Latent profiles of children's shyness: Behavioral, affective, and physiological components
Bibliographic record
Abstract
Abstract Shyness can manifest on behavioral, affective, and physiological levels, but little is known about how these components cluster. We coded behavioral expressions of avoidance/inhibition, collected self-reported nervousness, and measured cardiac vagal withdrawal in 152 children (M age = 7.82 years, 73 girls, 82% White) to a speech task in 2018–2021. A latent profile analysis using these behavioral, affective, and physiological indicators revealed four profiles: average reactive (43%), lower affective reactive (20%), higher affective reactive (26%), and consistently higher reactive (11%). Membership in the higher reactive profile predicted higher parent-reported temperamental shyness across 2 years. Findings provide empirical support for the long-theorized idea that shyness might exist as an emotional state but also represents a distinct temperamental quality for some children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".