Longer term impact of cigarette package warnings in Australia compared with the United Kingdom and Canada
Bibliographic record
Abstract
This study examines the effects of different cigarette package warnings in Australia, Canada and the United Kingdom up to 5 years post-implementation. The data came from the International Tobacco Control Surveys. Measures included salience of warnings, cognitive responses, forgoing cigarettes and avoiding warnings. Although salience of the UK warnings was higher than the Australian and Canadian pictorial warnings, this did not lead to greater levels of cognitive reactions, forgoing or avoiding. There was no difference in ratings between the Australian and UK warnings for cognitive responses and forgoing, but the Canadian warnings were responded to more strongly. Avoidance of the Australian warnings was greater than to UK ones, but less than to the Canadian warnings. The impact of warnings declined over time in all three countries. Declines were comparable between Australia and the United Kingdom on all measures except avoiding, where Australia had a greater rate of decline; and for salience where the decline was slower in Canada. Having two rotating sets of warnings does not appear to reduce wear-out over a single set of warnings. Warning size may be more important than warning type in preventing wear-out, although both probably contribute interactively.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".