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Record W2136221381 · doi:10.1123/iscj.2014-0112

Influence of Performance Enhancement and Administrative Tasks on Coaches’ Stress and Intentions to Continue

2015· article· en· W2136221381 on OpenAlexaff
Wendy M. Rodgers, Camilla J. Knight, Anne‐Marie Selzler, Ian Reade, Gregory F Ryan

Bibliographic record

VenueInternational Sport Coaching Journal · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoachingPsychologyCompetence (human resources)AutonomyConfirmatory factor analysisApplied psychologySocial psychologyStructural equation modeling

Abstract

fetched live from OpenAlex

The purposes of this study were to, (a) assess motivational experiences of performance enhancement tasks (PET) and administrative tasks (AT), and; (b) examine the relationships of emergent motivational experiences of each task type to coaches’ perceived stress and intentions to continue coaching. In total, 572 coaches completed an online survey, which assessed autonomy, competence, relatedness, and other characteristics of PET and AT, intentions to continue coaching, and perceived stress. Two separate exploratory factor analyses (EFA) were conducted, one for AT and one for PET. This was followed up with confirmatory factor analysis (CFA) and SEM to examine relationships between emerging factors and stress and intentions. The factors generated for PET reflected ideas of autonomy, time conflict, and satisfaction, and for AT also included competence, effort, and job requirements. The resulting experiences of AT and PET appear to have different influences on stress and intentions, suggesting their distinction will be important in future work examining coach retention.

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 score0.009
Threshold uncertainty score0.364

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 communication0.0000.001
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 head0.029
GPT teacher head0.285
Teacher spread0.256 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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