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Using Speech Sounds to Guide Word Learning: The Case of Bilingual Infants

2007· article· en· W2136573864 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChild Development · 2007
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of British ColumbiaUniversity of Ottawa
Fundersnot available
KeywordsPsychologyNeuroscience of multilingualismLanguage acquisitionLanguage developmentLinguisticsWord learningWord (group theory)Task (project management)Vocabulary developmentCognitionHomogeneousVocabularyDevelopmental psychologyTeaching methodMathematics education

Abstract

fetched live from OpenAlex

Despite the prevalence of bilingualism, language acquisition research has focused on monolingual infants. Monolinguals cannot learn minimally different words (e.g., "bih" and "dih") in a laboratory task until 17 months of age (J. F. Werker, C. T. Fennell, K. M. Corcoran, & C. L. Stager, 2002). This study was extended to 14- to 20-month-old bilingual infants: a heterogeneous sample (English and another language; N = 48) and two homogeneous samples (28 English-Chinese and 25 English-French infants). In all samples, bilinguals did not learn similar-sounding words until 20 months, indicating that they use relevant language sounds (i.e., consonants) to direct word learning developmentally later than monolinguals, possibly due to the increased cognitive load of learning two languages. However, this developmental pattern may be adaptive for bilingual word learning.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.354
Teacher spread0.323 · 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