The Short‐Term Impacts of Decriminalisation of Personal Possession of Select Illegal Drugs on Drug Poisonings in British Columbia, Canada (2015–2023)
Bibliographic record
Abstract
INTRODUCTION: Canada is in the midst of a crisis featuring drug poisonings. Decriminalisation of personal possession of select illegal drugs was implemented in British Columbia, Canada on 31 January 2023 as one element of a public health response to reduce drug-related harms. We evaluated the short-term impacts of decriminalisation on paramedic responses to opioid poisonings and drug poisoning deaths to detect if there were early signals of change. METHODS: We sourced population-based monthly counts of drug poisonings from the provincial emergency services provider and coroners service to compute total and sex-specific age-standardised rates per 100,000 (January 2015-December 2023 [97 months pre-decriminalisation and 11 months post-decriminalisation]). Generalised additive models in an interrupted time series design were used to evaluate the short-term impacts of decriminalisation on rates of paramedic responses to opioid poisonings and drug poisoning deaths. RESULTS: Decriminalisation was not associated with an immediate effect (β [95% confidence interval; CI] -0.078 [-0.318, 0.163]) or trend change (β [95% CI] -0.022 [-0.082, 0.037]) in the total rate of paramedic responses to opioid poisonings, nor was it associated with an immediate effect (β [95% CI] -0.165 [-0.477, 0.147]) or trend change (β [95% CI] -0.010 [-0.082, 0.062]) in the total rate of drug poisoning deaths. These findings were consistent after stratification by sex. DISCUSSION AND CONCLUSIONS: Decriminalisation of select illegal drugs was not associated with significant changes in drug poisonings in the first 11 months of its implementation. However, the direction of effects was encouraging from a public health standpoint.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".