Housewife or working mum-each to her own? The relevance of societal factors in the association between social roles and alcohol use among mothers in 16 industrialized countries
Bibliographic record
Abstract
AIMS: To investigate whether differences in gender-income equity at country level explain national differences in the links between alcohol use, and the combination of motherhood and paid labour. DESIGN: Cross-sectional data in 16 established market economies participating in the Gender, Alcohol and Culture: An International Study (GenACIS) study. SETTING: Population surveys. PARTICIPANTS: A total of 12,454 mothers (aged 25-49 years). MEASUREMENTS: Alcohol use was assessed as the quantity per drinking day. Paid labour, having a partner, gender-income ratio at country level and the interaction between individual and country characteristics were regressed on alcohol consumed per drinking day using multi-level modelling. FINDINGS: Mothers with a partner who were in paid labour reported consuming more alcohol on drinking days than partnered housewives. In countries with high gender-income equity, mothers with a partner who were in paid labour drank less alcohol per occasion, while alcohol use was higher among working partnered mothers living in countries with lower income equity. CONCLUSION: In countries which facilitate working mothers, daily alcohol use decreases as female social roles increase; in contrast, in countries where there are fewer incentives for mothers to remain in work, the protective effect of being a working mother (with partner) on alcohol use is weaker. These data suggest that a country's investment in measures to improve the compatibility of motherhood and paid labour may reduce women's alcohol use.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".