Bicycle helmet prevalence two years after the introduction of mandatory use legislation for under 18 year olds in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: To determine changes in helmet use in cyclists following the introduction of a bicycle helmet law for children under age 18. METHODS: Cyclists were observed by two independent observers from July to August 2004 (post-legislation) in Edmonton, Alberta. The data were compared with a similar survey completed at the same locations and days in July to August 2000 (pre-legislation). Data were collected for 271 cyclists in 2004 and 699 cyclists in 2000. RESULTS: The overall prevalence of helmet use increased from 43% (95% CI 39 to 47%) in 2000 to 53% (95% CI 47 to 59%) in 2004. Helmet use increased in those under 18, but did not change in those 18 and older. In the cluster adjusted multivariate Poisson regression model, the prevalence of helmet use significantly increased for those under age 18 (adjusted prevalence ratio (APR) 3.69, 95% CI 2.65 to 5.14), but not for those 18 years and older (APR 1.17, 95% CI 0.95 to 1.43). CONCLUSION: Extension of legislation to all age groups should be considered.
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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 | 0.000 |
| 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".