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Record W3131041260 · doi:10.1111/imig.12829

Exploring initial school integration among Syrian refugee children

2021· article· en· W3131041260 on OpenAlex
Yan Guo, Srabani Maitra, Shibao Guo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Migration · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRefugeeSyrian refugeesRacismIdentity (music)PopulationFocus groupGender studiesPsychologySociologyPolitical scienceDemographyLaw

Abstract

fetched live from OpenAlex

Abstract This paper explores the initial integration experiences of Syrian refugee children in schools in Canada. We conducted two focus groups with twelve Syrian refugee parents and three focus groups with eighteen children. Our research shows that Syrian refugee children experienced emotional barriers while struggling with their identity as Syrian “refugees.” Their low English proficiency, English only practice in classrooms and teachers’ low expectations further exacerbated the barriers to children's school integration. Syrian refugee children not only found it difficult to make friends with local students but were also subjected to constant bullying and racism that affected their sense of belonging and connection. Our research has both local and global implications, given a global increase in refugee student population. This paper makes an important contribution to the student voice theory by integrating the voices and concerns of Syrian refugee children trying to integrate into the Canadian school system.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.356
Teacher spread0.292 · 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