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Record W2059238222 · doi:10.1177/1046496404266684

Leadership Behaviors and Multidimensional Role Ambiguity Perceptions in Team Sports

2005· article· en· W2059238222 on OpenAlexaff
Mark R. Beauchamp, Steven R. Bray, Mark Eys, Albert V. Carron

Bibliographic record

VenueSmall Group Research · 2005
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWestern UniversityUniversity of Lethbridge
Fundersnot available
KeywordsOffensiveAmbiguityPsychologyPerceptionSocial psychologyAthletesVariance (accounting)InterdependenceDimension (graph theory)Applied psychologyManagement

Abstract

fetched live from OpenAlex

The relationships between leadership behaviors and athletes’ perceptions of role ambiguity were investigated within interdependent team sports. Early to midway through their respective seasons, the degree to which coaches engaged in training and instruction and positive feedback behaviors was investigated in relation to athletes’ subsequent perceptions of multi-dimensional role ambiguity. For nonstarters, coaches’ training and instruction accounted for significant variation in offensive and defensive role consequences ambiguity as well as offensive role evaluation ambiguity. However, for starters, neither of the leadership dimensions assessed in this study could explain significant variance in any of the role ambiguity dimensions. Results are discussed in terms of theory development and further research investigating possible antecedents of multidimensional role ambiguity.

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)0.006
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.165
GPT teacher head0.426
Teacher spread0.261 · 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

Citations48
Published2005
Admission routes1
Has abstractyes

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