Unlocking the power of ‘us’: Longitudinal evidence that identity leadership predicts team functioning and athlete well-being
Bibliographic record
Abstract
The social identity approach has become an important framework for understanding effective leadership. The present study is the first to longitudinally examine the relative impact of coaches' and athlete leaders' identity leadership on athletes' identification with their team, as well as the subsequent relationships with key team and individual outcomes. To investigate these research questions, 18 sport teams (N = 279) completed a questionnaire early and late in their season competition. To analyse these data, we conducted structural equation modelling and controlled both for baseline values and the nested structure of our data. Results revealed that it was mainly the identity leadership of athlete leaders (and not of the coach) early in the season that predicted athletes' team identification later in the season. This increased team identification in turn fed into both team outcomes (i.e., task climate, team resilience, team performance) and individual outcomes (i.e., well-being, burnout, and individual performance). The mediating role of team identification suggests that by building a shared sense of 'we', athlete leaders can improve the team's effectiveness and enhance athletes' well-being. Accordingly, we conclude that empowering athlete leaders and strengthening their identity leadership skills is an important way to unlock sport teams' full potential.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".