Update and Overview of Spinal Injuries in Canadian Ice Hockey, 1943 to 2011
Bibliographic record
Abstract
OBJECTIVE: To identify spinal injuries in Canadian ice hockey from 2006 to 2011 and to discuss data from 1943 to 2011 and impact of injury prevention programs. DESIGN: Data about spinal injuries with and without spinal cord injury in ice hockey have been collected by ThinkFirst's (now Parachute Canada) Canadian Ice Hockey Spinal Injuries Registry since 1981 through questionnaires from practitioners, ice hockey organizations, and media. SETTING: All Canadian provinces and territories. PARTICIPANTS: All registered Canadian ice hockey players. ASSESSMENT OF RISK FACTORS: Age, gender, level of play, location, mechanism of injury. MAIN OUTCOME MEASURES: Incidence, incidence rate, prevalence, and nature (morbidity) of the injuries. RESULTS: Between 2006 and 2011, 44 cases occurred, 4 (9.1%) of which were severe. The incidence in the recent years continues to be lower than the peak years. From 1943 to 2011, 355 cases have been documented, primarily males (97.7%) and cervical spine injuries (78.9%), resulting from impact with the boards (64.2%). Check or push from behind (36.0%) was still the most common cause of injury, although slightly lower during 2006 to 2011. From 1943 to 2011, Prince Edward Island, New Brunswick, and British Columbia/Yukon had the highest injury rates. Ontario and Quebec continued to show markedly different injury rates, with Ontario more than twice that of Quebec. CONCLUSIONS: Current data for 2006 to 2011 indicate that spinal injuries in ice hockey continue to occur, although still at lower rates than the peak years 1982 to 1995. It is imperative to continue educating players and team officials about spinal injury prevention and to reinforce the rules against checking or pushing from behind to reduce the incidence of these serious injuries.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.029 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".