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Record W4366251542 · doi:10.1002/dev.22388

Children's shyness and physiological arousal to a peer's social stress

2023· article· en· W4366251542 on OpenAlexafffund
Kristie L. Poole, Linda Sosa‐Hernandez, Emma S. Green, McLennon Wilson, Claudia Labahn, Heather A. Henderson

Bibliographic record

VenueDevelopmental Psychobiology · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsShynessPsychologyArousalStress (linguistics)Developmental psychologySocial stressSocial psychologyAnxietyPsychiatryLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

= 10.22 years, SD = 0.81, N = 62) were paired with an unfamiliar peer and engaged in a speech task while electrocardiography was recorded. We modeled changes in children's heart rate, a physiological correlate of anxiety, while they observed their peer prepare and deliver a speech. Results revealed that the observing child's shyness related to increases in their heart rate during their peer's preparation period, but modulation of this arousal was sensitive to the presenting peer's anxious behavior while delivering their speech. Specifically, if the presenting child displayed high levels of anxious behavior, the observing child's shyness was related to further increases in heart rate, but if the presenting child displayed low levels of anxious behavior, the observing child's shyness was related to decreases in heart rate from the preparation period. Shy children may experience physiological arousal to a peer's social stress but can regulate this arousal based on social cues from the peer, which may be due to heightened social threat detection and/or empathic anxiety.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.042
GPT teacher head0.319
Teacher spread0.277 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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