MétaCan
Menu
Back to cohort
Record W4247079110 · doi:10.1121/1.4784734

Language preference in monolingual and bilingual infants.

2009· article· en· W4247079110 on OpenAlexaff
Linda Polka, Ayasha Valji, Karen Mattock

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2009
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsActive listeningPreferenceFirst languageLinguisticsPsychologyNeuroscience of multilingualismCommunicationMathematics

Abstract

fetched live from OpenAlex

Previous research shows that infants in single-language families have some basic language discrimination abilities at birth which improve rapidly over the first 6 months of life, and that attention to the rhythmic properties of language supports these skills. Babies in monolingual families also prefer listening to their native language over an unfamiliar language when presented samples produced by one bilingual or two monolingual talkers. In this study we investigate the emergence of language-specific speech processing in bilingual infants by comparing language preference patterns in monolingual English, monolingual French, and bilingual English-French infants using a three-way language preference test. Listening times were measured to passages of adult-directed speech from three rhythmically different languages (English, French, Japanese; three talkers per language). Ten-month-olds in the monolingual groups listened equally to all three languages. However, 10-month-old bilinguals showed a significant preference for each native language over Japanese; listening times to English and French were not different. Individual bilingual 10-month-olds preferred the more prevalent native language in their input. These findings indicate bilingual infants listen more selectively when they encounter different languages. The implications of these findings for understanding speech processing in early bilingual acquisition will be discussed. [Work supported by SSHRC.]

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 score0.630
Threshold uncertainty score0.187

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 head0.016
GPT teacher head0.295
Teacher spread0.279 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicLanguage Development and DisordersFrench-language works237,207