Crude estimates of cannabis-attributable mortality and morbidity in Canada–implications for public health focused intervention priorities
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Cannabis is the most commonly used drug in Canada; while its use is currently controlled by criminal prohibition, debates about potential control reforms are intensifying. There is substantive evidence about cannabis-related risks to health in various key outcome domains; however, little is known about the actual extent of these harms specifically in Canada. METHODS: Based on epidemiological data (e.g. prevalence of relevant cannabis use rates and relevant risk behaviors; risk ratios; and annual numbers of morbidity/mortality cases in relevant domains), and applying the methodology of comparative risk assessment, we estimated attributable fractions for cannabis-related morbidity and mortality, specifically for: (i) motor-vehicle accidents (MVAs); (ii) use disorders; (iii) mental health (psychosis) and (iv) lung cancer. RESULTS: MVAs and lung cancer are the only domains where cannabis-attributable mortality is estimated to occur. While cannabis use results in morbidity in all domains, MVAs and use disorders by far outweigh the other domains in the number of cases; the popularly debated mental health consequences (e.g., psychosis) translate into relatively small case numbers. CONCLUSIONS: The present crude estimates should guide and help prioritize public health-oriented interventions for the cannabis-related health burden in the population in Canada; formal burden of disease calculations should be conducted.
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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 | 0.007 | 0.002 |
| 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 it