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Record W2124705217 · doi:10.1017/s0305000915000203

Entrainment of prosody in the interaction of mothers with their young children

2015· article· en· W2124705217 on OpenAlexaff
Eon‐Suk Ko, Amanda Seidl, Alejandrina Cristià, Melissa Reimchen, Mélanie Söderström

Bibliographic record

VenueJournal of Child Language · 2015
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDyadPsychologyConversationProsodyToddlerEntrainment (biomusicology)Developmental psychologyCommunicationLinguisticsRhythm

Abstract

fetched live from OpenAlex

Caregiver speech is not a static collection of utterances, but occurs in conversational exchanges, in which caregiver and child dynamically influence each other's speech. We investigate (a) whether children and caregivers modulate the prosody of their speech as a function of their interlocutor's speech, and (b) the influence of the initiator of the conversation on durational characteristics of the exchange. We analyzed naturalistic conversations from 13 mother-infant/toddler dyads aged 12-30 months across full-day recordings of 3-5 days per dyad using LENA and automated analytic tools. We found small, but significant, effects of mothers and their children influencing each other's speech, particularly in pitch measures. We also found longer utterances and shorter response latencies for the initiator of a conversation. While mothers show more mature conversational capabilities (more entrainment, shorter response latencies), our findings converge with prior research to highlight the active role of young children in the conversational exchange.

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)0.004
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
Metaresearch0.0010.004
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 science0.0000.001
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 head0.009
GPT teacher head0.268
Teacher spread0.259 · 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

Citations79
Published2015
Admission routes1
Has abstractyes

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