Student suggestions for addressing heavy episodic drinking
Bibliographic record
Abstract
Objective This study examines student suggestions for other students, campuses, and society to address heavy episodic drinking (HED) and associated harms. Participants: Included 110 post-secondary students (27 males, 83 females), ages 17 to 30 years, from five universities across four Canadian provinces. Method: Purposeful sampling was used to screen in participants who drank in excess of Canada’s Low-Risk Alcohol Drinking Guidelines. As part of a larger study, focus groups were held with qualifying students examining HED behaviors, suggestions and potential barriers to addressing HED among post-secondary students. Results: Suggestions included providing earlier education on harms, receiving messages from respected peers and adults, and teaching how to drink in moderation. Barriers included peer pressure, not knowing own limits, and post-secondary drinking culture. Conclusions: Campuses might not be using the most effective methods to reduce HED, may be facing unknown barriers, and need to understand perspectives of students in order to reduce HED.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".