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Record W2149486861 · doi:10.1123/jsep.34.3.345

Athletes’ Perceptions of Role Ambiguity and Coaching Competency in Sport Teams: A Multilevel Analysis

2012· article· en· W2149486861 on OpenAlexaff
Grégoire Bosselut, Jean-Philippe Heuzé, Mark Eys, Paul Fontayne, Philippe Sarrazin

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2012
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCoachingPsychologyAthletesAmbiguityPerceptionApplied psychologyTeam sportMultilevel modelSocial psychologyPhysical therapyComputer science

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the relationship between athletes' perceptions of role ambiguity and two theoretically derived dimensions of coaching competency (i.e., game strategy and technique competencies). A total of 243 players from 26 teams representing various interdependent sports completed French versions of the Role Ambiguity Scale and the Coaching Competency Scale. Multilevel analyses supported the existence of relationships between the four dimensions of role ambiguity and the two dimensions of coaching competency at both individual and team levels. When the levels were considered jointly, athletes perceiving greater ambiguity in their role in both offensive and defensive contexts were more critical of their coach's capacities to lead their team during competitions and to diagnose or formulate instructions during training sessions. The results also indicated that the dimension of scope of responsibilities was the main contributor to the relationship with coaching competency at an individual level, whereas role evaluation was the main contributor to this relationship at a group level. Findings are discussed in relation to the role episode model, the role ambiguity dimensions involved in the relationships according to the level of analysis considered, and the salience of ambiguity perceptions in the offensive context.

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)0.001
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 score0.017
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.016
GPT teacher head0.333
Teacher spread0.317 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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