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Record W4414874388 · doi:10.1037/dev0002072

The role of refugee children’s host country language in their resilience to resettlement: A longitudinal and within-family study on Syrian children’s early adaptation in Canada.

2025· article· en· W4414874388 on OpenAlexaffabout
S. WANG, Redab Al‐Janaideh, Xi Chen, Johanne Paradis, Adriana Soto‐Corominas, Alexandra Gottardo, Irene Vitoroulis, Jennifer M. Jenkins

Bibliographic record

VenueDevelopmental Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of OttawaWilfrid Laurier UniversityUniversity of AlbertaMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsRefugeeSiblingPsychological resilienceMental healthMultilevel modelCompetence (human resources)Family resilienceLongitudinal studyParenting styles

Abstract

fetched live from OpenAlex

One hundred twenty-six children (between 6 and 13 years) in 71 families who were resettled in Canada, as a result of the Syrian Civil War, were followed up over 3 years, using a sibling comparison, longitudinal design. This design allowed us to test the hypothesis that host country receptive language competence (L2) protects refugee children's mental health in families with limited resources (low parental education, large family size). The sibling comparison design unconfounded within- and between-family processes. Results using multilevel growth curve modeling showed that children's externalizing behavior started high and decreased over the 3 years of study. Receptive L2 was found to protect refugee children from the risks of low parental education and large family size while ruling out the possibility that this protective process occurred between families. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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)0.001
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 score0.497
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.303
Teacher spread0.291 · 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 routes2
Has abstractyes

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