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Record W4385952546 · doi:10.1177/17479541231193302

Exploring the use of individualized consideration by minor hockey coaches

2023· article· en· W4385952546 on OpenAlexaff
Alysha Matthews, Karl Erickson

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsYork University
Fundersnot available
KeywordsCoachingAthletesMinor (academic)PsychologyContext (archaeology)Field hockeyTransformational leadershipApplied psychologyIce hockeyMedical educationSocial psychologyPhysical medicine and rehabilitationPhysical therapyMedicineAdvertisingHumanities

Abstract

fetched live from OpenAlex

Transformational leadership has been presented as a tool for coaches to foster positive youth development. One component of this concept is individualized consideration (IC), where leaders show care through supporting their followers’ individual needs. Examining the unique context of minor hockey will provide a more nuanced and complex description of IC. Therefore, the purpose of this study is to demonstrate how minor hockey coaches consider individual differences and tailor their practice to athletes’ needs. Semi-structured qualitative interviews were conducted with 10 male minor hockey coaches whose teams consisted of 9- to 13-year-old, predominantly male, athletes. Findings show these coaches demonstrated the use of IC through three steps (a) gathering information about their athletes (e.g. engaging in interactions), (b) assessing individual needs (e.g. developmental) and (c) acting to support IC (e.g. adjusting coaching practices). Findings suggest (a) IC can be implemented to support basic and more complex needs of athletes, (b) IC can be implemented with teams of athletes and (c) the context of minor hockey is constraining the implementation of IC.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.078
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.252
GPT teacher head0.360
Teacher spread0.108 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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