MétaCan
Menu
Back to cohort

Bullying among immigrant and non‐immigrant early adolescents: School‐ and student‐level effects

2017· article· en· W2766027614 on OpenAlexafffund
Irene Vitoroulis, Katholiki Georgiades

Bibliographic record

VenueJournal of Adolescence · 2017
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsImmigrationOddsEthnic groupPsychologyPoison controlSuicide preventionInjury preventionInclusion (mineral)Developmental psychologySocial psychologyMedicineLogistic regressionSociologyEnvironmental healthGeography

Abstract

fetched live from OpenAlex

We examined the association between school immigrant concentration and bullying among immigrant and non-immigrant early adolescents, and identified potential explanatory factors. First generation immigrant students had reduced odds of victimization and perpetration in schools with high (20-60%), compared to low, levels of immigrant concentration. Second generation immigrant students had reduced odds of ethnic/racial victimization in moderately concentrated schools; while non-immigrants had increased odds in the same schools. Non-white students had increased odds of ethnic/racial victimization compared to White students. While students' sense of school belonging and perceived teacher cultural sensitivity were negatively associated with bullying, they did not account for the differential associations noted above. Results demonstrate the importance of immigrant density as a protective school characteristic for immigrant and ethnic minority youth. Additional social processes operating in schools that may explain bullying behaviors among immigrant and non-immigrant youth should be explored to inform programs for promoting inclusion in schools.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), 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

Citations60
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of AdolescenceSame topicBullying, Victimization, and AggressionFrench-language works237,207