Getting “The whole picture”: A review of international research on the outcomes of regulated cannabis supply
Bibliographic record
Abstract
BACKGROUND: Several jurisdictions have pursued reforms that regulate cannabis production and/or sale for adult (non-medical) use. Looking at outcomes of such reforms across multiple jurisdictions may help to identify outcomes that are inherent to non-criminal cannabis supply, as well as provide insight into the outcomes of specific regulation models. METHODS: We identified nine indicators of cannabis policy outcomes and aggregated them into three domains (social outcomes, outcomes in cannabis use, health-related outcomes). We assessed these outcomes across five jurisdictions with different models of regulating cannabis supply (Netherlands, Spain, U.S. states that legalized cannabis, Uruguay, and Canada). We used a three-level systematic literature review, prioritising studies with quasi-experimental design (i.e. comparative and longitudinal). We categorised the studies according to their design and the type of outcome (increase, decrease, or no outcome). RESULTS: Across long-standing as well as recent cannabis supply regimes, and across different models of cannabis supply, our review identified common outcomes: a decrease in cannabis-related arrests, an increase in adult (but not adolescent) cannabis use, and increase in healthcare utilization (not traffic-related). Negative health-related outcomes were most consistently found for the U.S. states that legalised cannabis for adult non-medicinal use (there were limitations to nuancing cannabis supply models across U.S. states). In the remaining jurisdictions (the Netherlands, Spain, Canada, Uruguay), the design or time-frame of the identified studies was limited, and studies on certain outcomes were lacking. CONCLUSIONS: Regulating cannabis supply may be associated with benefits in the social area and with potential harms regarding public health; there may though be trade-offs depending on the choice of a cannabis regulation model. Jurisdictions may attempt to mix and match the present models of cannabis regulation to achieve the best ratio of benefits and harms. More research into the specific parameters influencing cannabis policy outcomes is needed.
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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 | 0.014 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.019 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".