Alcohol and substance use policies on Canadian universitycampuses: Ascoping review of grey literature
Bibliographic record
Abstract
OBJECTIVE: We aimed to understand the current state of the grey literature pertaining to substance use policies on Canadian university campuses. METHODS: We followed Arksey and O'Malley's 5-step framework, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched institution webpages, the Centre for Innovation in Campus Mental Health(CICMH) and the Centre for Addiction and Mental Health (CAMH) websites for policy and/or guiding documents targeting student substance use on university campuses, published between 2012 to 2024. RESULTS: = 1). Institution documents included government regulations, outlined consumption rules in residence, and banned smoking. Few provided harm-reduction strategies. CICMH and CAMH documents encouraged applying whole-campus approaches when regulating substance use. CONCLUSIONS: Most institutions focused on individual-level approaches to regulation, and lacked comprehensive, action-based approaches. CICMH and CAMH documents can help create comprehensive, balanced approaches for harm reduction.
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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 | 0.001 | 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".