Bibliographic record
Abstract
BACKGROUND: In 2002, Hockey Canada changed the age classifications for minor ice hockey. Previously, 10- and 11-year-old children played at the Atom level (no bodychecking), and 12- and 13-year-old children played at the Peewee level (bodychecking allowed). After the policy change, 11-year-old players were placed in the Peewee division with 12-year-old players; the Atom division included 9- and 10-year-old players. The objective of this study was to examine the effect that the policy change had on injuries to 11-year-old players and compare this information with injury trends among 10- and 12-year-old players. METHODS: The study location was the Capital Health region, which serves the greater Edmonton area in Alberta. Capital Health maintains a database of all emergency department visits in the region. A search of the database identified 10-, 11- and 12-year-old players admitted to 7 emergency departments with hockey-related injuries during the 2 years before and the 2 years after the policy change. We also conducted a chart review for the 11-year-old players, extracting detailed information on the nature and circumstances of their injuries for the same period. RESULTS: The rate of injuries sustained by 11-year-old children playing at the Peewee level (with bodychecking) increased significantly compared with the rate among 11-year-old players at the Atom level (rate ratio [RR] 1.9, 95% confidence interval [CI] 1.4-2.4). The rate of severe injuries was more than 2 times greater among 11-year-old Peewee players than among 11-year-old Atom players (RR 2.4, 95% CI 1.6-3.6). Injury rates among the 10-year-old players (bodychecking never allowed) and the 12-year-old players (bodychecking always allowed) changed little over the study period. INTERPRETATION: The introduction of bodychecking to 11-year-old players was associated with a large increase in injury rates. From a public health perspective, the age at which bodychecking is introduced in minor hockey should be raised.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".