Norm Misperception and Witnessing Bullying: The Role of Individual and Contextual Characteristics
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that when young people witness bullying, perceived social norms of their peer group affect their behavior. However, few studies have examined the specificity of norm misperception (i.e., overestimation of peer antisocial responses and the underestimation of prosocial responses relative to the objective group norm) on specific witness responses (joining in, bystanding or active defending). OBJECTIVE: The present study analyzed the effect of norm misperception on witnessing bullying behaviors, as well as the moderating role of individual (gender and deviant peer pressure) and contextual characteristics (classroom descriptive norms). METHODS: = 12.31; SD = 1.08; 87 classrooms from 13 middle schools). RESULTS: The results show that young people who overestimate classmates' pro-bullying behaviors are more likely to nominate pro-bullying responses themselves, with higher effects in boys, and those adolescents with higher deviant peer pressure and in classrooms with higher pro-bullying. Overestimations of classmates' passive bystander behaviors was associated with more individual bystanding, with higher effects in boys. Underestimations of classmates' defending was associated with lower individual defending, with higher effects in those adolescents in classrooms with lower defending. This knowledge provides valuable empirical insights for developing bullying interventions to work adolescents' misperceptions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".