An examination of the smoking identities and taxonomies of smoking behaviour of youth
Bibliographic record
Abstract
OBJECTIVE: To address observations that the smoking identities of youth are valid descriptors of their smoking behaviour, we examined the relationships between self-reported smoking identities, perceived levels of addiction, and established taxonomies of smoking behaviour of youth. METHOD: Cross-sectional data were collected on demographics, perceived extent of addiction to tobacco, smoking history, and self-reported smoking identity from questionnaires administered to 8225 students in British Columbia, Canada. A total of 7246 participants were categorised according to four smoking taxonomies established in the literature. Differences in perceived physical and mental addiction between smoking identity groups were calculated. The strength of the associations between the taxonomies of smoking and the smoking identity groups was also assessed. RESULTS: There were significant differences in perceived levels of physical (Kruskal-Wallis chi(2) = 3985.02, p<0.001) and mental (Kruskal-Wallis chi(2) = 4046.09, p<0.001) addiction to tobacco by the participants' self-reported smoking identity. Youth smoking identities were modestly associated with the established smoking taxonomies (Pearson C contingency coefficient = 0.64-0.72). CONCLUSION: Self-reported smoking identities appear to provide valid characterisation of the smoking behaviour of youths that complement and elaborate existing taxonomies of smoking behaviour. Questions about self-reported smoking identity should be used in conjunction with smoking behaviour taxonomies when investigating youth smoking behaviours.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".