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Record W4411295714 · doi:10.1002/jad.70003

Norm Misperception and Witnessing Bullying: The Role of Individual and Contextual Characteristics

2025· article· en· W4411295714 on OpenAlexaff
Antonio Camacho, Kevin Runions, Rosario Ortega Ruiz, Eva M. Romera

Bibliographic record

VenueJournal of Adolescence · 2025
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsHamilton Health SciencesMental Health Research Canada
FundersUniversidad de Córdoba
KeywordsPsychologyNorm (philosophy)Social psychologyDevelopmental psychologyEpistemology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.284
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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