Prevalence of behaviors related to cigarette-caused fires: a survey of Ontario smokers
Bibliographic record
Abstract
OBJECTIVE: To identify the prevalence and correlates of behaviors related to the risk of cigarette-caused fires. DESIGN AND SETTING: Random-digit-dialed telephone survey in Ontario, Canada, July-September, 2005. SUBJECTS: 596 current cigarette smokers. OUTCOME MEASURES: Prevalence of fire-risk events and behaviors such as burning clothing or objects in the home, leaving lit cigarettes unattended, dozing while smoking, and smoking in bed and correlates of these behaviors. Respondents were also asked if they ever worry about cigarette-caused fires. RESULTS: One in four smokers admitted to leaving lit cigarettes unattended in the last 30 days, while 15% admitted to smoking while in bed. Leaving lit cigarettes unattended was independent of demographic, socioeconomic or nicotine dependence indicators, but was related to worry about burning other persons with a cigarette (OR 1.72, 95% CI 1.04 to 2.85) and smoking inside the home (OR 2.98, 95% CI 1.66 to 5.35). Persons who were not white (OR 3.97, 95% CI 1.80 to 8.80), aged 18-24 years (OR 3.75, 95% CI 1.41 to 9.96), who had high nicotine dependence (OR 9.13, 95% CI 2.22 to 37.52) and worried about burning objects in their home (OR 2.43, 95% CI 1.31 to 4.52) were more likely to smoke in bed. 10 (1.7%) smokers reported having ever had a fire in their home started by a cigarette. CONCLUSIONS: Smokers engage in behaviors such as smoking in bed and leaving lit cigarettes unattended that may place them at an increased risk of cigarette-caused fires. As governments move to regulate cigarette ignition propensity, it is important to establish surveillance for behaviors related to fire risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".