Coaches’ Perceptions of Social Identity in Youth Sport: When Youth Athletes Think and Behave as “Us”
Bibliographic record
Abstract
This study sought to examine coaches’ perceptions of social identity among their athletes and explore the ways that they may attempt to influence its development. Semistructured interviews were conducted with 12 head coaches (Mage = 49.25 years; SD = 6.5 years; Mexperience = 15.75 years; SD = 7.66 years; nfemale = 1) of male (n = 8) and female (n = 4) competitive youth ice hockey teams. Three main themes were identified through our analysis. First, the coaches’ perceptions of athletes’ social identities were described through examples of peer connection and similarity (i.e., in-group ties), athletes’ experience of positive affect (i.e., in-group affect), and athletes demonstrating the meaning and value that they attribute to team membership (i.e., cognitive centrality). Second, the coaches discussed a variety of ways that they sought to develop and reinforce a shared social identity within their teams. These behaviors aligned with principles advanced within the social identity leadership literature—namely, the coaches acted as in-group prototypes, in-group champions, entrepreneurs of identity, and embedders of identity. Finally, the coaches identified parents and cliques as key social agents with the ability to undermine social identity development. The findings are discussed in relation to both their theoretical and practical implications.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".