The potential effectiveness of warning labels on cigarette packages: the perceptions of young adult Canadians.
Bibliographic record
Abstract
BACKGROUND: Since 1989 when health warning labels appeared on Canadian cigarette packages, the labels have changed from text only covering less than one quarter of the package to text and graphics covering over half the package. This study examines how Canadians in their 20s feel about the current graphic warning labels and their potential to prevent smoking and encourage quitting. METHODS: Participants between 20 and 24 years of age were part of a 10-year cohort study begun when the group was in Grade 6, with the purpose of examining factors that may affect smoking. Five questions about warning labels were added to the 2002 questionnaire requesting information on perceptions of the labels and their potential impact on smoking behaviours of young adults. One item had been included in previous questionnaires. RESULTS: 32.8% (n = 1267) of the respondents were smokers, with males (35.6%) being more likely to smoke than females (30.4%). Current smokers were less likely than experimental/ex-smokers to believe that warning labels with stronger messages would make people their age less likely to smoke. Female current smokers were more likely to think about quitting. CONCLUSION: Despite the efforts taken in developing the labels, some young adults are skeptical about their effects. Warning labels may have to be modified to target issues that are relevant to young adults; gender differences are important in this modification. Warning labels can offer an additional component to a comprehensive tobacco control program, in that they provide health information.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".