Effect of a lockout of professional ice hockey players on injuries among minor league players
Bibliographic record
Abstract
Objective Based on the assumption that professional hockey is violent and that this influences the behaviour of children viewing it on TV, we investigated whether the absence of televised National Hockey League ice hockey games during a 1-year lockout reduced the rate of injuries of minor league hockey players in Canada. Methods This natural experiment enabled us to use a quasi-experimental design to compare injuries suffered during the NHL lockout year with those in the seasons before and after. Data regarding the injuries came from a Canadian injury surveillance program (CHIRPP) while denominators, total numbers of registered players, came from Hockey Canada. Results During the prelockout year the number and rates of injuries were as follows: 2153 (7.1, 95% CI 6.8 to 7.4, per 1000); during the lockout season they were 2215 (7.4, 95% CI 7.1 to 7.7, per 1000); and during the following year they were 2262 (7.0, 95% CI 6.7 to 7.3, per 1000). There were more severe injuries (concussions or fractures of long bones) and more injuries due to penalised acts during the NHL lockout year but the differences were not statistically significant. Conclusions These findings suggest that children are not influenced by viewing professional hockey. It may even be the case that when young players are not exposed to the consequences of aggressive play resulting in severe injuries etc. they become less fearful and more aggressive.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".