Strategies for Addressing Canada’s Opioid Crisis: A Cross-National Comparative Analysis of Drug Policies
Bibliographic record
Abstract
In 2020, the opioid epidemic claimed the lives of at least 7,560 Canadians, making it the deadliest addiction crisis in Canadian history (1). Contributing to the worsening of the opioid crisis is the criminalization of drug use, which has stigmatized individuals who use drugs, exacerbated health harms, widened socioeconomic and racial disparities and created a toxic illegal drug market, now responsible for most overdose deaths (2). Reforming the criminal justice-led approach and decriminalizing small amounts of drugs for personal possession have been proposed as potential solutions to the opioid crisis, having been successfully implemented to combat drug-related harms in other countries. This study seeks to examine alternatives to the drug criminalization approach through employing a cross-national comparative analysis of drug policies in Canada, Portugal, West Virginia, and Switzerland and assess which policy framework has been successful at reducing drug-related harms. The investigation reveals that punitive drug policies exacerbate drug-related harms, including overdose deaths, drug-related incarceration, problematic drug use and HIV infections. Alternatively, the low rates of opioid overdose deaths and related harms in European countries, like Portugal and Switzerland, can be attributed to innovative harm reduction policies and programs that improve access to treatment facilities and safe drug supplies.
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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) | 0.000 | 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) | 0.022 | 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".