Implementation of an all-ages mandatory helmet policy for ice skating
Bibliographic record
Abstract
Ice skaters sustain a significant number of head injuries each winter. We are the first to implement an all-ages helmet policy at a university-based Canadian arena. We report our experience from a cross-sectional observational study as well as the policy's consequences on helmet use and skating participation. Educational programming was provided prior to policy implementation. Observations of helmet use, falls and skater demographics were conducted prior to education/implementation and after policy implementation. The number of skaters observed was essentially unchanged by the policy; 361 skaters were observed pre-implementation, while 358 were observed post-implementation during the same number of observation-hours. Pre-implementation, helmet use ranged from 97% among children under 12 to 10% among adults; post-implementation use in all skaters was 99%. Falls were observed among all age groups, with preponderance among those aged 4-12. An all-ages helmet policy was successful both in achieving helmet use among all skaters and in maintaining participation rates.
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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 | 0.000 | 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".