Investigating the relationship between self-rated athlete leader behaviours and perceptions of team cohesion
Bibliographic record
Abstract
An athlete leader is defined as an athlete occupying a formal or informal role influencing team members towards achieving a common goal (Loughead et al., 2006). The majority of athlete leadership research has examined leader behaviours and cohesion from the athletes' perspective. That is, the athletes' ratings of the leadership provided to them (e.g., Price & Weiss, 2011). The purpose of the present study was to examine the association between self-rated athlete leader behaviours and perceptions of cohesion in sport teams. Athletes (N = 299) self-identified their leadership status as occupying a formal, informal, or no leadership role within their team. Next, the participants rated (a) the frequency of their own leadership behaviours using the Leadership Scale for Sports (Chelladurai & Saleh, 1980) and (b) two dimensions of cohesion (individual attractions to the group task and social) from the Group Environment Questionnaire (Carron et al., 1985). The results demonstrated that the self-rated athlete leader behaviour of social support was positively related to both individual attractions to the group-task (beta = .26, p< .001) and individual attractions to the group-social (beta = .60, p< .001). The results are discussed in terms of the implications for understanding the role of athletes in sport leadership.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".