Can Tobacco Control Be Transformative? Reducing Gender Inequity and Tobacco Use among Vulnerable Populations
Bibliographic record
Abstract
Tobacco use and exposure is unequally distributed across populations and countries and among women and men. These trends and patterns reflect and cause gender and economic inequities along with negative health impacts. Despite a commitment to gender analysis in the preamble to Framework Convention on Tobacco Control there is much yet to be done to fully understand how gender operates in tobacco control. Policies, program and research in tobacco control need to not only integrate gender, but rather operationalize gender with the goal of transforming gender and social inequities in the course of tobacco control initiatives. Gender transformative tobacco control goes beyond gender sensitive efforts and challenges policy and program developers to apply gender theory in designing their initiatives, with the goal of changing negative gender and social norms and improving social, economic, health and social indicators along with tobacco reduction. This paper outlines what is needed to progress tobacco control in enhancing the status of gendered and vulnerable groups, with a view to reducing gender and social inequities due to tobacco use and exposure.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".