Supporting the full participation of people who use drugs in policy fora: Provision of a temporary, conference-based overdose prevention site
Bibliographic record
Abstract
The overdose epidemic in North America remains acute and interventions are needed to mitigate harm and prevent death. People who use/d drugs (PWUD) hold essential knowledge to guide the development of these interventions and conferences are vital fora for hearing their perspectives and building support for new policies and programs. However, little guidance exists on how to best ensure the safety of PWUD during conferences. In October 2018, a low-threshold overdose prevention site (OPS) was implemented at a national drug policy and harm reduction conference in Edmonton, Canada. The OPS provided delegates with a monitored space to consume drugs and access drug consumption supplies. This commentary describes the implementation of the OPS with the aim of providing practical guidance for organizers of future substance use-related conferences, meetings, and other events.
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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 | 0.028 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.021 | 0.023 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".