Women and tobacco: a call for including gender in tobacco control research, policy and practice
Bibliographic record
Abstract
OBJECTIVES: Female smoking is predicted to double between 2005 and 2025. There have been numerous calls for action on women's tobacco use over the past two decades. In the present work, evidence about female tobacco use, progress, challenges and ways forward for developing gendered tobacco control is reviewed. METHODS: Literature on girls, women and tobacco was reviewed to identify trends and determinants of tobacco use and exposure, the application of gender analysis, tobacco marketing, the impact of tobacco control on girls and women and ways to address these issues particularly in low-income and middle-income countries. RESULTS: Global female tobacco use is increasingly complex, involving diverse products and factors including tobacco marketing, globalisation and changes in women's status. In high-income countries female smoking is declining but is increasingly concentrated among disadvantaged women. In low-income and middle-income countries the pattern is more complex; in several regions the gap between girls' and boys' smoking is narrow. Gendered analyses and approaches to tobacco control are uncommon, especially in low-income and middle-income countries. CONCLUSIONS: Tobacco control has remained largely gender blind, with little recognition of the importance of understanding the context and challenges of girl's and women's smoking and secondhand smoke exposure. There has been little integration of gender considerations in research, policy and programmes. The present work makes a case for gender and diversity analyses in tobacco control to reflect and identify intersecting factors affecting women's tobacco use. This will help animate the WHO Framework Convention on Tobacco Control's concern for gender specificity and women's leadership, and reduce the impact of tobacco on women.
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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 | 0.115 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.049 |
| Scholarly communication | 0.022 | 0.038 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.019 | 0.034 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".