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Record W3214877219 · doi:10.1136/bjsports-2021-ioc.199

216 Who’s keeping score? The effect of a score differential based running time rule on head impact rates in Canadian high school tackle football

2021· article· en· W3214877219 on OpenAlexaffabout
Mark Patrick Pankow, Reid A. Syrydiuk, Ash T Kolstad, Sagar Grewal, Christian A. Clermont, Christopher R. Dennison, Brent Hagel, Martin Mrázik, Carolyn A. Emery

Bibliographic record

VenuePoster presentations · 2021
Typearticle
Languageen
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsSpinal Cord Injury AlbertaAlberta Children's HospitalUniversity of AlbertaUniversity of VictoriaUniversity of Calgary
Fundersnot available
KeywordsFootballTeam sportConfidence intervalComputer sciencePsychologyAthletesSimulationPhysical therapyMedicineStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

<h3>Background</h3> Due to postulated associated long-term health issues in athletes, concussions and head impacts are of concern in tackle football. Football Canada mandated a game clock running-time rule (RTR) in the event of a second-half 35-point difference in games, citing player safety as the main rationale. <h3>Objective</h3> To examine the effectiveness of RTR on reducing game-related head impact rates in Canadian high school football using video analysis. <h3>Design</h3> Cross-sectional. <h3>Setting</h3> Calgary, Canada. <h3>Participants</h3> Players on two junior division high school teams (ages 15–16) in Calgary, Alberta were included. Fourteen games from the 2019 season (Team A: n=8, Team B: n=6) were videotaped for analyses. <h3>Assessment of Risk Factors</h3> Traditionally, the clock stops between plays until the referee signals for the clock to resume. With RTR the clock continues (except during exceptional circumstances such as injury, scores, or timeouts) in the event of a point differential of 35 points or greater in the second half of a game. <h3>Main Outcome Measurements</h3> Head impacts were reported as incidence rates (IR) [# head impacts/100 player-game-minutes (PGM) (95% confidence intervals (95% CI)]. Incidence rate ratios (IRR), offset for PGM, adjusted for game outcome (e.g., win, loss) and clustering by team game were used to compare score differential in games with and without running-time (≥35 points vs. &lt;35 points) by team unit (e.g., offense, defense). <h3>Results</h3> RTR games yielded 24% fewer plays than non-RTR games (IRR: 0.76, 95% CI: 0.68, 0.84). Head impact IR in RTR games were lower than non-RTR games for offensive units (IRR:0.80; 95% CI:0.68, 0.95) and defensive units (IRR:0.76; 95% CI:0.59, 0.99). There were no differences in special teams units. <h3>Conclusions</h3> RTR reduced game-related head impact IRs in this cohort for both offensive and defensive units. Sport governing bodies should consider the potential effect of RTR on injury and concussion rates at the youth level.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.055
GPT teacher head0.369
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes2
Has abstractyes

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