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Record W2157599703 · doi:10.1111/1467-8624.00318

Children's Understanding of Emotion in Speech

2001· article· en· W2157599703 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChild Development · 2001
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsParalanguagePsychologySadnessHappinessFocus (optics)Cognitive psychologyDevelopmental psychologyCommunicationSocial psychologyAnger

Abstract

fetched live from OpenAlex

Children's understanding of emotion in speech was explored in three experiments. In Experiment 1, 4- to 10-year-old children and adults (N = 165) judged the happiness or sadness of the speaker from cues conveyed by propositional content and affective paralanguage. When the cues conflicted (i.e., a happy situation was described with sad paralanguage), children relied primarily on content, in contrast to adults, who relied on paralanguage. There were gradual developmental changes from 4-year-olds' almost exclusive focus on content to adults' exclusive focus on paralanguage. Children of all ages exhibited greater response latencies to utterances with conflicting cues than to those with nonconflicting cues, indicating that they processed both sources of emotional information. Children accurately labeled the affective paralanguage when the propositional cues to emotion were obscured by a foreign language (Experiment 2, N = 20) or by low-pass filtering (Experiment 3, N = 60). The findings are consistent with children's limited understanding of the communicative functions of affective paralanguage.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

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)0.0010.000

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 head0.028
GPT teacher head0.276
Teacher spread0.248 · 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