EVALUATION OF THE EFFECT OF POLICY CHANGE ON PHYSICAL CONTACTS IN YOUTH ICE HOCKEY USING VIDEO ANALYSIS
Bibliographic record
Abstract
Background Policy disallowing body checking in youth ice hockey significantly reduces the risk of injury and concussion. Based on video analysis, frequency and intensity of player to player physical contacts (PCs) are higher in Pee Wee players (ages 11–12) in leagues allowing body checking, however this has not been examined in Bantam leagues (ages 13–14). Objective To determine the association between body checking policy and the frequency and intensity of physical contacts in Bantam ice hockey players (ages 13–14). Design Cohort study. Setting Ice hockey arenas. Participants Thirteen non-elite (lowest 60% by division of play) Bantam ice hockey games in Calgary, Alberta, Canada (2014–15 season) and 13 non-elite games in Vancouver, British Columbia, Canada (2014–15 season) were videotaped. Intervention Policy allowed body checking in Calgary and not Vancouver in the non-elite levels (2014–15). Main Outcome Measurements Incidence rate ratios [IRRs] (adjusted for player position) were estimated using multiple Poisson regression to examine the effect of body checking policy on player-to-player PCs [levels 1–5 with increasing intensity (levels correspond to 4–5 body checking)] and hooking/slashing behaviours. Results Lower rates of higher intensity contacts (levels 4–5 body checking) were observed in Bantam ice hockey players in a league where body checking was disallowed [IRR=0.09; 95% CI: 0.05–0.15]. Players in a league where body checking was disallowed, however, had significantly higher rates of hooking and slashing behaviours [IRR=1.81; 95% CI: 1.33–2.47]. Conclusions Bantam ice hockey players in a league where policy disallowed body checking are at a lower risk of high intensity physical contacts, but commit higher rates of hooking and slashing behaviours. This research informs the mechanisms explaining injury risk reduction related to body checking policy change and have important national public health implications for policy decisions related to rule enforcement in youth sport.
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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 | 0.016 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".