MétaCan
Menu
Back to cohort
Record W7133012241

Specific needs in literacy & language learning of refugee children: A comparison of German and Canadian Syrian refugee families

2018· dissertation· W7133012241 on OpenAlexaffabout
Anna Cavaco Yamashita

Bibliographic record

VenueTSpace · 2018
Typedissertation
Language
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsRefugeeGermanLiteracySample (material)Language proficiencyQualitative researchLanguage acquisitionFirst language
DOInot available

Abstract

fetched live from OpenAlex

Literacy and language development and wellbeing of Syrian refugee students are influenced by many factors including educational and refugee protection policies and socio-economic influences within schools and communities. The present study examined these factors contributing to the successes and challenges in language and literacy development, both in English, the second language (L2) and Arabic, the first language (L1), of Syrian refugee children as they settle in Canada. We employed a mixed measures design, five families participated in qualitative interviews, and nine children (5 girls; M age = 134.67 months) also completed a short battery of quantitative language and literacy measures. The interviews uncovered the importance of L1 maintenance and L2 acquisition, and support systems; and results from the quantitative measures suggested that the sample was significantly behind in language and literacy development. When compared to the German sample, both samples showed L2 difficulties.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.171
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.015
GPT teacher head0.397
Teacher spread0.382 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueTSpaceSame topicEducation and experiences of immigrants and refugeesFrench-language works237,207