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Record W4404860120 · doi:10.3390/bs14121147

Observed Shyness-Related Behavioral Responses to a Self-Presentation Speech Task: A Study Comparing Chinese and Canadian Children

2024· article· en· W4404860120 on OpenAlexafffundabout
Xiaoxue Kong, Taigan L. MacGowan, Shumin Wang, Yan Li, Louis A. Schmidt

Bibliographic record

VenueBehavioral Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsQueen's UniversityMcMaster UniversityUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShynessPsychologyDevelopmental psychologyContext (archaeology)Socioemotional selectivity theorySocial environmentSocial psychologyAnxiety

Abstract

fetched live from OpenAlex

Past research suggests that expressions of shyness are associated with several distinct behaviors that may differ between Eastern and Western cultures. However, this evidence has largely been derived from subjective ratings, such self-, teacher-, and parent-report measures. In this study, we examined between-country differences on measures of directly observed shyness-related behaviors during a speech task in children. Participants were 74 Chinese (Mage = 4.76 years old, SDage = 0.62 years old; 77.0% male) and 189 Canadian (Mage = 4.80 years old, SDage = 0.82 years old; 48.1% male) children aged 4–6 years. As predicted, the results reveal that Chinese children exhibit a higher frequency of gaze aversion and lower total time speaking compared to Canadian children. Additionally, significant interactions between country and gender were found for fidgeting and smiling behaviors, indicating that cultural expectations and norms influence how boys and girls express some shyness-related behaviors in social situations. These preliminary findings extend prior cross-cultural research on shyness-related behaviors indexed using subjective report measures to directly observed measures, highlighting the importance of cultural context in shaping children’s responses to social evaluation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.718

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.192
GPT teacher head0.449
Teacher spread0.258 · 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.

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
Published2024
Admission routes3
Has abstractyes

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