Intended and Unintended Effects of Banning Menthol Cigarettes
Bibliographic record
Abstract
Bans on menthol cigarettes have been recommended by the World Health Organization, adopted throughout the European Union, and proposed by the United States Food and Drug Administration (FDA), primarily due to concerns that menthol cigarettes enable youth smoking.Yet there is almost no direct evidence on their effects using real-world policy variation.We provide the first comprehensive evaluation of this policy by studying Canada where seven provinces banned menthol cigarettes prior to a nationwide menthol ban in 2018.Using provincial sales data, we show that menthol cigarette sales fell to zero immediately after menthol bans, with no meaningful effect on non-menthol sales.Survey data confirm that provincial menthol bans significantly reduced menthol cigarette smoking among both youths and adults.We also find strong evidence of substitution, however: provincial menthol bans significantly increased nonmenthol cigarette smoking among youths, resulting in no overall net change in youth smoking rates.We also document evidence of evasion: provincial menthol bans shifted smokers' cigarette purchases away from grocery stores and gas stations to First Nations reserves (where the menthol bans do not bind).Our results demonstrate the importance of accounting for substitution and evasion responses in the design of stricter tobacco regulations.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".