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Record W2086354494 · doi:10.1177/1046496404268533

Athletes’ Perceptions of the Sources of Role Ambiguity

2005· article· en· W2086354494 on OpenAlexaff
Mark Eys, Albert V. Carron, Mark R. Beauchamp, Steven R. Bray

Bibliographic record

VenueSmall Group Research · 2005
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsAmbiguityPsychologyAthletesConstruct (python library)PerceptionSet (abstract data type)Social psychologyDimension (graph theory)Scope (computer science)Relevance (law)Intervention (counseling)Applied psychologyCognitive psychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The purpose of the study was to determine athletes’perceptions of the sources of role ambiguity in interactive sport teams. Athletes (N = 151; 97 females and 54 males) were asked to identify why ambiguity might exist in relation to the scope of their role responsibilities, the behaviors necessary to fulfill those responsibilities, the evaluation of their role performance, and the consequences of not successfully fulfilling their role responsibilities. Results revealed an extensive set of possible sources for each dimension of role ambiguity that emerged from the responses that included factors associated with the role sender (e.g., coach), the focal person (e.g., the athlete), and the situation. The types and frequency of factors differed among the various dimensions of ambiguity thereby lending support to the necessity of considering role ambiguity in sport as a multidimensional construct. The relevance of the results to sport and future intervention research is discussed.

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)0.004
metaresearch head score (Gemma)0.018
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 score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.087
GPT teacher head0.408
Teacher spread0.320 · 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

Citations57
Published2005
Admission routes1
Has abstractyes

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