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Record W4414145538 · doi:10.31234/osf.io/ngw4s_v1

Understanding Refugee Parent-Child Discrepancies in Reporting Socio-Emotional Well-Being

2025· preprint· en· W4414145538 on OpenAlexfundaboutno aff
Yuying Huang, Hamza Qayumi, Kaja Kinga Jasińska

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsRefugeeAcculturationDisplaced personCultural sensitivitySyrian refugeesCultural diversity

Abstract

fetched live from OpenAlex

Canada has welcomed over 100,000 Syrian refugees since 2015, many of whom have faced displacement-related challenges that shape their socio-emotional well-being. Refugee children, in particular, are at heightened risk for socio-emotional difficulties due to their developmental sensitivity to adversity, exposure to traumatic events, and resettlement stressors. Assessing children’s socio-emotional well-being often relies on both parent-reports and child self-reports; however, discrepancies between these reports commonly occur, and the factors influencing such discrepancies are not well understood, particularly in displaced populations. The present study examined predictors of parent-child discrepancies in reports of socio-emotional well-being and explored whether such discrepancies were associated with children’s learning outcomes. Participants were Syrian refugee children (N = 55, Mage = 14.42) who were resettled in Canada for an average of six years. Results revealed that children consistently self-reported more socio-emotional problems than their parents reported. Moreover, longer time resettled in Canada predicted greater parent-child discrepancies, suggesting that resettlement-related factors and acculturation influence parent-child discrepancies. However, child self-reports, but not parent-reports, showed limited external validity; while parent-child communication barriers may contribute to discrepancies, differences in how socio-emotional constructs are understood and reported by parents and children are important to consider. These findings underscore the importance of including multiple informants in socio-emotional well-being assessments and carefully considering cultural and contextual factors when designing assessments, specifically given the complex dynamics in displaced families. Future research is important to advance the literature to determine whether assessments of socio-emotional well-being should be adapted for specific populations, as suggested by the present findings.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.456
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.387
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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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