Does social identity predict cognitions, intentions, and behaviours in youth athletes?
Bibliographic record
Abstract
Identity derived from group membership is termed social identity (SI; Tajfel & Turner, 1979), and is often conceptualized as involving three components: in-group ties (feelings of closeness and belonging), cognitive centrality (importance of membership), and in-group affect (feelings associated with membership; Cameron, 2004). Preliminary research in youth sport has demonstrated that the degree to which adolescents identify with their teams can influence both cognitions (e.g., perceptions of cohesion) and behaviours (e.g., pro- and anti-social behaviour; Bruner et al., 2014). In the current study, we sought to extend this literature by determining its predictability for cognitions (e.g., self-worth), intentions (e.g., commitment), and behaviours (e.g., effort) in youth athletes. In total, 303 athletes (Mage = 14.89, SD = 1.77; 133 females) from 26 interdependent sport teams (e.g., football, rugby, basketball, baseball, volleyball) completed questionnaires at two time points (T1 – social identity; T2 – self-worth, commitment, effort) during their athletic season. Multilevel analyses indicated that at level one (i.e., individual level), in-group ties predicted perceived effort (b = 0.14, p = .01) and commitment (b = 0.14, p < .001), whereas in-group affect predicted commitment (b = 0.25, p = .001) and self-worth (b = 0.96, p = .04). At level two (i.e., team level), team means for in-group ties predicted commitment (b = 0.32, p < .001) and self-worth (b = 2.40, p = .03). Social identity accounted for an overall variance of 3% for self-worth, 4% for effort, and 15% for commitment. Results indicate the influential role that identifying with a team can have on individual cognitions, intentions, and behaviours.Acknowledgments: Funding from the Alberta Centre for Child, Family, and Community Research
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".