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Record W4213270314 · doi:10.3389/fpsyg.2022.820745

Athlete Leadership Development Within Teams: Current Understanding and Future Directions

2022· review· en· W4213270314 on OpenAlexaff
Stewart T. Cotterill, Todd M. Loughead, Katrien Fransen

Bibliographic record

VenueFrontiers in Psychology · 2022
Typereview
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPsychologyAthletesLeadership developmentShared leadershipSport psychologyApplied psychologyPublic relationsMental healthLeadership styleNeuroleadershipEngineering ethicsSocial psychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Leadership has been shown to be a fundamental factor influencing the performance of sport teams. Within these teams, leadership can be provided by coaches, formal athlete leaders, such as team captains, and other 'informal' athlete leaders. The role of the athlete leader in a team, either formal or informal, has been consistently reported over the last 10 years to have a significant impact upon a teams' functioning and effectiveness, as well as teammates' general health and mental wellbeing. As such, cultivating the provision of this leadership within a team has emerged as an important focus for managers, coaches, sport psychologists and scholars alike. While the recognition of the importance of athlete leadership is well established, there has been a lag in the development of systematic approaches to enhance and develop the leadership skills and capabilities of the athletes within sport teams. As a result, this paper seeks to review contemporary examples and current understanding of approaches to athlete leadership development. The paper will also highlight future areas for research and applied practice development.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.209
GPT teacher head0.403
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations58
Published2022
Admission routes1
Has abstractyes

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