Peer Defending and Bullying at School: The Impact of Popularity, Resource Control Norms, and Gender
Bibliographic record
Abstract
Bullying is common in Canadian schools and harmful for victimized youth. Peer defending is an effective means of dissuading bullying in schools, but students rarely intervene on behalf of others. Popular students engage in more peer defending and bullying than other students, as their social power increases their chance of success in these interactions. Whether popular students use their power to defend or bully others may be related to the norms in their school. Specifically, popular students may be more likely to defend others in the context of high prosocial control norms, and more likely to bully others in the context of high coercive control norms. In two studies, this thesis examined whether resource control norms and gender influenced the peer defending and bullying behaviours of popular youth. Study 1 used multi-level modelling to examine the influence of resource control norms on peer defending. Results indicated that popularity was positively associated with peer defending. Further, the association between popularity and peer defending decreased for girls as prosocial control norms increased, and the association between popularity and peer defending increased with coercive control norms for boys and girls. Study 2 used multi-level modeling to examine the association between resource control norms and bullying. Popularity was positively associated with bullying. The association between popularity and bullying increased for boys as coercive control norms increased, and the association between popularity and bullying decreased with prosocial control norms. Together, these findings supported the notion that resource control norms could be targeted by antibullying interventions to promote peer defending while simultaneously dissuading bullying in schools.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".