) Dollar figures presented in constant dollars so as to eliminate the effect of inflation on the purchasing power of the dollar (e.g., the cost of 1000 kwh of electricity) Of course, these two may be found together in a single indicator (e.g., percapita spending on the arts). Once a decade, fairly reliable population figures become available through the U.S. census. Between censuses, we must rely on estimates, which, unfortunately, are available with varying reliability from many sources. For consistency, you should try to stick with one source of population estimates for all your indicators. Make it as authoritative a source as possible. The best possibility is your state government, which may use estimates of local population in legislated formulas for the distribution of public funds to counties and municipalities. Depending on your indicators, you may need several kinds of demographic information, for instance: Total population for calculating crime rates or death rates Population aged 18 and above for calculating workforce participation Population aged 5 and below for calculating child day-care need Minority population to calculate minority political representation Some of these kinds of numbers are already available, calculated in per-capita form. Crime rates are an example. If you accept these figures, you may inadvertently be introducing inconsistency into your figures because you cannot tell what population estimates were used. It is more accurate to obtain the raw figures (e.g., the number of crimes reported) and do the per-capita calculation yourself, using the population estimate of your choice. Dollar figures must be presented with care for them to have meaning in QOL indicators. Dollar trend lines that have not been adjusted for inflation give the distorted appearance of moving upward more than is accurate in terms of actual buying power. Therefore, dollar figures must be deflated. That is, they must be adjusted so that the figure for each year is presented in terms of the buying power for a single, selected, base year. The most logical choice for a base year is the most recent year. Thus, all dollar figures are presented at nearly current dollar value, making them most meaningful for those seeking to understand the indicator. The down side of this choice is that all dollar figures have to be recalculated each year using new deflator factors. The most authoritative and readily available source of deflator factors is the Economic Report of the President, which is published in January each year. You could rely on the Consumer Price Index as your only deflator factor. However, not all aspects of the economy react to inflation in the same way as consumer prices. So, depending on what indicators have been selected, you might need to use other factors. Figure 4

Table B-3. —Implicit prue deflatori for grass domestic product 1959–92 [Index numbers, 1987–100, escape as spied, quarterly data seasonally adjusted] Personal consumptions expenditures

Fund investment Nonresidential

Year of quarter

Gross Total domestic product

Durable goods

Nondurable goods

1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1982 1983 1984 1985 1986 1987 1988 1989 II III IV 1990 II III IV 1991 II III IV 1992 II III

25.6 26.0 26.3 26.9 27.2 27.7 28.4 29.4 30.3 31.0 33.4 35.2 37.1 38.8 41.3 44.9 49.2 52.3 55.9 60.3 65.5 71.7 78.9 83.8 87.2 91.0 94.4 96.9 100.0 103.9 108.5 113.2 117.8 85.0 88.4 92.3 95.5 98.0 101.2 105.5 106.9 108.1 109.1 110.1 111.3 112.6 113.9 115.0 116.5 117.5 118.7 118.9 119.8 120.6 121.2

37.4 37.7 38.3 38.1 39.1 40.4 40.6 41.3 42.3 43.9 45.2 46.4 48.3 49.2 50.3 54.1 59.2 52.4 65.2 69.1 74.1 40.9 86.4 90.1 92.4 93.9 95.4 96.3 100.0 102.0 104.2 105.7 107.6 90.6 93.3 94.4 95.9 97.1 101.0 101.1 103.6 104.0 104.5 104.5 105.4 105.5 105.4 106.1 106.1 107.3 108.0 104.3 108.6 109.4 109.1

28.6 29.1 29.3 29.4 30.1 30.5 31.1 32.2 32.9 34.3 35.9 37.7 39.0 40.4 43.7 50.1 54.2 58.4 59.8 54.1 71.1 79.4 85.7 88.6 90.8 93.4 95.9 96.1 100.0 103.7 109.3 115.9 120.1 89.4 91.8 94.2 97.0 96.3 101.5 105.6 107.0 109.5 109.9 110.8 113.3 114.3 115.6 119.3 113.4 119.9 120.2 120.8 121.4 127.2 122.9

IV IV IV IV IV IV IV I

I

I

I

27.0 27.5 27.7 28.2 28.6 29.1 29.7 30.6 31.4 32.7 34.1 35.6 37.4 38.8 41.0 45.2 48.9 51.8 55.4 59.4 64.7 71.4 77.8 82.2 86.2 89.6 93.1 96.0 100.0 104.2 109.3 115.0 120.0 83.8 87.6 90.7 94.6 97.0 101.6 106.1 107.4 108.9 109.8 111.0 112.7 114.6 115.7 117.6 118.6 119.5 120.4 121.4 122.3 173.4 123.8

Services

23.2 23.9 24.4 24.8 25.2 25.6 28.1 26.9 27.8 29.0 30.2 31.9 33.8 35.3 36.5 39.7 43.0 46.2 50.0 54.0 54.3 64.4 70.9 76.7 81.9 86.2 90.8 95.7 100.0 105.1 110.6 116.7 122.8 89.0 83.7 87.3 92.5 97.1 101.3 107.1 108.6 109.9 111.2 112.7 114.2 115.8 117.6 119.3 120.4 122.1 123.4 124.7 126.1 127.4 127.7

Total

Total

26.4 26.7 26.6 26.8 26.8 27.1 27.9 29.1 30.1 31.4 33.3 34.9 36.8 38.1 40.7 45.2 51.3 54.5 58.9 64.3 71.2 79.2 87.8 93.1 92.8 93.9 95.7 97.6 100.0 103.2 105.9 108.7 109.1 93.1 92.9 94.8 96.1 98.6 101.0 104.4 105.1 105.7 106.2 106.1 107.5 102.8 108.7 108.3 109.4 109.3 109.1 106.6 104.3 108.4 108.0

28.1 28.4 28.2 28.6 28.9 29.2 29.6 30.5 31.5 32.9 34.7 36.5 39.0 40.5 42.0 46.4 53.3 56.9 61.3 66.5 72.7 40.8 90.1 95.3 95.1 95.7 96.6 98.4 100.0 102.8 105.2 107.3 108.2 95.3 95.0 96.4 97.3 99.2 100.7 104.0 104.4 104.8 105.5 106.0 106.5 106.8 107.8 104.2 108.7 104.5 104.0 107.4 107.1 106.9 106.0

Fig. 4. Table B3.

Structures Producers durable equipment 24.4 24.2 24.0 24.1 24.4 24.7 25.4 26.3 27.2 28.6 30.5 32.7 35.2 37.6 40.7 46.3 52.0 54.7 59.2 65.2 72.5 80.8 92.5 98.6 95.5 96.1 98.0 98.5 100.0 104.6 108.9 112.3 114.3 97.5 95.1 97.2 98.5 98.8 101.2 106.3 107.4 108.6 109.3 110.1 111.2 111.9 112.7 113.3 113.9 114.2 114.8 114.4 113.9 114.2 114.9

31.2 32.1 32.2 32.4 32.6 32.8 32.9 33.6 34.7 36.0 37.7 39.4 41.7 42.2 42.7 46.5 54.1 58.2 62.4 67.2 72.9 50.9 88.5 93.0 94.1 95.4 95.7 98.4 100.0 101.9 103.4 104.9 105.4 93.8 94.9 96.0 96.5 99.5 100.5 102.8 103.0 103.1 103.6 103.5 104.1 104.3 105.3 105.2 106.2 105.8 104.9 104.5 104.2 103.9 107.5

Resi dential

23.9 24.0 24.0 24.0 23.8 24.1 24.9 25.9 26.9 28.4 30.4 21.4 33.2 35.2 38.3 42.4 46.6 49.6 54.6 61.3 68.0 74.8 80.9 85.2 87.3 89.7 92.0 95.8 100.0 104.2 107.8 110.7 111.8 86.0 88.0 96.7 93.1 97.3 101.5 105.3 106.5 107.3 108.2 104.8 110.2 110.6 111.1 111.0 111.3 111.6 112.5 111.8 111.7 112.3 113.4

Table B-3 Implicit prue deflatori for gross domestic product 1959–92 Continued [Index numbers, 1987–100 escape as noted quarterly data seasonally adjusted] Exports and imports of goods and services

Government purchases Federal

Year of quarter

1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1982 1983 1984 1985 1986 1987 1988 1989 II III IV 1990 II III IV 1991 II III IV 1992 II III a

IV IV IV IV IV IV IV I

I

I

I

Exports

Imports

Total

Total

28.0 28.6 29.0 28.9 28.9 29.1 30.0 31.0 31.8 32.3 33.3 35.3 36.6 38.1 43.6 53.0 58.5 61.2 64.3 68.9 78.0 87.1 92.9 95.2 96.8 98.9 97.7 96.9 100.0 105.3 107.7 109.2 110.9 94.3 98.2 98.7 97.7 97.4 101.6 106.6 107.8 107.5 107.6 107.4 108.2 108.2 109.3 110.9 111.1 110.9 110.7 111.0 111.1 111.0 111.0

23.4 23.8 23.8 23.7 24.3 24.9 25.3 25.8 26.0 26.2 26.7 28.4 30.0 32.2 37.3 53.5 58.5 60.5 66.4 70.7 83.1 101.4 104.5 99.7 95.9 94.7 91.9 91.2 100.0 105.1 107.8 111.4 110.5 98.5 95.4 93.6 94.2 93.6 102.6 106.0 107.6 108.8 106.9 107.7 109.8 108.0 111.4 116.5 112.8 110.1 109.3 109.8 108.4 109.1 107.4

20.4 20.9 21.3 22.3 22.8 23.4 24.0 25.0 26.3 27.9 29.6 31.9 34.4 37.0 40.0 44.0 48.4 51.8 55.4 59.6 65.1 72.0 78.1 84.0 87.7 91.4 95.0 97.4 100.0 103.6 107.8 112.2 115.9 85.8 87.5 92.3 96.2 98.3 100.9 104.3 106.1 107.5 108.4 109.0 110.6 111.1 112.7 114.1 115.1 116.4 116.3 116.9 117.7 118.7 119.7

21.5 21.3 21.7 27.0 23.3 23.9 24.6 25.5 26.5 28.1 29.6 31.8 34.4 37.6 40.9 44.8 49.3 57.6 56.2 60.4 68.0 73.4 81.4 8.1 91.0 91.9 96.9 98.6 100.0 102.8 106.8 111.2 115.2 89.0 89.9 95.0 98.1 98.8 100.2 103.6 106.0 106.6 106.8 107.3 109.6 110.1 111.7 113.2 114.5 114.3 115.5 116.6 118.6 119.3 120.0

Rational Nondefense defense

36.9 40.5 44.5 48.5 51.9 55.6 59.8 65.8 73.5 81.1 87.6 91.6 94.8 97.3 98.6 100.0 101.0 106.6 110.8 114.5 89.6 91.7 95.5 98.7 98.7 100.3 103.9 106.1 106.4 106.4 107.5 109.4 109.7 111.2 113.1 113.9 113.3 117.6 116.2 118.1 118.9 119.5

39.3 41.9 45.5 51.2 54.1 57.7 61.7 66.4 73.3 82.1 85.9 89.8 91.3 95.7 98.6 100.0 101.4 106.6 112.0 117.1 87.7 84.3 93.3 96.4 99.2 100.1 102.6 105.8 107.1 107.8 108.4 110.4 111.2 113.2 113.3 116.2 116.8 116.8 112.6 119.8 120.3 121.0

State and local

29.9 20.4 20.9 21.3 22.3 22.8 23.5 24.6 26.1 27.7 29.6 32.1 34.4 36.5 39.4 43.5 47.9 51.2 54.9 59.1 64.5 71.1 76.7 81.7 85.2 89.4 93.4 96.4 100.0 104.3 107.3 112.9 116.4 83.4 86.4 90.9 94.8 97.8 101.5 105.7 107.2 108.2 108.0 109.9 111.2 112.1 113.4 114.1 115.5 116.1 118.36 117.1 117.1 118.1 118.7

Final sales of domestic product

Gross domestic but licenses period

25.6 26.0 26.2 26.8 27.2 27.7 28.3 29.3 30.2 31.7 33.3 35.2 37.1 38.8 41.2 44.9 49.2 52.2 55.7 60.1 65.4 71.8 78.7 83.8 87.4 90.8 94.3 96.9 100.0 103.9 108.6 113.2 117.8 85.2 88.6 92.1 95.5 97.9 101.3 105.6 106.9 108.1 109.0 110.0 111.3 112.6 113.9 115.1 116.4 117.8 118.0 118.9 119.8 120.2 121.2

25.4 25.4 26.0 26.6 27.0 27.5 28.2 29.2 30.0 31.4 33.0 34.7 36.7 38.4 40.8 44.9 49.2 52.3 56.1 60.5 66.0 72.7 79.7 84.1 87.5 90.9 93.9 96.5 100.0 103.9 108.5 113.4 117.7 85.3 88.4 91.9 95.1 97.5 101.4 105.5 106.9 108.2 109.0 110.0 111.5 112.5 114.0 115.7 116.6 117.3 7.4 118.7 119.5 120.3 120.0

Percent change from preferring GDP implicit price 2.8 1.6 1.2 2.3 1.1 1.6 2.5 3.5 3.1 5.0 5.0 5.4 5.4 4.6 6.4 8.7 9.6 6.3 6.9 7.9 8.6 9.5 10.0 6.2 4.1 4.4 3.7 2.6 3.2 3.9 4.4 4.3 4.1

5.4 4.6 3.8 3.7 4.4 4.8 4.7 3.9 5.3 3.5 2.4 3.8 2.1 2.0

factors receipts and payments of factor from or to rest of the world Gross domestic product (GDP) less exports of goods and services plus imports of goods and services Quarterly changes are at annual rates Note—Separate deflates are not calculated for gross private domestic investment change in business advantages and net exports of goods and services Source: Department of Commerce, Bureau of Economic Analysis

b c

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(a display of Table B3 in the 1993 Economic Report, pp. 352–353) shows several different “implicit price deflators” which may be useful: Personal consumption expenditures—Total: for indicators related to personal income and spending Personal consumption expenditures—Services: for indicators related to service industries, tourism for example Fixed investment—Total: for indicators related to real estate values and real property investment Fixed investment—Residential: for indicators related to housing costs Government purchases—State and local: for indicators of local governmental expenditures etc. Table B3 from the 1993 Economic Report is reproduced as Figure 4. As you can see from Table B3, the federal government is using 1987 as its base year, meaning that $1.00 is worth $1.00 for that year. In order to change the base year to the year of your choice, you must solve the following equation, for each year for which you have data (X = the deflator factor for the year desired, adjusted to your base year): Economic Report figure for year desired =X Economic Report figure for base year For example, if you are using the total personal consumption expenditures column in the Economic Report, your base year is 1991, and you want to calculate the implicit price deflator for 1988, the equation would be as follows:

106.1 = X = 0.874 121.4 Note that for recent years, only seasonally adjusted, quarterly deflator figures are reported. These should be used, rather than the annual figures, both because they are the only figures available for recent years and because they are more accurate. Once you have developed a table of deflators with your own base year, you will need to apply these deflators to all dollar figures in your indicators. The equation you should use is as follows (X = the deflated dollar figure):

Actual dollar figure for a particular year =X Proper deflator figure for that year For example, if you are tracking an indicator of average public-school teacher salaries and the average salary in school year 1987–1988 was $27,000, you would compute the deflated salary for base year 1991 as follows, using the deflator calculated in the example above:

$27, 000 = X = $30, 892 0.874 In your written document, you may wish to show both actual and deflated dollar figures, especially in graphic form. Such a graph can clearly demonstrate the misleading dimensions of price and cost increases caused by inflation alone.

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Addressing Data Gaps You may encounter situations where data for an indicator are not available for a particular year. If the problem becomes repetitive, you may have to consider removing the indicator. However, if the gap is only an aberration, the indicator can still be used, but you should document the gap. As you report the figures, an N/A for not available may be sufficient, along with an explanation of the reason for the gap. If you graph the trend lines, make sure the line is broken where the break occurs. Some computerized graphics programs simply draw a straight line through the gap if you do not tell them otherwise.

Considering the Compilation of an Index You may be tempted to create an overall index, a number that represents the entire QOL. It would be fun to be able to say, “Last year our QOL was 78, and this year it has risen to 86.” By all means, resist such an impulse. Remember that one major problem with the use of the GNP is misinterpretation or lack of understanding of what it includes and excludes and what it actually tell us. Think about the Dow Jones index. Frequently, people believe that it will tell you how stocks in general are doing. Actually, it tells you how a very limited number of stocks in the industrial category are doing. Whenever you aggregate your data into one number, you will inevitably lose the detail and accuracy that you need. Remember that deciding which indicators are more important is a subjective, value-laden decision. Let it remain so. Let your numbers reflect exactly what each is intended to reflect.

Interpreting the Data Remember that you will need years of data points before you can draw any conclusions about whether statistically significant changes have actually occurred. Remember also that the indicators will not tell you why a change has occurred. You or your audience will have to pursue many leads in attempting to suggest the factors that may have brought about the changes. Be very cautious in your interpretations and speculations, lest you damage the credibility of your entire product. There is one person that is wiser than anybody, and that is everybody. (Talleyrand)

Designing and Using a Telephone Survey The purpose of the telephone survey is to provide data for indicators viewed as important, but for which no data are currently available in your community. Questions may be related to citizen perceptions, reported behaviors, or reported events. By surveying a scientific random sample of the population, one can infer that the answers approximate those of the entire population, within some margin of error.

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Methodology Populus Research, the company that conducted the telephone survey for JCCI in 1993, used a stratified sample designed to ensure an accurate representation of the population, geographically and by race and gender. Two key questions must be answered in determining the size of the sample: 1. How small do we want the margin of error to be? 2. How much confidence do we want to place in the interval between the estimate and the reality? For the JCCI survey, the desired margin of error was set at ±5% points with a confidence level of 95%. One might say, for example, that “48 ± 5% of households think that the QOL in Jacksonville is good” with 95% confidence. That is, if the survey were conducted 100 times, the result would be the same 95 times. In Jacksonville, for a population of 693,546, at least 384 calls needed to be completed, according to standard formulas for determining sample size.

Determining Questions and Writing a Script Your steering committee will have set a limit on the total number of indicators to be determined by survey questions. The JCCI survey uses 11 questions for indicators and five demographic questions. Once you have decided on the information you want and the number of indicators involved, you can proceed. Here are some things to consider as you write the script, including the survey questions: Give a great deal of thought to your indicator and the question. Remember, you will want to ask the same questions every year. Phrase the questions carefully, working backward from the indicator to the question that will bring you those results. Check other survey research performed in your area. Someone may already be asking your question every year. Order the questions so that those that are less personal and threatening are used at the beginning. Be sure to ask for demographic information. You will be interested in knowing this information, even if you are not going to report it. Try to keep your interview short and simple. Many people today are refusing to participate in surveys. If yours is long, you may lose your respondent in the middle of the interview. Although it is certainly possible for volunteers to make the telephone calls, someone will need to train and supervise volunteers carefully for the sake of accuracy and reliability. Ideally, responses should be recorded directly on a computer, thus saving hours of manual work. If your organization decides to do the telephone survey itself, and has not done this before, by all means consult professionals for advice.

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The survey questions used by JCCI can be found in the appendix of Life in Jacksonville: Quality Indicators for Progress.

Establishing Priorities Rationale for Establishing Priorities Establishing priorities will enhance your annual report card for the following reasons: Your indicators, which may number as many as 75, are clearly not equal in importance. Your elements or categories of the QOL may be valued differently by different people. A reader may have difficulty in establishing meaning because of the sheer number of indicators. The use of numbers may lead the reader to believe that the QOL is objective, simply because it is quantifiable. Establishing priorities will contribute the subjective values of citizens in a direct and open way. A community, or even an organization, cannot address all problems or concerns at once. Priorities tend to focus energies and resources. Elected officials usually find that community needs and desires for services outstrip available resources. Citizen priorities give guidance to elected officials as they decide on the allocation of resources among the many needs.

Method for Establishing Priorities: Selecting the most important indicator within each element: Each task force decides by consensus on the most important indicator within that particular element. This can be accomplished during the task force’s final meeting. Selecting the top three elements, along with their top indicators: The entire group (all task forces plus steering committee) holds a final meeting to establish priorities. A preliminary, mailed ballot gives all a chance to participate. At the meeting, task force chairs each make a brief presentation, attempting to persuade the group that their element, along with its top indicator, is the most important one. A thorough discussion and debate follows. The results of the preliminary, mailed ballot are displayed. Written ballots are distributed, asking members to indicate a first, second, and third choice. Votes are weighted, with number one = 3, number two = 2, and number three = 1, to achieve clear separation. Results are again displayed. Participants discuss the results and decide on the best interpretation and whether another ballot is necessary. In Jacksonville, participants agreed that education was by far the top priority. Below education was a grouping of five elements, with little separation between them. The participants agreed by consensus to keep this grouping, rather than try to force a selection of the top three (Figure 5).

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Shaping Jacksonville's Future

TOP PRIORITTES FOR COMMUNITY ACTION BALLOT DIRECTIONS: Listed below are the indicators chosen by the nine task forces as the most important within each element. Your task is to help select the top priorities for community action in the next decade. Please vote for your top three choices. #1 indicates your top choice, #2 your second choice, and #3 your third choice Economy: New Jobs Created Public Safety: Perception of Neighborhood Safety Health: Infant Mortality Education: High School Graduation Rate Natural Environment: Air Quality Mobility: Commuting Time Government/Politics: Perception of Government Leadership Social Environment: Perception of Racial Harmony Culture/Recreation: Local Government Support of the Arts

Fig. 5. Sample ballot.

Displaying Priorities in the Report Priorities are displayed in the report in the following ways: Within each element, the top priority indicator appears first, and is highlighted to indicate its status. Elements are listed in order of priority, with the top element highlighted and noted.

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Optional Your community may have recently developed a community vision and prioritized community goals. In that case, you may choose to use those existing priorities. If you have already established broad community goals, as you search for indicators you may want to find indicators related to each goal, insofar as is possible. Unless we change our direction, we are likely to end up where we are heading. (Old Chinese proverb)

Setting Targets Rationale for Setting Targets Tracking trends is meaningful if a community is concerned about its QOL. Yet you may soon realize that an important ingredient is missing. Once indicators are observed for a few years at particular levels and trend lines are seen to be moving in positive or negative directions, questions start to emerge. Is the level of this indicator good or bad? If its trend line is moving in a positive direction, are we still a long way from where we should be? If it is moving in a negative direction, should we worry a lot or a little?

Comparison Data Insufficient One way to put indicators into context is to provide comparison data. Unfortunately, this is very difficult because communities are unique in their demographics, forms of government, and community values. Even if they are similar, localities tend to measure similar trends in dissimilar ways. For instance, two city governments may report expenditures for a category called human services, but the specific services provided by each city may differ substantially. Even comparisons of data as seemingly uniform as the “uniform crime statistics” can be misleading because of differing crime reporting practices among police departments. Some useful comparable data at the state and federal level are available, and you may wish judiciously to include some of these in the explanatory information you provide with certain indicators. If you choose to include comparative data, be certain to document each item as thoroughly as possible, including the geographic area to which it applies and the date of its origin.

Community Aspirations More significant than comparison data might be your community’s own judgments of where each trend line should (as opposed to will or might) be at some date in the future. A major enhancement of a QOL project might well be the addition of targets for each of the indicators. A target is simply a number that expresses the community’s aspirations for a certain future date for that particular indicator. With targets in place, observers of your community’s QOL would be

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able not only to watch the trends but also to evaluate their movement in relation to these fixed targets. To be credible and accepted, targets must be the product of a broad-based community consensus. As with the process of identifying indicators at the beginning, a process of selecting targets must include widespread citizen participation. Targets need to be selected with care, beginning with agreement on the criteria for selection. In general, the target will be most satisfying if it reflects a truly desirable level or condition for the indicator. However, it will be most useful for achieving actual QOL improvements if it appears to be realistic and feasible within the time available before the target date. The trick for each volunteer task force will be to establish an acceptable balance between desirability and feasibility for each indicator, while perhaps stretching a bit toward the desirable so as to sustain people’s idealism about improving the community.

Staff Research Needed Volunteer task force members will need guidance in order to make informed target choices. A good deal of staff research will be required to provide the necessary information. Several kinds of information should be provided, as available: Comparison data from similar communities, other states, and the nation, where available Information about any comparable targets, goals, or standards set in other communities, states, and the nation Graphs with projections of indicator trend lines displaying both past experience and alternative futures based on differing assumptions about the degree of improvement to be achieved by the target date. If comparison data are available, use them, but stress the necessary caveat about the limited accuracy of comparisons. Flawed comparison data may be more useful than no data at all in helping to gain a perspective on a desirable and realistic target. If targets or goals set elsewhere can be found, these may be very useful. As with comparison data, it is important to document what the goal is, to what jurisdiction it applies, and the target date for accomplishment. Discovery of goals from elsewhere should not necessarily lead to their acceptance for your community. The task force members will still need to make their own judgments about the desirability and feasibility of each goal for your community. Some goals and standards are set by private advocacy and professional groups. For example, advocates of local law enforcement recommend a certain minimum number of police officers, based on a jurisdiction’s population. Additional goals are set by governments. For instance, a local police department may set its own goal for the ratio of police officers to population, based on its particular needs and budgeted resources. Other governmental goals may be set through legislation or regulations. For example, standards set by national environmental protection agency (EPA) and its state equivalents provide goals for air and water pollution abatement, and local comprehensive plans often set standards for accommodating traffic congestion.

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Presenting trends and targets through graphic display is usually more helpful for task force members than presenting numbers alone. If you project trend lines from the past into the future, you should clearly identify your rationale for the projection, especially if you are simply continuing the “best fit” line into the future. Some computer graphics programs can do best-fit projections for you automatically. You can offer alternative projections by making assumptions of percentage changes from the best-fit line, say 10% greater and 10% lesser. If you combine one or more trend-line projections with a proposed target on the same graph, task force members can readily visualize the relationships among the lines and more easily make judgments about the desirability and feasibility of a target.

When to Set Targets At JCCI, we set targets for the year 2000, 6 years after the inception of our project in 1985. Although targets could be decided upon in the first year of the project, it would be very difficult to do so. For many of the indicators, professional standards or governmental goals may be lacking. In these cases, trends and history may form the major basis for selection of the target. So, if you have little or no trend information, you may have no basis for the target. Additionally, as indicated above, much staff research must be accomplished to support volunteer task forces in making decisions about targets. This research cannot be initiated until after the indicators have been selected and will probably require a month or more of staff time. Following completion of staff research, at least three additional task force meetings will be required. For these reasons, we recommend that you wait until you have published at least six annual reports before setting targets. After this period, you will probably also want to review all indicators since some may proven to be ineffective. Your citizen task forces can then accomplish two important tasks at once: review and evaluation of all indicators and the setting of a target for each indicator. The next section, “Preparing for Publication,” includes suggestions for displaying targets in your reports, if and when you do undertake this step.

Preparing for Publication This section guides you through the staff process of deciding how to display your indicators in written form, what additional information to include, and how to prepare your written materials for publication. If you have the computerized capability for desktop publishing, these decisions become part of the same process. Otherwise, you may be responsible for deciding what information to print and how it should be displayed, while others may deal with the details of creating the printed product. There are at least three good reasons to publish the results of your project: 1. Citizens will become better informed about important aspects of the local QOL 2. Decision-makers may be influenced to take actions toward improving the local QOL

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3. Researchers, planners, and others interested in the details and methodology behind the indicators will have the information they need to understand, how the indicator numbers were derived and perhaps why the trends are moving as they are The first two of these call for a public report, which clearly and concisely communicates the essence of the indictor trends and how they relate to the QOL. The third suggests the need for a research report with documentation of methodology and explanations of trends, to the extent that these are available.

The Public Report Once you have gone through all the hard work of planning the project, assembling participants, choosing indicators, and collecting the data, you will want the results of all this effort to get the broadest exposure possible within the community. Your best bet for achieving this exposure is to present the information clearly and concisely in a report designed especially for the general public. Ideally, every citizen in your community should have access to the public report, as a tool for making his or her own evaluation about the community’s QOL. Other possible audiences include the media, business leaders, educators, and locally elected and appointed officials. Although you have probably gathered reams of interesting and important data relating to your indicators, not all of it can be included in the public report. Your task is to decide which components of the data are most important and will be most informative to your reader. In this report, you will want to present at least the following: Basic information about each indicator, its trends, and (if one has been chosen) its target Additional information explaining the QOL concept and the context for the tracking of indicator trends and setting of targets Perhaps some analysis of trends and some interpretation of their meaning in terms of the status of the local QOL and priorities for its improvement This report should be designed in an easily readable and visually striking format. Perhaps the best advice is to minimize text, while maximizing headings, definitions, explanations, short tables of figures, and simplified graphs.

The Research Report This report may be as important to you as it is for those for whom you print it. One choice would be not to print it all. However, you will still have to gather all your documentation and put it into some organized form so that you can recreate your research next year and so that you are prepared to answer queries about the methodology and meaning of each indicator. If you do not make this detailed information available, you will probably soon wish you had, as those queries come in. Several audiences exist for the research report, including at least: Public and academic libraries Local planning agencies

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Local government agencies Nonprofit organizations (human services, the arts, etc.) Economic development organizations, including Chambers of Commerce The research report may become a particularly valuable resource for agencies and organizations involved in visioning or strategic planning efforts. A logical way to organize this report is to present it in four parts: 1. An introduction including information such as: A description of the overall purpose, process, and methods of the QOL project Criteria used for the evaluation and selection of indicators (and targets, if you have developed them) General background information about the community, perhaps including demographics, geography and climate, the economy, and government Recognition of people and/or organizations—especially volunteers and contributors—who participated in the project Perhaps a summary statement evaluating overall trends in the QOL 2. A summary page (perhaps a foldout page) displaying just the figures for each year for each indicator, which can be effective as an overall reference sheet for both researchers and people with a general interest 3. Display of the indicators, perhaps one indicator to a page or two-page spread, including at least the following for each: The specific definition of the indicator Figures for all years available in tabular form Figures in graphic form The target, if you have one Description of the method of calculation Identification of the source of data A listing of explanations, caveats, etc. 4. An appendix with technical information, which might include the detailed results of a telephone survey, if one were used, source and definitions of the deflator factors used, etc. Visual impact and easy readability are less important for this report than they are for the public report. However, the research report needs to present its information in clear and organized form to be useful. At a minimum, you should use a generally uniform layout to display each indicator.

Publishing Decisions After deciding the types of reports you want to publish and their components, you will then need to explore the options available for publishing these documents. With the right skills and access to a computer system with desktop publishing software, you can design the reports and prepare the artwork in house. This is probably the most economical choice. Otherwise, you will need to organize your materials and contact printing companies that can provide the services you need. For each report you choose to publish, you will need to answer questions about:

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Budget. The funds you have to spend on publishing costs will impact all of your printing choices. For example, you may have to settle on a simple one-color design in order to afford to print the desired number of reports for your distribution plan. When planning your publishing budget, do not forget about the donation of in-kind services. Perhaps you can entice a local corporation to pay for printing costs by agreeing to a prominent acknowledgment on the report covers and references in the project’s publicity. You may find that photocopying the report pages may be more practical (although less aesthetically pleasing) than reproducing them on a printing press. Time line. Working with your designer and printer, plan backward from the scheduled release date of the document. Set a deadline for each step, making sure that you add plenty of cushion time. It is important not to plan a time line that is too tight, especially for your first year’s publication, because you are apt to run into unanticipated problems. Most importantly, do not skimp on time to proof read the document—the credibility of your entire project is at stake. Before beginning the design process, all decisions about which indicators and components to include should be finalized and all the data should be in hand. If promised information does not arrive as planned, you may be faced with costly revisions or an embarrassing delay in releasing your report. Quantity. Well before you are ready to publish the reports, you will need to have a clear idea of your distribution plan and the total number of reports you want to be available. Determining the public demand for the document can be difficult, especially for the first release of the report. In developing your distribution plan, you should consider the amount of publicity you expect to generate and alternate ways you can reach the public with your report. For instance, you might be able to persuade a local newspaper to publish a special insert featuring your QOL indicators. Design. There are numerous components that make up the overall look of the report. Some include ink color(s), paper type, paper color, graphics, and cover artwork. Your choices may be constrained by your budget, but you should strive for a look that invites readers to open the report and keeps them interested in the information. When designing the layout of the report, keep in mind that you will be releasing the document annually and strive for a format that will easily accommodate future years of data. In addition, many publications require special designing to qualify for bulk rate postage, so check with the U.S. postal service before settling on your format. Two areas where you can save printing costs include the number of pages and the type of paper you choose for your report. Remember that thicker and heavier documents will cost more to both print and mail. You can also save costs by working with standard paper sizes. After determining the dimensions of the paper and the number of pages, you can choose the best way to put it all together. Choices here include spiral binding (like JCCI’s research report), saddle stitch (like JCCI’s public report), or perfect binding.

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Distribution and Public Education Distributing your product and informing the community about your work is a project in itself. Your sponsoring organization has probably had some experience in public relations with other projects. The suggestions listed here are but a few of the many directions you might choose to take. Your task forces and steering committee can generate many options for you.

Develop a Distribution Plan Consider the many ways that you can reach the largest numbers of citizens possible. In developing your distribution plan, consider the overall goals of your project. Who are you trying to reach? What do you want this audience to do with the report? Carefully develop a distribution list for a mass mailing of the report. At minimum, include: Libraries All citizen volunteers who worked on the project All public officials The media Resource persons who presented to your task forces All data sources Major community institutions If you publish both a public report and a research report, you will need to determine the most appropriate report for each group. You might arrange personal visits for small groups of individuals who are especially important to your project’s goals. For example, you could schedule personal visits to deliver the report and briefly explain its contents to your community’s top government officials.

Involve the Media One of the most cost-effective ways of getting the word out about your project is through the mass media. You will find the task of gaining assistance from your local print and broadcast media much easier if you have kept these organizations informed and involved from the beginning. One effective way of accomplishing this is by recruiting media professionals to serve on the project’s steering committee or on the various task forces. Some ways of gaining media attention include: Mailing press advisories that alert the local media to the upcoming release of the report Mailing press releases that explain your project clearly and concisely in a maximum of two pages Arranging a press conference to formally release the project to the media

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Arranging one-on-one meetings with the editorial staff of various local media organizations Scheduling appearances on local television and radio interview shows to discuss your project If your organization does not have experience in media relations, consider seeking volunteer help from a local media professional, or from an advertising or public relations firm.

Organize a Formal Release Event One way to attract media attention is through a formal event to release the report, perhaps a luncheon or dinner convened by the funding or sponsoring organization. This event could also serve to honor and thank the citizens who participated in the project.

Present Your Report to the Community One of the best ways of bringing your project to citizens is through presentations to civic, social, and professional organizations. Many of these groups hold weekly or monthly meetings and welcome presentations about what is happening in the community. The local QOL is a topic that will certainly fit within the concerns of almost any group. The first step is to develop a standard 15–20 minute presentation that explains the community QOL concept, outlines your project, and describes the results. You may want to develop a short slide show or video for these presentations. Recruit volunteers from the steering committee and the task forces to serve as speakers. Market your presentation by sending local organizations a flyer advertising your presentation and by asking the project’s participants to arrange presentations to organizations in which they are members. Never doubt that a small group of thoughtful, committed people can change the world. Indeed, it is the only thing that ever has. (Margaret Mead)

Encouraging Citizen Action and Use of the Report Purposes of the Report In Jacksonville, the QOL indicators were designed to fulfill a number of purposes: To produce an annual report card on community progress To serve as a planning tool for government and private institutions To educate the residents about their community and the factors they consider important to their QOL To increase awareness of the many components of progress and their interrelatedness, the connections between people and their environment To highlight community success stories and give credit for work well done

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To identify areas of decline or concern where community action is needed To help focus community resources and efforts in the areas of highest priority To encourage residents to take an active part in addressing community problems To promote accountability of local government To stimulate new and better ways of measuring progress

Limitations of the Report The product was not expected to be a community action plan, nor did JCCI appoint itself to ensure single handedly that community problems would be adequately addressed. Nor did we expect that public policy changes would occur directly simply as a result of publication of the report. Indicators are simply that—they give an “indication” of where the community is making progress, and where trouble is brewing. The indicators alone, however, will not Tell you the underlying causes of the problems Give you a full understanding of the nature of the problems Tell you how the community is currently addressing a particular problem Prescribe a detailed action plan The targets tell us how much progress we hope to achieve by a certain date. Yet the targets themselves are not broad-based goals. For example, education was selected the top-priority element in Jacksonville. The top-priority indicator was the high school graduation rate. To citizens the high school graduation rate was an output indicator that tells us how successful the schools are in preparing students for their roles in life after their school years. The method we should use to measure this indicator of progress is not evident from our report. For example, clearly we do not want to improve the high school graduation rate by simply lowering graduation requirements. The report tells us where we want to be but not how to get there. Nevertheless, the first step in making changes is increasing public awareness of the problems and the need for changes. This report takes the first step.

Uses of the Report The indicators have been widely used within the community. In a number of cases, community action and policy changes have resulted. Although this project was conceived as primarily a planning and monitoring tool, there is plenty of room for citizen action. Here are some of the uses of the report in Jacksonville: City planners, editorial writers, journalists, and researchers use the report extensively as an integral part of their work. Elected officials refer to the report as they determine how to allocate resources to meet community needs. Many institutions use the report as a comprehensive view of the community in a strategic planning process.

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Institutions use the report as a guide in setting their annual work plans. JCCI refers to the data as it selects its study issues for the year. Private and community foundations use the report in their grant-making decisions. The Chamber of Commerce uses the report as an economic development tool and as a method of setting priorities within its annual work plan. Citizens use the report to support their recommendations to public officials.

Resulting Community Actions Here are a few of the actions and changes that have occurred at least partially because of the report: JCCI studied preventing school dropouts as a result of the dropout data. The JCCI study recommended a number of actions, including the appointment of a full-time dropout coordinator in the schools and the initiation of the Cities-inSchools program. Both recommendations have been implemented. In fact, the Cities-in-Schools program has now expanded to 15 schools and has produced hard evidence of reducing the dropout rate in those schools. In response to the rapid and steady increase of the perception of racism in our community, the Jacksonville Community Foundation devoted a year of grant making in a special program to the cause of furthering positive race relations. The Chamber of Commerce received an environmental award for its work in increasing public awareness of the plight of the St. Johns River, after examining water quality indicators and studying the causes of the declining water quality. A spin-off from their efforts was the formation of a grassroots citizen organization called the Stewards of the St. Johns River. The Stewards work for the restoration and preservation of the river. They have initiated a Riverwatch Hotline, have sponsored a local Adopt-a-Shore program, have stimulated the formation of a Water Quality Commission, and have educated school children about the river. In response to Jacksonville’s unusually high level of lung cancer, health scientists felt that an epidemiological study was needed to pinpoint the causes. At least partially because of the evidence provided by the indicator, city planners were able to include funding for such a study as a part of the city’s comprehensive plan. City bioenvironmental officials are now working on the design of a water quality index, which will make measures of river water quality more understandable to the average citizen. Officials currently monitor more than ten components of water quality, but our report details only two of these. Thus the reader does not get a complete picture and may not fully understand the pieces that are reported.

Ways to Stimulate Actions and Policy Changes Several ideas are listed here. Many more will no doubt come to mind as you think of your own community:

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Try to involve groups with a particular interest in an element. As an example, make a presentation to the Sierra Club about the natural environment. Get them to analyze and interpret the data, and suggest action steps that any citizen could undertake. Take the report to the members of your city council and school board. Enlist their help in understanding the data related to their interests. They, in turn, may suggest neighborhood associations or parent teacher associations, which would like to hear your message. Try to get the newspaper to do a series, focusing on each element of the QOL. Such a series will produce greater results than you could ever achieve on your own. Use the report as a tool for government accountability. Ask questions when the report is released and encourage government officials to disclose their plans for improvements. Urge institutions to use your product internally, as they exert influence on the community. Be patient but persistent and community change will evolve.

The Annual Review Process Need for Annual Updates Once you have published your first report, you will have to plan for future reports. Although a one-time snapshot of a community is useful, trend data is definitely more useful. Updating the data is largely a staff function. It is a good idea, however, to involve a volunteer review committee in the annual process.

The Review Committee Charge: The charge of the review committee is to: Examine the entire document for accuracy Advise staff regarding format Make recommendations for improving the product next year Develop a brief summary report of highlights Value: The value of the review committee lies in: Noticing and alerting staff to aberrations in the data Correcting minor errors Providing people interested in participating in public relations activities Continuing citizen involvement in the project Ensuring the continuing commitment of funders and key community organizations Composition: The review committee should include: People who like and understand numbers People familiar with community interests such as health, the economy, and most of the other elements of the QOL (because of their knowledge, they will more easily spot any anomalies or errors)

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Representatives from the governing body of the sponsoring organization and funding sources An expert in public relations Some people who have been involved in the project before, and some people new to the project Again, be sensitive to the balance by race, gender, and sections of the city. Size: A review committee of ten people should be sufficient. A larger group will make it difficult to move through the document.

Making Changes in Indicators The review committee, particularly those who were not involved in the initial project, may have a tendency to want to rethink each indicator and to redo many of the indicators. Since many of the indicators are less than perfect, it is natural that a newcomer will think that better indicators are available. The newcomer should be encouraged to find better indicators, but should be told that these were the best available at the time. The chair will need to keep the discussions focused on the task at hand. In general, the goal should be to retain the indicators unchanged, so that you will have consistency over the years. However, minor changes will have to be made from time to time. As these changes are considered, it is important to refer back to the criteria for selection of indicators. Dropping indicators. An indicator may have proven difficult in some way. An indicator about new tree plantings was dropped because of the inconsistencies in data collection each year. An indicator on immunization rates was dropped because the data could not be verified and was seldom available when needed for the annual report. Modifying indicators. At times, it may be necessary to modify indicators. Under discussion in Jacksonville is the indicator measuring water levels in the Floridan aquifer. Experts differ on exactly what that indicator tells us and how it can best be expressed. Staff will do extra research on this during the year, reporting back to the next review committee for a final decision. Adding new indicators. In some cases, new indicators, not previously available, have emerged. In other situations, new important problems, worthy of measurement and inclusion, have developed. As an example, an indicator on AIDS was not available in 1985 but has since been added to the JCCI indicators. If the new indicators meet the criteria for selection of indicators and gain the approval of the review committee, the staff should be instructed to gather the data for inclusion in the next year’s report.

The Summary Report When sufficient trend data has been accumulated, the annual summary report may include a section on highlights. The “gold stars” highlight the areas of progress, while the “red flags” alert the community to issues which require community action. The review committee should edit, revise, and eventually approve a draft prepared by staff.

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JULY

AUG

SEPT

OCT

NOV

DEC

Staff collects data

Telephone survey

Review committee Report printed

Fig. 6. Time line for annual review process.

Time Line A 3-month period should be allowed for the staff to collect and compile the data for the annual report. Three 2-hour meetings should be sufficient for the review committee to complete its work (Figure 6).

Notes 1. Published by the Jacksonville Community Council Inc., Jacksonville, Florida (originally © 1994 by the Jacksonville Community Council Inc.). David Swain is the editor of this manual. JCCI has released the contents of this manual into the public domain with the stipulation that any use of its content in other documents for public or organizational use be accompanied by a full source reference, including identification of the title, author, publisher, and date of publication.

MARIAN CHAMBERS, Executive Director, Jacksonville Community Council Inc. [email protected]

DAVID SWAIN, Professional Staff, Jacksonville Community Council Inc. [email protected]

Contributors

Maybelle Taylor Bennett is Director of the Howard University Community Association, where she works with the Senior Vice President and area residents to implement planning, development, historic preservation, and cultural and human service activities in the university’s neighboring communities. Key activities have included: housing; a new Middle School of Mathematics and Science; commercial uses; a Trauma I hospital; and a service corps. She is a planner by profession, who received her master’s degree in Urban Planning from Columbia University. She served for 16 years on the Zoning Commission for the District of Columbia. Genevieve Bertone is the Executive Director for Sustainable Works, a Santa Monica-based nonprofit organization that helps students, residents, businesses, and cities incorporate sustainable actions into their everyday lives, operations and programs. She is currently pursuing a master’s degree in urban planning, with an emphasis on environmental planning, at the University of California, Los Angeles. As Vice Chair of the Santa Monica Sustainable City Task Force she is helping to create an implementation plan and engage the public in meeting the goals of the Sustainable City Plan. She has extensive experience working to help the nonprofit sector engage the community in local and global environmental initiatives. Originally from Oklahoma, she lives in Santa Monica with her husband. Marian Chambers was a highly respected civic leader in Jacksonville, Florida, from 1975 until her death in 1996. For many years, she served as executive director of the Jacksonville Community Council Inc. (JCCI), a local, nonprofit thinktank organization that instigates community improvement through citizen learning and advocacy. Perhaps her most significant contribution was envisioning and institutionalizing a unique process to measure community progress, based on community indicators selected and maintained through volunteer citizen effort. Since 1985, JCCI’s pioneering work has played a leadership role in a burgeoning national and international community-indicators movement. In 1991, she was chief author of a “replication manual” (included in this volume) designed to help other communities adapt and build on the Jacksonville experience. Nancy Findeisen is president and chief executive officer of the Community Services Planning Council Inc., Sacramento, California, a post she has held since 1983. She has over 30 years experience in community development and social services planning. She initiated the Human Services Information System, a comprehensive regional database of health and social indicators. She served 13 years as a member of the Board of Education of an urban school district and has held leadership positions with other organizations, including League of Women Voters, California Urban School Districts Association and Nonprofit Resource Center. She is past president and a current board member of the National Association of Planning Councils. She received a bachelor’s degree in education from Florida State University.

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Rodney D. Green has, for 11 years, served as Executive Director of the Howard University Center for Urban Progress, a unit designed to strengthen the university’s urban research, community service, and community development agenda at local, federal, and international levels. He has directed over 50 projects with a value of over $15 million in this period. He has also served as a professor of urban economics since 1977, authoring three scholarly books and over 40 journal articles. He received his bachelor’s degree in politics and economics from Yale University and his M.A. and Ph.D. (1980) in economics from the American University. Peter Hardi is Senior Fellow at the International Institute for Sustainable Development, Canada. He holds an M.Sc. in chemistry and a Ph.D. in political science. He combines a comprehensive knowledge of the theoretical and methodological issues of sustainable development (SD) with practical field experience in designing and implementing SD strategies and indicator projects in a variety of settings, ranging from local communities to international agencies, both in developed and developing countries. Dr. Hardi is member of the editorial board of the journal Ecological Indicators. He is the author of several books and monographs on the environment, SD, and measurement. Meg Holden, an assistant professor of Urban Studies and Geography at Simon Fraser University, obtained her Ph.D. in public and urban policy from the New School for Social Research in New York City. Holden’s research examines and promotes the hope of cities around the world for sustainable development. She works on this through policy and action, civic engagement and social learning, urban philosophy and ethics, and community-based information systems approaches. Her current projects include directing the Regional Vancouver Urban Observatory, within the UN-Habitat Global Urban Observatory network, to develop an interperspective indicator set for the future-sustainable Vancouver region, and working with the Learning City, an urban sustainability research and education initiative based in Vancouver. Charlotte Kahn cofounded and directs the Boston Indicators Project at the Boston Foundation in partnership with the City of Boston and the Metropolitan Area Planning Council. She has been the director of the Boston Persistent Poverty Project and Community Building Network at the foundation, and previously directed the Public Education Fund of the Tax Equity Alliance for Massachusetts and Boston Urban Gardeners (BUG), an organization dedicated to community gardening, neighborhood open space, and job training in urban landscape management. She attended Cornell University, holds a master’s degree from Antioch University, and received a Loeb Fellowship in Advanced Environmental Studies from the Harvard Graduate School of Design. She has served on numerous local boards, from President of the Boston GreenSpace Alliance to Board Chair of the Codman Square Health Center, and is a founding member of the National Neighborhood Indicators Partnership and the Community Indicators Consortium.

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Ellen Kamman is currently working as a research consultant in Durban, South Africa, and is involved in a number of research projects in the Eastern Cape province through the Fort Hare Institute of Social and Economic Research (FHISER). After finishing her master’s degree in health sciences in the Netherlands, she emigrated to South Africa in 1996. As a researcher at FHISER, she was involved in various research projects, including poverty and livelihoods projects, quality-of-life research, and social indicators projects. She has worked for a development research company in Durban as senior data manager and researcher. Her statistical background, combined with an affinity for working with large datasets has proven very useful in her current and previous positions. She currently lives in Durban with her husband and two children. Dean Kubani is a Senior Environmental Analyst with the City of Santa Monica’s Environmental Programs Division. He acts as coordinator of Santa Monica’s Sustainable City Program and has overseen the ongoing development, implementation and evaluation of the program since its adoption by the Santa Monica City Council in 1994. His work involves sustainable program and policy development, introduction of sustainable practices into municipal operations, oversight of residential and business sustainability initiatives, indicator development and program evaluation, and extensive public outreach efforts. Dean has lectured on sustainability at universities throughout the country, and has presented information about Santa Monica’s Sustainable City Program at state, national, and international conferences. He sits on the Advisory Boards of the International Sustainability Indicators Network and the University of Southern California Center for Sustainable Cities. Before his employment at the City of Santa Monica, Dean worked as a Policy Analyst in the nonprofit sector and was a Project Manager for an environmental engineering firm in Southern California. He lives in Santa Monica with his wife and two daughters. Haydar Kurban has served as an assistant professor of Economics at Howard University since 2001. Previously, he served as a Research Assistant Professor at the Center for Urban Economic Development at the University of Illinois at Chicago. His publications (with Brookings Institution and in journals including Regional Science and Urban Economics) focus on urban sprawl, the spatial impacts of federal fund allocations, urban industrial clusters, earnings inequality, local economic development programs, and local electric power systems. He is a co-investigator on an NSF-funded project to design reliable power systems. He earned his Ph.D. from the University of Illinois at Chicago in 1999. Filomena Maggino is researcher and professor of Social Statistics at the University of Florence (Italy) at the Faculties of Economics, Political Sciences, Psychology and Education. In the past she conducted research works concerning the creation of computerized information systems in support of the public intervention directed to groups of population at high risk (elderly and young people, mental patients, etc.), participating to experimental projects finalized to the construction of monitoring system supporting social and health services. In the past

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years she focused specifically her research work on statistical models concerning (a) the subjective measurement (construction and validation of instruments in epidemiological, psychological, and social fields); and (b) the comparison and integration of objective and subjective social indicators within territorial-spatial and temporal dimensions also finalized to the evaluation of public structures (schools, universities). Lorenzo Morris is Professor and Chair of the Howard University Political Science Department. Previously, he was Assistant Professor at the Massachusetts Institute of Technology and a Brookings Institution Research Fellow. He has published five books and approximately 100 articles on diverse subjects including electoral politics, black politics, comparative politics, community development, and higher education policy. He has been a consultant on election organizing, education policy, and party politics in several countries, particularly in francophone Africa. He received his Ph.D. from the University of Chicago and B.A. from Fisk University. Shannon Clements Parry is the founder of Sustainable Places where she consults on sustainable city indicators, sustainable practices in the film and television industry, green building, and a host of other urban sustainability projects. She is an LEED accredited professional. She received her master’s degree in urban planning from the University of California at Los Angeles (UCLA) where she was the Director of the Environmental Coalition and founding member of the UCLA Sustainability Committee. She received the Erin Brockovich/Ed Masry Fellowship for Leadership in Environmental Justice, as well as the GSA Jeffrey L. Hanson Distinguished Service Award. She holds a B.S. in Environmental Science, Policy and Management, and a B.A. in Peace and Conflict Studies from the University of California at Berkeley. László Pintér has been with the International Institute for Sustainable Development (IISD), Canada, since 1994 and helped set up the Institute’s program on Measurement and Assessment. Serving as Director since 2003, his role is to provide strategic leadership to ensure program growth and influence, manage the program team and coordination with other program areas according to IISD’s overall vision and mission. In 2004 he also led the design of IISD’s Sustainable Natural Resources Management program around the concept of adaptive ecosystem management and resilience, with initial emphasis on water and agriculture. He is a frequent speaker at international events and serves on the board of a number of organizations, including the Canadian and International Sustainability Indicators Network and Helio International, and chairs the Planning Group of the Winnipeg Community Indicator System initiative and the Capacity Building Working Group of UNEP-DEWA. His project work, personal interests, and publications are related to the role of information in decision-making, sustainability assessment and reporting in place-based, regional and global contexts, and the design and implementation of effective sustainable development strategies on the national level. He also works in the areas of integrated vulnerability analysis and adaptation planning. László holds a diploma in Agronomy (1988) from Gödöllö University of

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Agricultural Sciences, Hungary, a master’s degree in natural resources management (1994) from the University of Manitoba, Canada and a Ph.D. from the University of Minnesota (2002). During 2000–2001 he spent ten months as a Global Environmental Assessment Practitioner Fellow at the Kennedy School of Government of Harvard University, where he carried out research on the relationship of global integrated environmental assessment system design and effectiveness. László lives with his wife and three children in Winnipeg, Canada. Don R. Rahtz is a marketing/marketing communications researcher and Professor of Marketing at The College of William and Mary in Virginia. He received his Ph.D. from Virginia Tech. in 1984. His expertise is in marketing communication programs, marketing research, survey methodology, analysis, and market assessment. He has had a particular interest in quality of life, environmental issues, economic sustainable development, business/community interface evaluation, and health systems. He has traveled and worked extensively in the South and Southeast Asian area with a focus on Bangladesh, Cambodia, Vietnam, and Thailand. He has conducted a variety of workshops and seminars, and acted as a consultant to businesses in both the public and private sectors concerning these topics, both in the United States and abroad. He has been active in promoting the quality-of-life field of study in a variety of disciplines. He has published a variety of articles in journals from the social, behavioral science, communication, and marketing areas. He is a founding member of the International Society for Quality-of-Life Studies (ISQOLS), and has been instrumental in the planning and execution of three Quality-of-Life/Marketing Conferences and all of the International Society for Quality-of-Life Studies International Conferences. He currently serves as the Vice President for Programs for the International Society for Quality-of-Life Studies, a post he took over after serving as Vice President for External Affairs. Robin Richards is a Project Manager/Researcher for the Community Agency for Social Enquiry (CASE), a nonprofit research organization in Johannesburg. He has a master’s degree in human geography. His research interests include, urbanization and informal settlements; poverty and livelihoods; quality of life in cities; local government; social indicators; and land reform. His recently completed studies include an investigation of urban poverty for the City of Johannesburg which contributed to the formulation of the City’s Human Development Strategy; an impact evaluation study of an urban renewal project in Alexandra township, Johannesburg; and an evaluation of transferred Land Reform Projects in South Africa. Joe Sirgy is a social/industrial psychologist, Professor of Marketing, and Virginia Real Estate Research Fellow at Virginia Polytechnic Institute and State University (Virginia Tech.). He has published extensively in the area of quality-of-life (QOL) research in relation to theory, philosophy, measurement, business, and public policy. He received his Ph.D. from the University of Massachusetts in 1979. He is the author/editor of several books related to QOL including: New Dimensions of Quality-of-Life/Marketing Research (1995), Handbook of Qualityof-Life Research (2001), The Psychology of Quality of Life (2002), Advances in

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Quality-of-Life Theory and Research (2003), and Community Quality-of-Life Indicators: Best Cases (2004). He cofounded the International Society for Quality-of-Life Studies in 1995 and is currently serving as its Executive Director. He is also the immediate past president of the Academy of Marketing Science, the largest academic association of marketing professors worldwide. He received the Distinguished Fellow Award from both the Academy of Marketing Science and the International Society for Quality-of-Life Studies. In 2003, the International Society for Quality-of-Life Studies honored him as the Distinguished QOL Researcher for research excellence and a record of lifetime achievement in QOL research. David Swain worked on the professional staff of the Jacksonville Community Council Inc., Florida, from 1986 until he retired in 2002. For most of this period, he served as associate director, staffing studies, and overseeing JCCI’s process of volunteer-citizen studies and advocacy on significant community issues. He also followed Marian Chambers as the leader and primary staff worker in JCCI’s ongoing efforts on community indicators. He facilitated several major expansion and upgrade projects that have kept these efforts on the cutting edge of the community indicators movement. He also wrote sections of the “replication kit” included in this volume. Since retirement, he has continued his involvement in the movement internationally as a consultant and advocate. Charles Verharen is a graduate professor in the philosophy department at Howard University. His primary research field is philosophy and culture. Currently completing a book-length manuscript on Africana philosophy of education, he has published Rationality in Philosophy and Science, and his research appears in Philosophical Forum, Teaching Philosophy, Radical Philosophy Review, Journal of Black Studies, Western Journal of Black Studies, and the Encyclopedia of the World’s Minorities. The cofounder of the Howard University Mini Medical School, the Howard Community Technology Center, and the Howard Philosophy Outreach Program, he has received the UNESCO International Centre for Engineering Education Platinum Award, and an Andrew Mellon grant for the Salzburg Seminar. Ben Warner is the Associate Director for Jacksonville Community Council Inc. (JCCI). Before joining JCCI in 1998, he worked in the mental health field, where he directed day treatment programs for dually diagnosed (mental illness/developmentally disabled) individuals in Northeast and Central Florida. He also worked with homelessness issues, developing a highly successful pilot transitional housing program. For his work with homelessness, he was awarded the Michael R. Wilson Social Justice Award in 1997. At JCCI, Warner has staffed studies and/or implementation efforts on topics ranging from arts and culture to growth management and regional cooperation. In addition, he works to pioneer, develop, maintain and enhance JCCI’s Quality-ofLife Progress Report and its new Race Relations Progress Report. He completed his undergraduate studies in sociology at Brigham Young University, and received his master’s in social work from Florida State University.

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Jennifer Wolch is College Dean of Graduate Programs, Professor of Geography, and Director of the Center for Sustainable Cities at the University of Southern California, where she teaches courses on Los Angeles, urban social problems, and sustainable cities. Her research focuses on metropolitan sprawl, urban open space and environmental justice, and human–animal relations, particularly attitudes toward animals and animal-inclusive city planning and design. She also investigates urban poverty, homelessness and human service delivery. She is the author of Landscapes of Despair: From Deinstitutionalization to Homelessness (with M. Dear, Princeton University Press, 1987), The Shadow State: Government and Voluntary Sector in Transition (Foundation Center, 1990), and Malign Neglect: Homelessness in an American City (with M. Dear, JosseyBass, 1993), and coeditor of The Power of Geography: How Territory Shapes Social Life (with M. Dear, Unwin Hyman, 1989), Animal Geographies: Place, Politics and Identity in the Nature/Culture Borderlands (with J. Emel, Verso, 1998), and Up Against the Sprawl: Public Policy and the Making of Southern California (with M. Pastor Jr. and P. Dreier, Minnesota University Press, 2004). She has received fellowships from the Guggenheim Foundation, Center for Advanced Study in the Social and Behavioral Sciences, and the Rockefeller Foundation’s Bellagio Study Center.

Social Indicators Research Series 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.

14. 15. 16.

17. 18.

19. 20. 21. 22.

V. Møller (ed.): Quality of Life in South Africa. 1997 ISBN 0-7923-4797-8 G. Baechler: Violence Through Environmental Discrimination. Causes, Rwanda Arena, and Conﬂict Model. 1999 ISBN 0-7923-5495-8 P. Bowles and L.T. Woods (eds.): Japan after the Economic Miracle. In Search of New Directories. 1999 ISBN 0-7923-6031-1 E. Diener and D.R. Rahtz (eds.): Advances in Quality of Life Theory and Research. Volume I. 1999 ISBN 0-7923-6060-5 Kwong-leung Tang (ed.): Social Development in Asia. 2000 ISBN 0-7923-6256-X M.M. Beyerlein (ed.): Work Teams: Past, Present and Future. 2000 ISBN 0-7923-6699-9 A. Ben-Arieh, N.H. Kaufman, A.B. Andrews, R. Goerge, B.J. Lee, J.L. Aber (eds.): Measuring and Monitoring Children’s Well-Being. 2001 ISBN 0-7923-6789-8 M.J. Sirgy: Handbook of Quality-of-Life Research. An Ethical Marketing Perspective. 2001 ISBN 1-4020-0172-X G. Preyer and M. B¨os (eds.): Borderlines in a Globalized World. New Perspectives in a Sociology of the World-System. 2002 ISBN 1-4020-0515-6 V. Nikolic-Ristanovic: Social Change, Gender and Violence: Post-communist and war affected societies. 2002 ISBN 1-4020-0726-4 M.R. Hagerty, J. Vogel and V. Møller: Assessing Quality of Life and Living Conditions to Guide National Policy. 2002 ISBN 1-4020-0727-2 M.J. Sirgy: The Psychology of Quality of Life. 2002 ISBN 1-4020-0800-7 S. McBride, L. Dobuzinskis, M. Grifﬁn Cohen and J. Busumtwi-Sam (eds.): Global Instability. Uncertainty and new visions in political economy. 2002 ISBN 1-4020-0946-1 Doh. Chull Shin, C.P. Rutkowski and Chong-Min Park (eds.): The Quality of Life in Korea. Comparative and Dynamic Perspectives. 2003 ISBN 1-4020-0947-X W. Glatzer: Rich and Poor. Disparities, Perceptions, Concomitants. 2002 ISBN 1-4020-1012-5 E. Gullone and R.A. Cummins (eds.): The Universality of Subjective Wellbeing Indicators. A Multi-disciplinary and Multi-national Perspective. 2002 ISBN 1-4020-1044-3 B.D. Zumbo (ed.): Advances in Quality of Life Research 2001. 2003 ISBN 1-4020-1100-8 J. Vogel, T. Theorell, S. Svallfors, H.-H. Noll and B. Christoph: European Welfare Production. Institutional Conﬁguration and Distributional Outcome. 2003 ISBN 1-4020-1149-0 A.C. Michalos: Essays on the Quality of Life. 2003 ISBN 1-4020-1342-6 M.J. Sirgy, D. Rahtz and A.C. Samli (eds.): Advances in Quality-of-Life Theory and Research. 2003 ISBN 1-4020-1474-0 M. Fine-Davis, J. Fagnani, D. Giovannini, L. Højgaard and H. Clarke: Fathers and Mothers: Dilemmas of the Work-Life Balance. 2004 ISBN 1-4020-1807-X M.J. Sirgy, D.R. Rahtz and D.J. Lee (eds.): Community Quality-of-Life Indicators. Best Cases. 2004 ISBN 1-4020-2201-8

23. 24. 25. 26.

27. 28.

A. Dannerbeck, F. Casas, M. Sadurni and G. Coenders (eds.): Quality-of-Life Research on Children and Adolescents. 2004 ISBN 1-4020-2311-1 W. Glatzer, S. von Below and M. Stoffregen (eds.): Challenges for Quality of Life in the Contemporary World. 2004 ISBN 1-4020-2890-3 D.T.L. Shek, Y. Chan and P.S.N. Lee (eds.): Quality of Life Research in Chinese, Western and Global Contexts. 2005 ISBN 1-4020-3601-9 A.C. Michalos (ed.): Citation Classics from Social Indicators Research. The Most Cited Articles Edited and Introduced by Alex C. Michalos. 2005 ISBN 1-4020-3722-8 A. Ben-Arieh and R.M. Goerge (eds.): Indicators of Children’s Well Being. Understanding Their Role, Usage and Policy Inﬂuence. 2006 ISBN 1-4020-4237-X M.J. Sirgy, D. Rahtz and D. Swain (eds.): Community Quality-of-Life Indicators. Best Cases II. 2006 ISBN 1-4020-4624-3

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