Trends in youth use of non-cigarette tobacco products in England, Canada, and the US and the impact of England’s menthol cigarette ban on use
Bibliographic record
Abstract
England banned menthol as a characterising flavour in cigarettes (but not other tobacco products) in May 2020. Canada banned menthol as an ingredient in all tobacco products in January 2017. The US currently has no federal ban on menthol in tobacco products. Evidence suggests that England’s ban on menthol in cigarettes has reduced youth menthol cigarette smoking (doi: 10.1001/jamanetworkopen.2022.10029). However, it is possible that youth are instead using menthol non-cigarette tobacco products in England. This study therefore uses a quasi-experimental design to 1) describe trends in youth use of non-cigarette tobacco products (cigarillos, cigars, waterpipes, bidis, smokeless tobacco, and heated tobacco) in England, Canada and the US; 2) assess whether England’s May 2020 ban on menthol cigarettes (but not other tobacco products) has impacted youth use of non-cigarette tobacco products.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".