Converging evidence for the under-reporting of concussions in youth ice hockey
Bibliographic record
Abstract
BACKGROUND: Concussions are potentially serious injuries. The few investigations of prevalence or incidence in youth ice hockey have typically relied on prospective reports from physicians or trainers and did not survey players, despite the knowledge that many athletes do not report probable concussions. OBJECTIVE: This study sought to compare concussion rates in youth ice hockey that were estimated from a variety of reporting strategies. METHODS: Rates were calculated from British Columbia Amateur Hockey Association (BCAHA) official injury reports, from direct game observation by minor hockey volunteers (such as coaches and managers), as well as from retrospective surveys of both elite and non-elite youth players. All research was conducted within the BCAHA. RESULTS: Estimates from official injury reports for male players were between 0.25 and 0.61 concussions per 1000 player game hours (PGH). Concussion estimates from volunteer reports were between 4.44 and 7.94 per 1000 PGH. Player survey estimates were between 6.65 and 8.32 per 1000 PGH, and 9.72 and 24.30 per 1000 PGH for elite and non-elite male youth hockey, respectively. CONCLUSION: It was found that concussions are considerably under-reported to the BCAHA by youth hockey players and team personnel.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".