The impact of cigarette package design on perceptions of risk
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: More than 40 countries have laws prohibiting misleading information from tobacco packages, including the words 'light', 'mild' and 'low-tar'. Little is known about the extent to which other words and package designs prove misleading to consumers. METHODS: A mall-intercept study was conducted with adult smokers (n = 312) and non-smokers (n = 291) in Ontario, Canada. Participants viewed pairs of cigarette packages that differed along a single attribute and completed ratings of perceived taste, tar delivery and health risk. RESULTS: Respondents were significantly more likely to rate packages with the terms 'light', 'mild', 'smooth' and 'silver' as having a smoother taste, delivering less tar and lower health risk compared with 'regular' and 'full flavor' brands. Respondents also rated packages with lighter colors and a picture of a filter as significantly more likely to taste smooth, deliver less tar and lower risk. Smokers were significantly more likely than non-smokers to perceive brands as having a lower health risk, while smokers of light and mild cigarettes were significantly more likely than other smokers to perceive brands as smoother and reducing risk. Perceptions of taste were significantly associated with perceptions of tar level and risk. CONCLUSION: The findings suggest that current regulations have failed to remove misleading information from tobacco packaging.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it