Drinking on campus: self-reports and breath tests.
Bibliographic record
Abstract
OBJECTIVE: Concern about excessive alcohol consumption by college students has been raised by surveys indicating that more than 40% of students are "heavy" drinkers. This definition is based on students' reports of consuming five or more drinks (four or more for women) on an occasion sometime during the past 2 weeks. The present survey examines the degree to which this 2-week 5+/4+ drink criterion characterizes a student's pattern of alcohol use, and whether a 5+/4+ criterion for a drinking occasion is a valid indicator of high blood alcohol concentration (BAC). METHOD: Students (N = 856, 70% male) were interviewed as they returned home between 10 PM and 3 AM. Students reported their drinking of the past 2 weeks and of the night they were interviewed, then provided breath samples to determine their BAC. RESULTS: Among the students in the sample classified as "heavy" drinkers on the basis of self-reports, 49% had zero BAC on the night they were interviewed. Those who reported consuming 5+/4+ drinks the evening of the interview had a mean BAC <0.08%. The distribution of BACs in the entire sample showed 74.4% of students had a BAC of zero and 11.8% had a BAC <0.05%. Very high BACs (i.e., > or =0.15%) were rare (1.3%). CONCLUSIONS: Self-reports of consuming 5+/4+ drinks on at least one occasion during the previous 2 weeks did not reliably identify a pattern of heavy drinking. Moreover, reports of 5+/4+ drinks on an occasion were not necessarily associated with high BACs.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".