The GENAHTO Project (Gender and Alcohol’s Harm to Others): Design and Methods for a Multinational Study of Alcohol’s Harm to Persons Other than the Drinker
Bibliographic record
Abstract
AIMS: Most alcohol research has focused on how drinking harms the drinker. Research on alcohol's harms to others (AHTO) has studied primarily single or small groups of countries. This article describes the methodology of a new multinational study - GENAHTO - of how social and cultural contexts are related to AHTO, from the perspectives of both perpetrators and victims. DESIGN: of AHTO. The countries surveyed vary widely in alcohol policies, drinking cultures, gender-role definitions, and socioeconomic conditions. PARTICIPANTS: More than 140,000 men and women, aged 15-84, participated in the surveys. MEASURES: Individual-level measures include demographics, alcohol use patterns, and alcohol-related harms. Regional- and societal-level measures include socioeconomic conditions, drinking patterns, alcohol policies, gender inequality, and income inequality. FINDINGS: The project seeks to identify characteristics of AHTO victims and perpetrators; within-country regional differences in AHTO; and associations between national alcohol polices and individual and regional levels of AHTO. CONCLUSIONS: GENAHTO is the first project to assess AHTO in diverse societies. Its findings can inform policies to abate AHTO in varying cultural contexts.
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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 | 0.036 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".