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Record W2953493809 · doi:10.1558/jmbs.10973

Language Proficiency, Use, and Maintenance among People with Vietnamese Heritage Living in Australia

2019· article· en· W2953493809 on OpenAlexaboutno aff
Sharynne McLeod, Sarah Verdon, Cen Wang, Van H. Tran

Bibliographic record

VenueJournal of Monolingual and Bilingual Speech · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseHeritage languageImmigrationPsychologyFirst languageMultilingualismGrandparentPolitical scienceSociologyGender studiesMedicineLinguisticsDevelopmental psychologyPedagogy

Abstract

fetched live from OpenAlex

Multilingualism provides cultural, economic and social benefits to individuals and societies. Many people with Vietnamese heritage have migrated to English-speaking countries such as Australia, Canada and the US. This study describes language proficiency, use and maintenance of 271 adults with Vietnamese heritage living across Australia. The majority were first-generation immigrants (76.6%), spoke Vietnamese as their first language (94.3%), and indicated Vietnamese was their most proficient language (78.5%). The majority were more likely to use Vietnamese (than English) with their mother, father, older siblings, Vietnamese-speaking grandparents, relatives in Vietnam, and Vietnamese friends. They used English and Vietnamese with their partners, children, younger siblings and English-speaking grandparents. They were more likely to speak English when working, studying and watching TV, but used English and Vietnamese equally on social media. The most important reasons for maintaining Vietnamese were: maintaining bonds with relatives, maintaining Vietnamese cultural identity, and building friendships.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.995

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 studies0.0000.000
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 head0.032
GPT teacher head0.367
Teacher spread0.335 · 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 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

Citations21
Published2019
Admission routes1
Has abstractyes

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