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 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 | 0.032 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.037 | 0.049 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".