‘Now we call it research’: participatory health research involving marginalized women who use drugs
Bibliographic record
Abstract
In this paper, we discuss and analyse the strategies employed and challenges encountered when conducting a recent feminist participatory action research study with highly marginalized women who were illicit drug users in an inner city area of Vancouver, Canada. Through an analysis of the political economy of participatory praxis within current neoliberal contexts, we focus on three main areas: (i) reconceptualizing the pragmatics of participation; (ii) the microeconomic implications of participatory research, including ethical issues in payment for research participation; and (iii) the value and limits of using research as a tool for activism and empowerment. We conclude with a brief discussion of what we see to be some of the most salient social justice implications arising from feminist and participatory approaches to health research within neoliberal political spaces.
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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 | 0.046 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.042 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| 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".