Athlete Leadership as a Shared Process: Using a Social-Network Approach to Examine Athlete Leadership in Competitive Female Youth Soccer Teams
Bibliographic record
Abstract
The present study sought to address 2 limitations of previous athlete-leadership research: (a) Researchers have predominantly examined the shared nature of athlete leadership using aggregated approaches, which has limited our ability to examine differences in the degree of sharedness between teams, and (b) the limited availability of research related to dyadic predictors (i.e., qualities of the relation between 2 individuals) of athlete leadership. Therefore, social-network analysis was used to examine athlete leadership across multiple levels (i.e., individual, dyadic, and network) in 4 competitive female youth soccer teams ( N = 68). Findings demonstrated differences in the degree to which athlete leadership was shared between the teams. Furthermore, multiple-regression quadratic-assignment procedures showed that skill nomination and formal leadership status were significant predictors of how often participants reported looking to their teammates for leadership.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.006 |
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; both teacher heads agree on what is shown here.
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".