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Record W1648999852

Opportunities and Pitfalls of Community-Based Research: A Case Study

2003· article· en· W1648999852 on OpenAlexfundaboutno aff
Michael Polanyi, Lynn Cockburn

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2003
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsParticipatory action researchPublic relationsSociologyAction (physics)Action researchAlienationCitizen journalismCollective actionCommunity engagementEngineering ethicsPolitical sciencePedagogyEngineering
DOInot available

Abstract

fetched live from OpenAlex

Support for, and engagement in, community-based (CBR) has increased over the past decade (Green et al., 1995; Sclove, 1997). Research between university academics and community-based individuals and organizations have spread. Such are said to generate new knowledge, empower community members, build common ground, stimulate collective action and solve complex problems. Yet the qualities of these partnerships vary, and on the process and outcomes of these forms of is limited (El Ansari, Phillips, & Hammick, 2001). This paper aims to bring attention to the opportunities and pitfalls associated with CBR. We are particularly interested here in the tensions that arise when university academics engage in CBR projects. To this end, we draw on our experience as academic partners in a recent two-year CBR project aimed at stimulating by, and collective action to improve the situation of, Ontario injured workers. Our experience suggests that CBR, even when based at a university setting, has the potential to engage marginalized communities in critical reflection and action on their social concerns. It can stimulate learning, and build people's capacity and commitment to collectively address real-world problems. However, the institutional structures and university culture pose fundamental challenges to practicing CBR. University researchers need to be aware of these potential pitfalls to be successful in building new knowledge and stimulating informed community action to address social problems. Otherwise, they may unwittingly exacerbate marginalized communities' alienation and distress, and actually perpetuate injustice and inequality. Participatory Research Researchers have come to question the capacity of conventional approaches to understand and stimulate action on complex and enduring social problems (Hohrman & Shear, 2002; Mason & Mitroff, 1981). They doubt outsiders' capacity to understand issues that have important normative and experiential dimensions (Ansley & Gaventa, 1997; Evered & Louis, 1981). Academic researchers are recognizing that community involvement can help access participants, make more relevant, improve interpretation of study results, and increase the likelihood that findings will be applied (Schensul, 1999). At the same time, citizens and communities are increasingly seeing as an effective approach to solving local problems, and are claiming the right to participate in on issues affecting them. Educators are also recognizing the potential of community involvement and service-learning as an effective means of applied learning and citizenship building (Eyler & Giles, 1999). The renaissance of CBR over the past decade has spawned a new literature on the topic. Researchers have conducted case study reviews (Sclove, 1997), topic-specific reviews (Allman, Myers, & Cockerill, 1997), and assessments of challenges and facilitating factors (Wolff & Maurana, 2001) on this topic. However, to understand CBR dynamics, Israel and colleagues (1998) suggest the need for in-depth, multiple case study evaluations of the content and processes (as well as outcomes) of community-based endeavours (p. 194). CBR has roots in participatory research (PR), a term coined in the early 1970s by adult educators and community groups in developing countries who saw the approach as an alternative to colonial practices (Hall, 1993). PR, referred to by some as participatory action research (Whyte, 1991), is a collective process of investigation, analysis, and action through which marginalized groups identify and address problematic social and economic issues and interactions. It emphasizes the importance of alternative, non-dominant systems of knowledge production, such as traditional knowledge and local experience. To Rajesh Tandon (1988), participatory attempts to present people as researchers themselves in pursuit of answers to the questions of their daily struggle and survival (p. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0410.019
Scholarly communication0.0090.009
Open science0.0060.017
Research integrity0.0110.009
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.561
GPT teacher head0.528
Teacher spread0.033 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2003
Admission routes2
Has abstractyes

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