Bibliographic record
Abstract
OBJECTIVES: This article outlines smoking trends over the past 10 years among the population aged 18 or older. Factors associated with smoking cessation and relapse are examined, as well as factors associated with having no intention of quitting in the next 6 months. DATA SOURCES: Data are from the household cross-sectional and longitudinal components of Statistics Canada's National Population Health Survey (1994/95 to 2002/03) (NPHS) and from the 2000/01 and 2003 Canadian Community Health Survey (CCHS). ANALYTICAL TECHNIQUES: Trends in smoking rates were calculated using cross-sectional data from the NPHS and the CCHS. Factors associated with cessation and relapsing were examined using pooling of repeated observations over two-year periods and logistic regression based on NPHS longitudinal data from 1994/95 to 2002/03. Factors associated with having no plans to quit were examined with logistic regression, based on 2003 CCHS cross-sectional data. MAIN RESULTS: In 2003, 19% of the Canadian population aged 18 or older smoked cigarettes daily, down 7 percentage points from a decade earlier. Smoking cessation, relapsing and having no plans to quit were all associated with addiction levels, notably, cigarettes smoked per day. Smoke-free homes and workplace smoking bans were associated with reduced cigarette consumption.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".