Using the Social Identity Approach to Understand Pro-Social and Anti-Social Moral Behaviour Toward Teammates in Competitive Youth Soccer.
Bibliographic record
Abstract
The Social Identity Approach (SIA; Tafjel & Turner, 1979) provides an informative theoretical framework to understand and test how team identification can influence youth moral development. Based on the tenets of SIA and previous research, higher team identification is generally associated with adaptive behaviour toward in-group team members. This study examined the association of team identification on participants' pro-social and anti-social moral behaviour toward team members in a sample of 177 competitive youth soccer players (Mage= 14.66 years). Participants completed measures of social identity (team identification) and both pro-social and anti-social behaviour towards teammates during competition and in social situations. The Social Identity Questionnaire in Sport (SIQS; Bruner & Benson, 2018) examines three dimensions of team identification – in-group ties, in-group affect, and cognitive centrality – which were entered as individual predictors into a regression model testing the association with moral behaviour towards teammates during competition and in social situations. Regression analyses revealed in-group ties was significantly positively associated with pro-social behaviour in competition (β = .27) and in-group affect was significantly negatively associated with anti-social behaviour (competitive (β = - .30, and social (β = -.40; ps < .01). No social identity dimensions were significantly associated with pro-social behaviour in social situations. Overall, the results support the SIA and recent research (e.g., Bruner et al., 2018; McLaren et al., 2021) suggesting that a shared sense of social identity, in particular in-group ties and in-group affect, is associated with shared team goals and values (e.g., greater pro-social and reduced anti-social teammate interactions).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".