An Economic Evaluation of Disallowing Body Checking in 11- to 12-Year-Old Ice Hockey Leagues
Bibliographic record
Abstract
BACKGROUND: After a national policy change in 2013 disallowing body checking in Pee Wee ice hockey games, the rate of injury was reduced by 50% in Alberta. However, the effect on associated health care costs has not been examined previously. HYPOTHESIS: A national policy removing body checking in Pee Wee (ages 11-12 years) ice hockey games will reduce injury rates, as well as costs. STUDY DESIGN: Cost-effectiveness analysis alongside cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: A cost-effectiveness analysis was conducted alongside a cohort study comparing rates of game injuries in Pee Wee hockey games in Alberta in a season when body checking was allowed (2011-2012) with a season when it was disallowed after a national policy change (2013-2014). The effectiveness measure was the rate of game injuries per 1000 player-hours. Costs were estimated based on associated health care use from both the publicly funded health care system and privately paid health care cost perspectives. Probabilistic sensitivity analysis was conducted using bootstrapping. RESULTS: Disallowing body checking significantly reduced the rate of game injuries (-2.21; 95% CI [-3.12, -1.31] injuries per 1000 player-hours). We found no statistically significant difference in public health care system (-$83; 95% CI [-$386, $220]) or private health care costs (-$70; 95% CI [-$198, $57]) per 1000 player-hours. The probability that the policy of disallowing body checking was dominant (with both fewer injuries and lower costs) from the perspective of the public health care system and privately paid health care was 78% and 92%, respectively. CONCLUSION: Given the significant reduction in injuries, combined with lower public health care system and private costs in the large majority of iterations in the probabilistic sensitivity analysis, our findings support the policy change disallowing body checking in ice hockey in 11- and 12-year-old ice hockey leagues.
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".