The Incidence and Types of Physical Contact Associated with Body Checking Regulation Experience in 13–14 Year Old Ice Hockey Players
Bibliographic record
Abstract
BACKGROUND: Ice hockey has one of the highest sport participation and injury rates in youth in Canada. Body checking (BC) is the predominant mechanism of injury in leagues in which it is permitted. The objectives of this study were to determine whether the incidence and types of physical contact differ for Bantam players (aged 13-14 years) who were exposed to BC at Pee Wee level (aged 11-12 years) in Calgary, Alberta versus Bantam players who were not exposed to BC at Pee Wee level in Québec City, Québec. All teams were exposed to BC at bantam level; METHODS: A cohort study was conducted in Québec City and Calgary. Sixteen games for Calgary and 15 for Québec City were randomly selected and analysed with a validated observation system to quantify five intensities of physical contact and to observe different types of physical contact such as slashing and holding; RESULTS: A total of 5610 incidences of physical contact with the trunk and 3429 other types of physical contact were observed. Very light intensity trunk contact was more frequent in Calgary (adjusted incidence RR (ARR): 1.71; 95% CI: 1.28-2.29). Holding (ARR: 1.04; 95% CI: 1.02-1.07) and slashing (ARR: 1.38; 95% CI: 1.07-1.77) were more frequent in Calgary; CONCLUSION: RESULTS suggest that players' physical contacts differ between Bantam leagues in which BC was permitted at Pee Wee level and leagues in which it was not permitted until Bantam level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".