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Record W2031283831 · doi:10.1017/s1366728913000813

Bilingualism and receptive vocabulary achievement: Could sociocultural context make a difference?

2014· article· en· W2031283831 on OpenAlexaffabout
Lisa Smithson, Johanne Paradis, Elena Nicoladis

Bibliographic record

VenueBilingualism Language and Cognition · 2014
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNeuroscience of multilingualismVocabularyPsychologyContext (archaeology)Sociocultural evolutionPeabody Picture Vocabulary TestLinguisticsSociologyGeography

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate receptive vocabulary achievement among French–English bilinguals in Canada. Standardized test scores of receptive vocabulary were measured in both languages from preschool, early-elementary, and late-elementary French–English bilingual children, and French–English bilingual adults. Mean vocabulary scores across all bilingual age groups were statistically equivalent to or above the standard mean in French and English with the exception of the early-elementary bilinguals who scored below the standard mean on the English vocabulary assessment. Mean vocabulary scores of the preschool and adult bilingual groups were not significantly different from those of their monolingual peers in either language. However, early-elementary and late-elementary bilingual children scored significantly lower than monolinguals on the English vocabulary assessment. The positive sociocultural context for French–English bilingualism in Canada as well as language input changes in school are discussed as underlying reasons for these findings.

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 score0.841
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.293
Teacher spread0.277 · 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

Citations102
Published2014
Admission routes2
Has abstractyes

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