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Record W635007055 · doi:10.82308/36925

Factors affecting the job satisfaction of Canadian male university basketball coaches

2003· article· en· W635007055 on OpenAlexaboutno aff
M. J. Davies

Bibliographic record

VenueeScholarship@McGill (McGill) · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsBasketballJob satisfactionPsychologyCoachingApplied psychologySocial psychologyGeography

Abstract

fetched live from OpenAlex

The purpose of the current study was to investigate factors affecting the job satisfaction of Canadian male university basketball coaches, as it pertained to their goals and measures of success for themselves, their athletes, and their team. Semi-structured individual interviews were conducted with six university coaches. Three higher-order categories emerged: (a) personal variables, which encompassed the philosophies the participants developed based on their athletic and coaching experiences, (b) internal elements, which involved what the coaches did for their athletes' academic, athletic, and personal development and the coaches' personal development, and (c) external influences, which included tangible and measurable positive and negative factors that affected the level of satisfaction derived from the other higher order categories. These results provide a clearer understanding of factors that affect coaches' job satisfaction, as well as the goals that coaches set and how they measure success. In addition, this information may be incorporated into coach training programs.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.422
Threshold uncertainty score0.849

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.240
Teacher spread0.194 · 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
Published2003
Admission routes1
Has abstractyes

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