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Record W2398164711 · doi:10.1002/icd.1985

Do Questions Get Infants Talking? Infant Vocal Responses to Questions and Declaratives in Maternal Speech

2016· article· en· W2398164711 on OpenAlexafffund
Melissa Reimchen, Mélanie Söderström

Bibliographic record

VenueInfant and Child Development · 2016
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsPsychologyUtteranceSentenceDevelopmental psychologySession (web analytics)Language developmentConversationMean length of utteranceLinguisticsCommunication

Abstract

fetched live from OpenAlex

Maternal questions play a crucial role in early language acquisition by virtue of their special grammatical, prosodic and lexical forms, and their abundance in the input. Infants are able to discriminate questions from other sentence types and produce rising intonations in their own requests. This study examined whether caregiver questions were related to the quantity of infant vocalizations. Thirty‐six infants aged 10 and 14 months participated in a laboratory play session with their mothers. In separate blocks, mothers were instructed to ask questions and to refrain from asking questions. Both block‐level and utterance‐level analyses found no evidence that maternal questions affected the amount of infant‐response vocalizations. Mothers of 14‐month‐olds (but not 10‐month‐olds) tended to repeat questions. Copyright © 2016 John Wiley & Sons, Ltd.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.011
GPT teacher head0.295
Teacher spread0.284 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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