MétaCan
Menu
Back to cohort
Record W4414077636 · doi:10.1002/rrq.70126

Refugee Displacement and Migration Impact Cross-Linguistic Transfer Between Arabic and English: Insights from Syrian Refugees

2025· article· en· W4414077636 on OpenAlexfundaboutno aff
Sarah Akkad, Kaja Kinga Jasińska

Bibliographic record

VenueReading Research Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsRefugeeDisplacement (psychology)Context (archaeology)Syrian refugeesArabicReading (process)Forced migrationLiteracy

Abstract

fetched live from OpenAlex

ABSTRACT The role of migration experiences on first language (L1) and second language (L2) literacy and cross‐linguistic transfer in refugee foreign language learners has recently received attention, but remains empirically underspecified. We investigated (1) migration‐related ecological predictors of L1 reading; (2) within‐ and across‐language predictors of reading; and (3) migration‐related ecological moderators of cross‐linguistic transfer from L1 phonological awareness (PA) to L2 reading. Our sample included 81 Syrian refugees between 9 and 18 years old who resettled in Canada. Displacement in an Arabic‐speaking country, shorter displacement durations, and older ages of L2 acquisition (L2 AoA) were associated with better L1 reading. Cross‐linguistic transfer of PA to reading was overall greater in the L2‐L1 direction, and migration experiences associated with better L1 reading were also associated with greater transfer in the L1‐L2 direction. These findings highlight the need to understand refugees' biliteracy in the context of their migration experiences.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.028
GPT teacher head0.438
Teacher spread0.410 · 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.

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

Explore more

Same venueReading Research QuarterlySame topicEducation and experiences of immigrants and refugeesFrench-language works237,207