Police officers’ perceptions of their role at overdose events: a qualitative study
Bibliographic record
Abstract
Introduction The Good Samaritan Drug Overdose Act, a federal law enacted in Canada in 2017, aims to increase bystander response to overdoses by offering legal protection for arrests related to simple possession at the scene of an overdose. As this legislation suggests, a shift has occurred to view overdose events as a medical issue, constituting a shift in the role of police officers. Our study aimed to uncover the role police perceive for themselves at overdose events.Methods Twenty-two qualitative interviews were conducted with police officers across British Columbia (BC). A thematic analysis was completed to identify patterns in the data.Findings Police officers perceived their primary role was to ensure the safety of first responders and bystanders at overdose events. Some officers favored enforcing mandatory treatment and used coercive practices to ensure overdose victims received further medical care.Discussion Policies which reframe overdose events in terms of a health rather than criminal response put into question whether police officers have a role at overdose events and, if so, what it is.Conclusions Education and awareness are needed to reduce stigma towards people who use drugs, misunderstandings around naloxone and harmful practices such as coercion, at overdose 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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".