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Record W2038667536 · doi:10.1503/cjs.008913

Factors affecting the relative age effect in NHL athletes

2014· article· en· W2038667536 on OpenAlexaffvenueabout
Caroline Parent‐Harvey, Christophe Desjardins, Edward J. Harvey

Bibliographic record

VenueCanadian Journal of Surgery · 2014
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineLeagueDemographyAthletesEliteCompetition (biology)Physical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: The relative age effect (RAE) has been reported for a number of different activities. The RAE is the phenomena whereby players born in the first few months of a competition year are advantaged for selection to elite sports. Much of the literature has identified elite male athletics, such as the National Hockey League (NHL), as having consistently large RAEs. We propose that RAE may be lessened in the NHL since the last examination. METHODS: We examined demographic and selection factors to understand current NHL selection biases. RESULTS: We found that RAE was weak and was only evident when birth dates were broken into year halves. Players born in the first half of the year were relatively advantaged for entry into the NHL. We found that the RAE is smaller than reported in previous studies. Intraplayer comparisons for multiple factors, including place of birth, country of play, type of hockey played, height and weight, revealed no differences. Players who were not drafted (e.g., free agents) or who played university hockey in North America had no apparent RAE. CONCLUSION: We found little evidence of an RAE in the current NHL player rosters. A larger study of all Canadian minor hockey intercity teams could help determine the existence of an RAE.

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)0.003
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 score0.014
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.296
Teacher spread0.240 · 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

Citations7
Published2014
Admission routes3
Has abstractyes

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