Регуляторні норми щодо сигарет зі зниженою займистістю і зменшення рівнів пожеж, а також пов'язаних із пожежами травматизму та смертності в Канаді
Bibliographic record
Abstract
BACKGROUND: On October 1, 2005, Canada became the first country to implement a nationwide cigarette fire-safety standard for Reduced Ignition Propensity (RIP) cigarettes. The aim of the paper is to estimate the impact of the RIP cigarette regulations on the number of smoking-related fires (SRF), fire injuries (SRFI), and fatalities (SRFF) in Canada.METHODS: As there are no national fire statistics data, the data from Canadian provinces were studied. The data with smoking mentioned as the source of ignition were found for four provinces and grouped into two time periods: pre-implementation (2000–2004) and post-implementation (2005–2009). Average annual indicators for each period were compared.RESULTS: In Alberta, the number of home SRF and SRFF did not change much, while small (14%) reduction was observed in SRFI. In British Columbia, the percentage of SRF in all fires decreased by 15% and the number of SRFI and SRFF declined by 41% and 49% respectively. In Ontario, the average number of SRF and SRFI per year slightly decreased; however, the number of SRFF increased. In Saskatchewan, fires caused by smokers’ materials decreased almost by half while number of fatalities and injuries decreased even to a larger extent. Most prominent was the reduction of fatalities and injuries in fires with cigarettes as the source of ignition: they decreased more than three-fold in Saskatchewan.CONCLUSION: Canadian fire statistics do not allow estimating fire loss reduction as a result of the implemented RIP cigarette regulations for the whole country. Two Canadian provinces (British Columbia and Saskatchewan) experienced substantial reduction in fires ignited by manufactured cigarettes, and a corresponding reduction in the associated fire fatalities and injuries. In Alberta, only the number of smoking fire injuries has shown some decrease. No substantial changes were observed in Ontario, probably due to high level of cigarette smuggling.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".