What’s Your Cap? The Highlights and Lowlights of Developing a Research and Theory-Driven Binge Drinking Prevention Initiative on a Canadian University Campus
Bibliographic record
Abstract
Binge drinking is a serious health concern on university campuses across North America. This article examines the development of the University of Saskatchewan Student Binge Drinking Prevention Initiative (BDPI) and its grounding within the theoretical and research literature. We begin the article by establishing the rates and patterns of high-‐risk drinking among university students. Next, we review the BDPI’s formation, and its commitment to drawing upon the latest empirical evidence on prevention campaigns. We also look at the guidance that Community Coalition Action Theory provided to the BDPI’s development. Together, these approaches enabled the BDPI to be student-‐run, proactive, and account for gender and other forms of diversity. Last, the central highlights and lowlights for students involved in the BDPI’s development are shared. This paper helps fill a gap in the literature on developing coalition prevention efforts aimed at reducing high-‐risk alcohol consumption by university students.
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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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.016 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".