Perceived impacts of North Americas first de-medicalized safer supply program
Bibliographic record
Abstract
BACKGROUND: The Drug User Liberation Front led an evaluation of a non-medicalized model of safer supply known as a "Compassion Club." This club sourced, rigorously tested, packaged, and accurately labeled certain illicit substances and then provided them to club members at cost in order to investigate the effects and feasibility of a non-medical model of safer supply. Operating for 14 months, the club provided low-cost, quality-controlled illicit substances to individuals at risk of fatal overdose in Vancouver, Canada's Downtown Eastside neighbourhood. This study was undertaken to explore perceived impacts of the Compassion Club among its participants, as well as their perceptions regarding how the Club could be improved. METHODS: At the one-year time point of club operations 43 participants from the club's membership completed an interviewer-administered survey which is utilized in this cross sectional analysis. Descriptive statistics were employed to assess the perceived influence of club membership on various factors, including drug use patterns, harm reduction practices, financial outcomes, housing stability, and overall well-being. RESULTS: Applicable responses reported benefits from membership in the Compassion Club, including reduced drug use (64.3%), decreased reliance on illicit markets (86.7%), lowered risk of overdose (90.0%), and increased likelihood of using sterile equipment (84.6%). Mental health (74.2%), physical health (63.3%), and overall well-being (70.0%) were also noted improvements. Suggestions for club improvement included extended operating hours, broader substance selection, and improved accessibility. CONCLUSION: The reported reductions in drug use and improved adherence to harm reduction practices described herein underscore the perceived benefits of this unique program. Compassion Clubs represent a distinct strategy to mitigate overdose risk and enhance the well-being of drug users. These insights advance ongoing dialogues on overdose prevention strategies, urging further research to refine non-medicalized approaches within the evolving landscape of interventions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".