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Record W2258113989 · doi:10.1111/bjdp.12135

Guess who? Children use prosody to infer intended listeners

2016· article· en· W2258113989 on OpenAlexafffund
Anisha Varghese, Elizabeth S. Nilsen

Bibliographic record

VenueBritish Journal of Developmental Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of WaterlooCentre for Addiction and Mental Health
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsProsodyPsychologyChoseDevelopmental psychologyEmotional prosodyCognitive psychologyLinguistics

Abstract

fetched live from OpenAlex

This study examined the relative influence of prosody and semantic content in children's inferences about intended listeners. Children (n = 72), who ranged in age from 5 to 10 years, heard greetings with prosody and content that was either infant or adult directed and chose the intended listener from amongst an infant or an adult. While content affected all children's choices, the effect of prosody was stronger (at least, for children aged 7-10 years). For conditions in which prosodic cues were suggestive of one listener, and content cues, another, children aged 7-10 years chose the listener according to prosody. In contrast, the youngest age group (5- to 6-year-olds) chose listeners at chance levels in these incongruent conditions. While prosodic cues were most influential in determining children's choices, their ratings of how certain they felt about their choices indicated that content nonetheless influenced their thinking about the intended listener. Results are the first to show the unique influence of prosody in children's thinking about appropriate speech styles. Findings add to work showing children's ability to use prosody to make inferences about speakers' communicative intentions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.313
Teacher spread0.289 · 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.

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

Citations6
Published2016
Admission routes2
Has abstractyes

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