Worth the Risk? Muddled Relationships in Community-Based Participatory Research
Bibliographic record
Abstract
Community-based participatory research (CBPR) is a collaborative research approach that has two purposes: (a) to generate knowledge about and (b) to take action to improve the lives of people facing health, social, economic, political, and environmental inequities. The foundation of all CBPR projects is its partnership--its cooperative relationship between community members, service providers, program planners, policy makers, and academics. It is with people--and through relationships--that partnerships are built and sustained. Although relationships between academics and community members are critical to creating knowledge and change, they are overlooked in the literature. We often hear about CBPR "gone wrong," when tensions and conflicts arise because relationship boundaries become blurred. Our purpose is to expose the muddled relationships that can be created between academics and community members in CBPR projects. Drawing upon our experiences presented in a series of vignettes, we consider the nature of these relationships. We explore whether we conduct, in CBPR, good research at the expense of muddling relationships. Despite the potential for muddled relationships, we believe that CBPR is the best approach for research aimed at achieving a more equitable and just society.
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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 | 0.147 | 0.199 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".