The implementation and public health impacts of cannabis legalization in Canada: a systematic review
Bibliographic record
Abstract
AIMS: We provide a narrative summary of research on changes in cannabis arrests, cannabis products and prices, cannabis use and cannabis-related harm since legalization. METHODS: We systematically searched for research on the impacts of cannabis legalization in Canada in PubMed, Embase, Statistics Canada and government websites and Google Scholar, published between 2006 and 2021. RESULTS: Cannabis legalization in Canada has been followed by substantial reductions in cannabis-related arrests and cannabis prices. It has also increased adults' access to a diverse range of cannabis products, including edibles and extracts. The prevalence of cannabis use among young adults has increased, but there have been no marked increases or decreases in use among high school students or changes in the prevalence of daily or near-daily use. Legalization has been associated with increased adult hospital attendances for psychiatric distress and vomiting, unintentional ingestion of edible cannabis products by children and hospitalizations for cannabis use disorders in adults. There is conflicting evidence on whether cannabis-impaired driving has increased since legalization. There is suggestive evidence that presentations to emergency departments with psychoses and cannabis use disorders may have increased since legalization. CONCLUSIONS: Legalization of cannabis in Canada appears to have reduced cannabis arrests and increased access to a variety of more potent cannabis products at lower prices. Since 2019, recent cannabis use in Canada has modestly increased among adults but not among adolescents. There is evidence of increased acute adverse effects of cannabis among adults and children.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".