Deadly in pink: the impact of cigarette packaging among young women
Bibliographic record
Abstract
BACKGROUND: This study sought to examine the impact of cigarette packaging on young women, including the impact of 'plain' packaging. METHODS: Participants were randomised to view eight cigarette packs designed according to one of four experimental conditions: fully-branded female brands; the same brands without descriptors (eg, 'slims'); the same brands without brand imagery or descriptors (ie, 'plain' packs); and fully branded non-female brands as a control condition. Participants rated packs on perceived appeal, taste, tar, health risks and smoker 'traits'. RESULTS: Fully-branded female packs were rated as significantly more appealing than 'no descriptor' packs, 'plain' packs and non-female branded packs. Female branded packs were associated with a greater number of positive attributes including glamour, slimness and attractiveness, compared to brands without descriptors and 'plain' packs. Women who viewed plain packs were less likely to believe that smoking helps people control their appetite--an important predictor of smoking among young women--compared to women who viewed branded female packs. CONCLUSIONS: 'Plain' packaging--removing colours and design elements--and removing descriptors such as 'slims' from packs may reduce brand appeal and thereby susceptibility to smoking among young women.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".