Policy Impact on Menthol-Flavored Accessory Use: Cross-National Trends from the U.S., England, and Canada
Bibliographic record
Abstract
This project aims to investigate the trends in the use of menthol-flavored accessories and non-menthol cigarettes—across jurisdictions that have implemented different types of menthol bans. Our main goal is to assess whether there has been an increased uptake of menthol-flavored accessories to flavor factory on-menthol cigarettes in regions with different levels of restriction on menthol cigarettes. We want to compare cross-national trends from Canada, England, and the U.S. We will also compare hypothetical and actual responses to the ban (U.S.). Comparing these settings will allow for a deeper understanding on how the comprehensiveness of the ban influences consumer behavior in individuals who smoke menthol and non-menthol cigarettes. Ultimately, we want to be able to inform future flavor and accessory regulation and develop a brief report based on these trends.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".