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Record W3061415325 · doi:10.5296/ijsw.v7i2.17422

‘It’s Like You Are Trapped in a Small Place’: Language Skill Acquisition and Settlement Outcomes of Ageing Cambodian Refugees

2020· article· en· W3061415325 on OpenAlexafffundabout
Shamette Hepburn

Bibliographic record

VenueInternational Journal of Social Work · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsYork University
FundersYork University
KeywordsRefugeeSettlement (finance)TransnationalismImmigrationNarrativeInclusion (mineral)BureaucracySecond-language acquisitionLiteracyMultilingualismLanguage barrierDreyfus model of skill acquisitionSociologyPolitical sciencePedagogyGender studiesLinguisticsBusinessPolitics

Abstract

fetched live from OpenAlex

Language skill acquisition is one of the main challenges encountered by refugees and immigrants entering and transitioning to a new society. In Canada, adult newcomers’ language education is primarily tasked to English as a Second Language (ESL) programs. These programs aim to provide English language training, preparation for the labour market and integration into Canadian society. This paper presents findings of a larger qualitative study that explored the experiences of 15 community-dwelling Cambodian Canadians (aged 55 and older) in northwest Toronto. Drawing on critical transnationalism and postcolonialism, it examines Cambodian Canadians’ reflections on their language skill acquisition and integration vis-à-vis the education and migration regimes which form part of the resettlement bureaucracy supporting these activities and processes. Decades after participating in language education programs, ageing Cambodian Canadians’ narratives reveal that inadequate resources and support have resulted in lower than desired language skill acquisition and differential inclusion within their communities.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.333
Teacher spread0.316 · 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 designQualitative
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
Published2020
Admission routes3
Has abstractyes

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