MétaCan
Menu
Back to cohort
Record W1578952521 · doi:10.24095/hpcdp.33.2.01

Influence of viewing professional ice hockey on youth hockey injuries

2013· article· en· W1578952521 on OpenAlexafffundvenueabout
Glenn Keays, Barry Pless

Bibliographic record

VenueChronic diseases and injuries in Canada · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Children's Hospital
FundersHealth Canada
KeywordsIce hockeyLeagueMinor (academic)AttendanceLock (firearm)PsychologyAdvertisingMedicineEngineeringPolitical scienceBusinessPhysical medicine and rehabilitationLaw

Abstract

fetched live from OpenAlex

INTRODUCTION: Most televised National Hockey League (NHL) games include violent body checks, illegal hits and fights. We postulated that minor league players imitated these behaviours and that not seeing these games would reduce the rate of injuries among younger hockey players. METHODS: Using a quasi-experimental design, we compared 7 years of televised NHL matches (2002-2009) with the year of the NHL lock-out (2004/2005). Data from the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) were used to identify the injuries and to ascertain whether they were due to intentional contact and illegal acts including fights. RESULTS: We found no significant differences in the proportions of all injuries and those involving intentional contact, violations or illegal acts among male minor league hockey players during the year when professional players were locked out and the years before and after the lock-out. CONCLUSION: We concluded that not seeing televised NHL violence may not reduce injuries, although a possible effect may have been obscured because there was a striking increase in attendance at equally violent minor league games during the lock-out.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.304
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2013
Admission routes4
Has abstractyes

Explore more

Same venueChronic diseases and injuries in CanadaSame topicGun Ownership and Violence ResearchFrench-language works237,207