Keeping smoking affordable in higher tax environments via smoking thinner roll-your-own cigarettes: Findings from the International Tobacco Control Four Country Survey 2006–15
Bibliographic record
Abstract
BACKGROUND: Roll-Your-Own tobacco (RYO) use is increasingly popular in many countries: it is generally cheaper than factory-made cigarettes (FM), and smokers can further reduce costs by adjusting the amount of tobacco in each cigarette. However, the level of risk of RYO compared with FM cigarettes is similar and does not meaningfully change with cigarette weight. We assessed the weight of tobacco in RYO cigarettes across jurisdictions with differing tobacco taxes/prices and over time. METHOD: Six waves of the International Tobacco Control 4 Country longitudinal study of smokers and recent ex-smokers, providing 3176 observations from exclusive RYO users covering 2006-15, are used to calculate the weight of tobacco used in RYO cigarettes in the US, Canada, Australia, and the UK. Multilevel regression analyses were used to compare weights across countries, socio-demographic factors, and over time. RESULTS: Smokers in the UK and Australia, where tobacco is relatively expensive, show higher levels of exclusive RYO use (25.8% and 13.8% respectively) and lower mean weights of tobacco per RYO cigarette (0.51 g(sd 0.32 g) and 0.53 g(0.28 g)), compared with both Canada and especially the US (6.0% and 3.5%, and 0.76 g(0.45 g) and 1.07 g(0.51 g)). Smokers in the UK and Australia also exhibited a statistically significant year-on-year decrease in the mean weight of each RYO cigarette. CONCLUSIONS: Taxation of RYO should increase considerably in the UK and Australia so that RYO and FM cigarettes are taxed equivalently to reduce RYO attractiveness and inequalities. Other measures to reduce the price differentials, including taxing RYO solely on weight, are also discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".