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Record W4281293583 · doi:10.1002/dev.22272

Observed shyness leads to more automatic imitation in early childhood

2022· article· en· W4281293583 on OpenAlexafffund
Taigan L. MacGowan, James Mirabelli, Sukhvinder S. Obhi, Louis A. Schmidt

Bibliographic record

VenueDevelopmental Psychobiology · 2022
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsShynessImitationPsychologyDevelopmental psychologyCognitive psychologySocial psychologyAnxietyPsychiatry

Abstract

fetched live from OpenAlex

The authors investigated children's automatic imitation in the context of observed shyness by adapting the widely used automatic imitation task (AIT). AIT performance in 6-year-old children (N = 38; 22 female; 71% White) and young adults (17-22 years; N = 122; 99 female; 32% White) was first examined as a proof of concept and to assess age-related differences in responses to the task (Experiment 1). Although error rate measures of automatic imitation were comparable between children and adults, children displayed less reaction time interference than adults. Children's shyness coded from direct behavioral observations was then examined in relation to AIT scores (Experiment 2). Observed shyness at 5 years old predicted higher automatic imitation one year later. We discuss the latter findings in the context of an adaptive strategy. We argue that shy children may possess a heightened sensitivity to others' motor cues and therefore are more likely to implicitly imitate social partners' actions. This tendency may serve as a strategy to signal appeasement and affiliation, allowing for shy children to blend in and feel less inhibited in a social environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.048
GPT teacher head0.309
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes2
Has abstractyes

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