Effect of legislation on the use of bicycle helmets.
Bibliographic record
Abstract
BACKGROUND: About 50 Canadian children and adolescents die each year from bicycle-related injuries, and 75% of all bicycle-related deaths are due to head injuries. Although the use of helmets can reduce the risk of head injury by 85%, the rate of voluntary helmet use continues to be low in many North American jurisdictions. We measured compliance before, during and after 1997, when legislation making the use of helmets mandatory for cyclists was enacted in Nova Scotia. METHODS: In the summers and autumns of 1995 through 1999, trained observers who had a direct view of oncoming bicycle traffic recorded helmet use, sex and age group of cyclists in Halifax on arterial, residential and recreational roads. Sampling was done during peak traffic times of sunny days. We abstracted data from the Canadian Hospitals Injury Reporting and Prevention Program database on bicycle-related injuries treated during the same period at the Emergency Department of the IWK Health Centre, Halifax. RESULTS: The rate of helmet use rose dramatically after legislation was enacted, from 36% in 1995 and 38% in 1996, to 75% in 1997, 86% in 1998 and 84% in 1999. The proportion of injured cyclists with head injuries in 1998/99 was half that in 1995/96 (7/443 [1.6%] v. 15/416 [3.6%]) (p = 0.06). Police carried out regular education and enforcement. There were no helmet-promoting mass media education campaigns after 1997. INTERPRETATION: Rates of helmet use rose rapidly following the introduction of legislation mandating the use of helmets while bicycling. The increased rates were sustained for 2 years afterward, with regular education and enforcement by police.
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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 | 0.001 | 0.001 |
| 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".