The knowledge and effect of a drug-related good samaritan law among people who use drugs in Vancouver, Canada
Bibliographic record
Abstract
In response to the drug poisoning crisis in Canada and the US, some jurisdictions have enacted drug-related Good Samaritan laws (GSLs) to encourage observers of acute poisoning events to call emergency medical services (EMS) during times of overdose.To date, the effectiveness of GSLs are indeterminate.This thesis undertook a literature review on the effectiveness of GSLs, evaluated the working knowledge of a GSL, and the impact of this law among participants of three large prospective cohort studies of communityrecruited people who use illicit drugs (PWUD) in Vancouver, a full year after the enactment of a GSL in Canada.Overall, the literature review demonstrated mixed evidence with regard to the effectiveness of GSLs.Only about a third of our sample had accurate knowledge of the GSL and the GSL did not appear to have changed EMS-calling rates.Additional measures are urgently needed to support the aims of GSLs.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".