Community-Based Research Networks: Development and Lessons Learned in an Emerging Field

By Stoecker, Randy; Ambler, Susan H. et al. | Michigan Journal of Community Service Learning, Summer 2003 | Go to article overview

Community-Based Research Networks: Development and Lessons Learned in an Emerging Field


Stoecker, Randy, Ambler, Susan H., Cutforth, Nick, Donohue, Patrick, Dougherty, Dan, Marullo, Sam, Nelson, Kris S., Stutts, Nancy B., Michigan Journal of Community Service Learning


In the last decade a variety of models and approaches have been developed for doing CBR projects (Murphy, Scammell, & Sclove, 1997; Park, Brydon-Miller, Hall, & Jackson, 1993; Petras & Porpora, 1993; Porpora, 1999; Stoecker, 1999; Strand, 2000; Stringer, 1999; Williams, 1997). In addition, models are emerging for creating and maintaining CBR centers on single campuses (Cheadle et al., 2002; Stoecker, 2002). But we know little about multi-institutional CBR networks serving metropolitan or wider regions, partly because until very recently there have been too few cases to compare.

The first known United States network of higher education institutions and community organizations supporting CBR was the Chicago Policy Research Action Group, or PRAG, founded in 1989. With four Chicago institutions--Loyola University, DePaul University, the University of Illinois at Chicago, and Chicago State University--and more than 15 nonprofit and community organizations (Policy Research Action Group, 2002), PRAG set the standard for CBR networks and is the only one that has been written about. But writings about PRAG emphasize its projects (Nyden, Figert, Shibley, & Burrows, 1997), so we still know little about how to develop such a network. There are also specialty CBR networks, especially focused on public health (Minkler, 2000), such as the Center for Community Health Education, Research and Service in Boston and the Center for Healthy Communities in Dayton, Ohio (Center for Healthy Communities, 2000). The Community-University Research Alliances program of the Social Sciences and Humanities Research Council of Canada also sponsors specialty CBR networks in areas such as housing (Social Sciences and Humanities Research Council of Canada, 2001).

Since the middle 1990s, however, and especially in the last two years, a number of locality-based generalist CBR networks have developed. After discussing CBR networks' importance relative to single campus centers, we present brief histories and descriptions of seven CBR networks: Neighborhood Planning for Community Revitalization (NPCR) in Minneapolis St. Paul, Just Connections in Appalachia, the Trenton Center in New Jersey, the Washington DC Community Research and Learning (CoRAL) Network, the Denver-based Colorado Community-based Research Network (CCBRN), Campus-Community Partnership of Metro Richmond in Virginia, and the University-Community Collaborative of Philadelphia (UCCP). We then compare the networks' self-identified strengths, weaknesses, opportunities, and threats to draw out lessons for network formation, maintenance, and growth.

Why a CBR Network?

Six networks analyzed here developed partly through the Corella and Bertram F. Bonner Foundation Community Research Project program (2002), funded through the Corporation for National Service. The Bonner Foundation convened a meeting in Philadelphia in January 2001 with participants from an earlier Bonner CBR project focused on creating individual campuses centers, and including many new community organizations and institutions. There we discussed why we should form local and regional CBR networks, rather than just establish individual campus centers. We revisited this question at a June 2002 meeting in Spartanburg, South Carolina. Our discussions produced the following hypothesized benefits of CBR networks.

One of the most important hypothesized values of CBR networks is their synergistic effect.

Because networks employ a "weak ties" structure (Granovetter, 1973), they can tap a more diverse array of resources than can isolated efforts. Networks access different forms of funding, deploy different models of CBR, and link skills such as the multilingualism of community college students with the advanced statistical skills of students at a Ph.D. institution. Thus, networks can reduce competition and instead jointly take on complex projects for which individual CBR practitioners, or even individual centers, lack the capacity. …

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