Who Drinks Most of the Total Alcohol in Young Men—Risky Single Occasion Drinking as Normative Behaviour
Bibliographic record
Abstract
AIMS: The objectives of this study were to analyse (a) the distribution of risky single-occasion drinking (RSOD) among 19-year-old men in Switzerland and (b) to show the percentage of all alcohol consumption in the form of RSOD. METHODS: The study was based on a census of Swiss francophone 19-year-old men consecutively reporting for processing. The study was conducted at Army Recruitment Center. The participants were 4116 recruits consecutively enrolling for mandatory army recruitment procedures between 23 January and 29 August in 2007. The measures were alcohol consumption measured in drinks of approximately 10 g of pure alcohol, number of drinking occasions with six or more drinks (RSOD) in the past 12 months and a retrospective 1 week drinking diary. RESULTS: 264 recruits were never seen by the research staff, 3536 of the remaining 3852 conscripts completed a questionnaire which showed that 7.2% abstained from alcohol and 75.5% of those drinking had an RSOD day at least monthly. The typical frequency of drinking was 1-3 days per week on weekends. The average quantity on weekends was about seven drinks, 69.3% of the total weekly consumption was in the form of RSOD days, and of all the alcohol consumed, 96.2% was by drinkers who had RSOD days at least once a month. CONCLUSION: Among young men, RSOD constitutes the norm. Prevention consequently must address the total population and not only high-risk drinkers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".