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Record W4402455080 · doi:10.1080/23750472.2024.2400191

Hockey referees: are they part of the solution for concussions in youth hockey?

2024· article· en· W4402455080 on OpenAlexaffabout
Robin Tharle-Oluk, Amanda M. Miles, Jeffrey G. Caron, David J. Hancock

Bibliographic record

VenueManaging Sport and Leisure · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationMemorial University of Newfoundland
Fundersnot available
KeywordsIce hockeyPsychologyAeronauticsApplied psychologyEngineeringPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Rationale/purpose Concussions pose short – and long-term risks for youth athletes. To mitigate these risks, sport organizations must find ways to enhance athlete safety, including prompt removal of athletes who display signs and symptoms of concussions. Some sport organizations have incorporated officials in concussion prevention and management strategies. The purpose of this study was to gain sport officials’ perspectives of being able to remove athletes with suspected concussion from games.Design/methodology/approach We conducted a qualitative study using semi-structured interviews with 10 ice hockey officials from across Canada. We implemented a pragmatic approach with a reflexive thematic analysis to maintain the participants’ truths and perspectives within the results.Findings Our analysis resulted in the four themes: (a) Considerations and Importance of the Protocol, (b) Officials’ Knowledge of Concussions, (c) Required Training, and (d) Barriers.Practical Implications Removing athletes with suspected concussions could be added to officials’ duties; however, hesitancy exists regarding implementation and effectiveness of the protocol. Focus on the implementation and education of the officials is required.Research Contribution This study contributes to the growing literature on sport officials and their role with respect to concussions in youth ice hockey.

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 score0.026
Threshold uncertainty score0.236

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 studies0.0000.000
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 head0.076
GPT teacher head0.326
Teacher spread0.250 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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