A gender-focused multilevel analysis of how country, regional and individual level factors relate to harm from others’ drinking
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine how gender, age and education, regional prevalence of male and female risky drinking and country-level economic gender equality are associated with harms from other people's drinking. METHODS: 24,823 adults in ten countries were surveyed about harms from drinking by people they know and strangers. Country-level economic gender equality and regional prevalence of risky drinking along with age and gender were entered as independent variables into three-level random intercept models predicting alcohol-related harm. FINDINGS: At the individual level, younger respondents were consistently more likely to report harms from others' drinking, while, for women, higher education was associated with lower risk of harms from known drinkers but higher risk of harms from strangers. Regional rate of men's risky drinking was associated with known and stranger harm, while regional-level women's risky drinking was associated with harm from strangers. Gender equality was only associated with harms in models in models that did not include risky drinking. CONCLUSIONS: Youth and regional levels of men's drinking was consistently associated with harm from others attributable to alcohol. Policies that decrease the risky drinking of men would be likely to reduce harms attributable to the drinking of others.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".