Getting over the patriarchal barriers: women's management of men's smoking in Chinese families
Bibliographic record
Abstract
Chinese family is a patriarchal power system. How the system influences young mothers' agency in managing family men's smoking is unknown. Applying a gender lens, this ethnographic study explored how mothers of young children in Chinese extended families reacted to men's smoking. The study sample included 29 participants from 22 families. Semi-structured interviews and field observations were transcribed and analysis was conducted using open coding and constant comparison. The findings indicate that young mothers' interventions to reduce family men's home smoking were mediated by gendered relationships between the mothers and the smokers. The mothers could directly confront their husbands' smoking, although they were more conservative about their men's smoking in the presence of other family smokers. They experienced difficulty in directly confronting senior family men's smoking but found ways to skirt patriarchal constraints, either by persuading seniors to stop smoking in subtle ways, or more importantly, by using other non-smoking family members as 'mediators' to influence senior men's smoking. While future smoking cessation interventions should support mothers in protecting their children from tobacco smoke, the interventions should also include other family members who are in a better power position, particularly the grandparents of the children, to reduce home smoking.
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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 | 0.006 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".