Analysis of Gender Differences in the Impact of Taxation and Taxation Structure on Cigarette Consumption in 17 ITC Countries
Bibliographic record
Abstract
Although increasing taxes has been established as the most effective tobacco control policy, it is not clear whether these policies reduce cigarette consumption equally among women and men. In this study, we examine whether the association between taxation/taxation structure and cigarette consumption differs by gender. The data is from the International Tobacco Control Policy Evaluation (ITC) Projects in 17 countries. Cigarette consumption was measured by gender for each ITC country. Generalized estimating equations (GEE) were employed to investigate gender differences in the association between cigarette consumption and tax structures, while controlling for time-variant demographic characteristics such as unemployment rates, proportions of adults, and percent of female population. Tiered tax structures are associated with higher cigarette consumption among both males and females. Female smokers are more responsive to an average tax increase than male smokers. Among males, higher ad valorem share in excise taxes is associated with lower cigarette consumption, but it is not the case for females. Females may not be as responsive to the prices raised by ad valorem taxes, despite being responsive to average taxes, suggesting that smokers by gender may face different prices.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".