Emotion dynamics among preadolescents getting to know each other: Dyadic associations with shyness.
Bibliographic record
Abstract
= 10.13 years, 75.8% White) were observed during an unstructured "getting to know you" task. Children's shyness was assessed through parent- and child-report. Using grid-sequence analysis (Brinberg et al., 2017) we identified three dyadic emotion clusters: Flexible and Shared Positive Affect (60%), Flexible and Shared Neutral Affect (35%), and Stable and Shared Negative Affect (17%). Children in the Stable and Shared Negative Affect cluster were rated higher in shyness relative to children in the Flexible and Shared Positive Affect cluster. Further, children more similar in shyness to their dyadic partner displayed more stable negative and neutral affect expressions than children who differed in shyness from their partner. Together, these findings suggest that shyness is related to less positive and less flexible emotion expressions when meeting a new peer, holding critical implications for friendship initiation among children varying in shyness. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".