An ethic for community-based participatory action research
Bibliographic record
Abstract
Ethical issues have been of ongoing interest in discussions of community-based participatory action research (CBPAR). In this article we suggest that the notion of reciprocity ‐ defined as an ongoing process of exchange with the aim of establishing and maintaining equality between parties ‐ can provide a guide to the ethical practice of CBPAR. Through sharing our experiences with a CBPAR project focused on mental health services and supports in several cultural-linguistic immigrant communities in Ontario, Canada, we provide insights into our attempts at establishing reciprocal relationships with community members collaborating in the research study and discuss how these relationships contributed to ethical practice. We examine the successes and challenges with specific attention to issues of power and gain for the researched community. We begin with a discussion of the concept of reciprocity, followed by a description of how it was put into practice in our project, and, finally, conclude with suggestions for how an ethic of reciprocity might contribute to other CBPAR projects.
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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 | 0.379 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.020 | 0.104 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.014 | 0.026 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".