Beyond light and mild: cigarette brand descriptors and perceptions of risk in the International Tobacco Control (ITC) Four Country Survey
Bibliographic record
Abstract
AIMS: To examine perceptions of risk related to type of cigarette brand. DESIGN AND SETTING: Cross-sectional findings from wave 5 of the ITC Four Country Survey, conducted with nationally representative samples of smokers in 2006. PARTICIPANTS: A total of 8243 current and former adult (≥18 years) smokers from Canada (n=2022), the United States (n=2034), the United Kingdom (n=2019) and Australia (n=2168). MEASUREMENTS: Outcomes included beliefs about the relative risks of cigarettes, including perceptions of 'own' brand. Correlates included socio-demographic, smoking-related covariates and brand characteristics. FINDINGS: One-fifth of smokers believed incorrectly that 'some cigarette brands could be less harmful' than others. False beliefs were higher in both the United States and United Kingdom compared to Canada and Australia. Smokers of 'light/mild', 'slim' and 100 mm/120 mm cigarettes were more likely to believe that some cigarettes could be less harmful [odds ratio (OR)=1.29, 95% confidence interval (CI)=1.12-1.48 and that their own brand might be a little less harmful (OR=2.61, 95% CI=2.01-3.41). Smokers of 'gold', 'silver', 'blue' or 'purple' brands were more likely to believe that their 'own brand might be a little less harmful' compared to smokers of 'red' or 'black' brands (OR=12.48, 95% CI=1.45-107.31). CONCLUSIONS: Despite current prohibitions on the words 'light' and 'mild', smokers in western countries continue to falsely believe that some cigarette brands may be less harmful than others. These beliefs are associated with descriptive words and elements of package design that have yet to be prohibited, including the names of colours and long, slim cigarettes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".