Police officers’ knowledge, understanding and implementation of the Good Samaritan Drug Overdose Act in BC, Canada
Bibliographic record
Abstract
INTRODUCTION: In May 2017, the Good Samaritan Drug Overdose Act (GSDOA) was enacted in Canada - amending the Controlled Drugs and Substances Act. For people present at an overdose, the GSDOA offers legal protection from simple drug possession as well as breach of charges related to simple possession including probation, pre-trial release, conditional sentences, and parole. It is unclear if the GSDOA has been fully implemented by police officers. METHODS: We conducted 22 key informant interviews with police officers across British Columbia, Canada. Convenience sampling was initially employed, followed by purposeful sampling to ensure diversity in jurisdictions and participant demographics (e.g. age, sex, policing experience). A thematic analysis was conducted RESULTS: Our findings show that awareness and knowledge of the GSDOA vary among police officers. Many officers reported being unaware of the GSDOA or could not correctly define for whom and when the GSDOA applies. Information about the GSDOA was largely disseminated via email. Many officers expressed concerns with this dissemination method given the potential that key legal information would be overlooked. Police officers reported that not arresting for simple possession at an overdose was common practice, even before the enactment of the GSDOA. Thus, some officers did not believe that the GSDOA considerably changed police practices. Finally, police officers reported that they exercised discretion applying the GSDOA. Police officer interpretation of the intention and content of the GSDOA had critical implications for how they applied it in practice. CONCLUSION: Effective education for law enforcement, including the dissemination of information beyond email, is needed to improve officers' awareness and understanding of the GSDOA. Given officers' use of discretion when applying the GSDOA, greater legal reforms, such as de jure decriminalization, may be required to fully protect persons at an overdose from simple possession for controlled substances.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".