Smokers' reactions to cigarette package warnings with graphic imagery and with only text: a comparison between Mexico and Canada
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
OBJECTIVE: This comparison of population-based representative samples of adult smokers in Canada (n=1 751) and Mexico (n=1 081) aimed to determine whether cigarette packages with graphic warning labels in Canada had a stronger impact than the text-only warning labels in Mexico. MATERIALS AND METHODS: Bivariate and multivariate adjusted models were used in this study. Results. Canadian smokers reported higher warning label salience (i.e., noticing labels & processing label messages) than Mexican smokers, and warning label salience independently predicted intention to quit. Moreover, Canadians had higher levels of knowledge about smoking-related health outcomes that were included as content on Canadian, but not Mexican, warning labels. Finally, a majority of Mexican smokers want their cigarette packs to contain more information than they currently contain. DISCUSSION: These results are consistent with other studies that indicate that cigarette packages whose warning labels contain prominent graphic imagery are more likely than text-only warning labels to promote smoking-related knowledge and smoking cessation.
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.
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 | 0.000 | 0.000 |
| 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