Governing through community allegiance: a qualitative examination of peer research in community-based participatory research
Bibliographic record
Abstract
The disappointing results of many public health interventions have been attributed in part to the lack of meaningful community engagement in the planning, implementation, and evaluation of these initiatives. Community-based participatory research (CBPR) has emerged as an alternative research paradigm that directly involves community members in all aspects of the research process. Their involvement is often said to be an empowering experience that builds capacity. In this paper, we interrogate these assump-tions, drawing on interview data from a qualitative study investigating the experiences of 18 peer researchers (PRs) recruited from nine CBPR studies in Toronto, Canada. These individuals brought to their respective projects experience of homelessness, living with HIV, being an immigrant or refugee, identifying as transgender, and of having a mental illness. The reflections of PRs are compared to those of other research team members collected in sepa-rate focus groups. Findings from these interviews are discussed with an atten-tion to Foucault’s concept of ‘governmentality’, and compared against popular community-based research principles developed by Israel and colleagues. While PRs spoke about participating in CBPR initiatives to share their experi-ence and improve conditions for their communities, these emancipatory goals were often subsumed within corporatist research environments that limited participation. Overall, this study offers a much-needed theoretical engagement with this popular research approach and raises critical questions about the lim-its of community engagement in collaborative public health research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.190 | 0.177 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.026 | 0.052 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".