Mandatory helmet legislation and children's exposure to cycling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Mandatory helmet legislation for cyclists is the subject of much debate. Opponents of helmet legislation suggest that making riders wear helmets will reduce ridership, thus having a negative overall impact on health. Mandatory bicycle helmet legislation for children was introduced in Ontario, Canada in October 1995. The objective of our study was to examine trends in children's cycling rates before and after helmet legislation in one health district. SETTING: Child cyclists were observed at 111 preselected sites (schools, parks, residential streets, and major intersections) in the late spring and summer of 1993-97 and in 1999, in a defined urban community. PARTICIPANTS: Trained observers counted the number of child cyclists. The number of children observed in each area was divided by the number of observation hours, resulting in the calculation of cyclists per hour. MAIN OUTCOME MEASURE: A general linear model, using Tukey's method, compared the mean number of cyclists per hour for each year, and for each type of site. RESULTS: Although the number of child cyclists per hour was significantly different in different years, these differences could not be attributed to legislation. In 1996, the year after legislation came into effect, average cycling levels were higher (6.84 cyclists per hour) than in 1995, the year before legislation (4.33 cyclists per hour). CONCLUSION: Contrary to the findings in Australia, the introduction of helmet legislation did not have a significant negative impact on child cycling in this community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it