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Record W2012300556 · doi:10.1007/s10903-014-0108-6

Do First Generation Immigrant Adolescents Face Higher Rates of Bullying, Violence and Suicidal Behaviours Than Do Third Generation and Native Born?

2014· review· en· W2012300556 on OpenAlexafffund
Kevin Pottie, Govinda P. Dahal, Katholiki Georgiades, Kamila Premji, Ghayda Hassan

Bibliographic record

VenueJournal of Immigrant and Minority Health · 2014
Typereview
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversité du Québec à MontréalMcMaster UniversityInstitute of Population and Public HealthBruyèreUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsAggressionSuicide preventionPoison controlImmigrationInjury preventionPsychologyPeer victimizationEthnic groupTurkishClinical psychologyHuman factors and ergonomicsOccupational safety and healthMedicineDevelopmental psychologyMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

We conducted a systematic review to examine first generation immigrant adolescents' likelihood of experiencing bullying, violence, and suicidal behaviours compared to their later-generation and native born counterparts, and to identify factors that may underlie these risks. Eighteen studies met full inclusion criteria. First generation immigrant adolescents experience higher rate of bullying and peer aggression compared to third generation and native counterparts. Refugee status and advanced parental age were associated with increased parent to child aggression among South East Asians. Family cohesion was associated with lower rates of violence. Suicidal ideation was lower across most immigrant adolescents' ethnicities, with the exception of Turkish and South Asian Surinamese female adolescents in the Netherlands. Bullying and peer aggression of immigrant children and adolescents and potential mitigating factors such as family cohesion warrant research and program attention by policymakers, teachers and parents.

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)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.380
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations172
Published2014
Admission routes2
Has abstractyes

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