A Comparative Analysis of Canadian University Policies Toward Alcohol, Drugs, and Gambling Use
Bibliographic record
Abstract
ABSTRACT Objectives: Emerging adulthood remains a critical period in the participation of risky behaviors, including alcohol and substance use as well as gambling. College students are at greatest risk for participation in these risky behaviors because they are continuously exposed to multiple, drinking, substance use, and gambling environments without the support and guidance often present at home. Previous public policy studies have suggested that college and university policies might help decrease a variety of risky behaviors (eg, alcohol, substance use and gambling) among students. Although some studies have compared gambling-related policies to alcohol and substance use related policies in the United States, this has not yet been done in Canada. Thus, the current study constitutes the first Canadian comparison of college gambling policies to alcohol and substance use policies. Methods: Data were collected from 96 English and French colleges/universities across Canada adapting Shaffer et al's (2005) 15-item measure assessing the prevalence of gambling, alcohol and substance use related policies. Results: Analyses revealed significantly more schools had either an alcohol or substance use related policy (90% and 83%), compared to schools with a gambling-related policy (32%). Conclusions: The scarce prevalence of college gambling-related policies suggests that Canadian colleges and universities underestimate the risks associated with heavy participation in gambling activities. Although alcohol and substance use policies remain essential, gambling policies can have a significant influence on college student participatory behaviors. The present research suggests greater awareness and need for college and university administrators to develop appropriate gambling-related policies and programs.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".