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Record W2153397505 · doi:10.1017/s1366728914000820

Minimal second language exposure, SES, and early word comprehension: New evidence from a direct assessment

2015· article· en· W2153397505 on OpenAlexaff
Stephanie De Anda, Natalia Arias‐Trejo, Diane Poulin‐Dubois, Pascal Zesiger, Margaret Friend

Bibliographic record

VenueBilingualism Language and Cognition · 2015
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsConcordia University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsComprehensionVocabularyPsychologySocioeconomic statusVocabulary developmentExtant taxonLinguisticsLanguage developmentDevelopmental psychologyMedicineEnvironmental healthPopulationBiology

Abstract

fetched live from OpenAlex

Although the extant literature provides robust evidence of the influence of language exposure and socioeconomic status (SES) on language acquisition, it is unknown how sensitive the early receptive vocabulary system is to these factors. The current study investigates effects of minimal second language exposure and SES on the comprehension vocabulary of 16-month-old children in the language in which they receive the greatest exposure. Study 1 revealed minimal second language exposure and SES exert significant and independent effects on a direct measure of vocabulary comprehension in English-dominant and English monolingual children (N = 72). In Study 2, we replicated the effect of minimal second language exposure in Spanish-dominant and Spanish monolingual children (N = 86), however no effect of SES on vocabulary was obtained. Our results emphasize the sensitivity of the language system to minimal changes in the environment in early development.

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)0.006
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.044
GPT teacher head0.330
Teacher spread0.286 · 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

Citations91
Published2015
Admission routes1
Has abstractyes

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