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Record W4281945045 · doi:10.3138/cpp.2021-064

The Youngest Bilingual Canadians: Insights from the 2016 Census Regarding Children Aged 0–9 Years

2022· article· en· W4281945045 on OpenAlexaffvenueabout
Esther Schott, Lena V. Kremin, Krista Byers‐Heinlein

Bibliographic record

VenueCanadian Public Policy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsConcordia University
Fundersnot available
KeywordsNeuroscience of multilingualismCensusIndigenousImmigrationHome languageBilingual educationGeographyFirst languageIndigenous languagePsychologyDemographyMedicineSociologyPedagogyPopulation

Abstract

fetched live from OpenAlex

In this study, we used 2016 Canadian Census data to examine home bilingualism among children aged 0–9 years. Across Canada, 18 percent of children used at least two languages at home, which rose to more than 25 percent in large cities and the Canadian territories. English and French was the most common language pair in Quebec and Ontario, and various other pairs were spoken in most provinces. In the territories, 17 percent of children spoke an Indigenous language and English, and we discuss specific opportunities and challenges for Indigenous language revitalization. The presence of bilingual adults in the home and immigration generation were the strongest predictors of children’s home bilingualism. We conclude by discussing how policies can encourage child bilingualism, such as by supporting children’s home language in early and primary education settings. Such policies must be tailored to the needs of the specific communities to optimally support bilingual children and their families.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.037
GPT teacher head0.343
Teacher spread0.305 · 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 designNot applicable
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

Citations16
Published2022
Admission routes3
Has abstractyes

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