The generative potential of mess in community-based participatory research with young people who use(d) drugs in Vancouver
Bibliographic record
Abstract
Community-based participatory research (CBPR) is increasingly standard practice for critical qualitative health research with young people who use(d) drugs in Vancouver, Canada. One aim of CBPR in this context is to redress the essentialization, erasure, and exploitation of people who use(d) drugs in health research. In this paper, we reflect on a partnership that began in 2018 between three university researchers and roughly ten young people (ages 17-28) who have current or past experience with drug use and homelessness in Greater Vancouver. We focus on moments when our guiding principles of shared leadership, safety, and inclusion became fraught in practice, forcing us in some cases to re-imagine these principles, and in others to accept that certain ethical dilemmas in research can never be fully resolved. We argue that this messiness can be traced to the complex and diverse positionalities of each person on our team, including young people. As such, creating space for mess was ethically necessary and empirically valuable for our CBPR project.
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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 | 0.108 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.038 | 0.073 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".