Bullying Victimization and Perpetration Among Adolescent Sport Teammates
Bibliographic record
Abstract
PURPOSE: Bullying is a specific pattern of repeated victimization explored with great frequency in school-based literature, but receiving little attention within sport. The current study explored the prevalence of bullying in sport, and examined whether bullying experiences were associated with perceptions about relationships with peers and coaches. METHOD: Adolescent sport team members (n = 359, 64% female) with an average age of 14.47 years (SD = 1.34) completed a pen-and-paper or online questionnaire assessing how frequently they perpetrated or were victimized by bullying during school and sport generally, as well as recent experiences with 16 bullying behaviors on their sport team. Participants also reported on relationships with their coach and teammates. RESULTS: Bullying was less prevalent in sport compared with school, and occurred at a relatively low frequency overall. However, by identifying participants who reported experiencing one or more act of bullying on their team recently, results revealed that those victimized through bullying reported weaker connections with peers, whereas those perpetrating bullying only reported weaker coach relationships. CONCLUSION: With the underlying message that bullying may occur in adolescent sport through negative teammate interactions, sport researchers should build upon these findings to develop approaches to mitigate peer victimization in sport.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".