Cross-Situational Variability in Childhood Personality States
Bibliographic record
Abstract
Personality variability is an important individual difference construct that is the focus of major psychological theories and relates to socioemotional functioning. Although cross-situational personality variability has been studied extensively in adult populations, little is known about variability in children’s personality. In this study, we aimed to address this gap in knowledge by evaluating whether cross-situational variability is a potentially meaningful individual difference in youth. We used a “thin slice” approach in which research assistants viewed videos of 324 children (Mage=9.92) completing 15 standardized tasks and rated youth’s Big Five personality states. Cross-situational variability in each personality state was estimated by the calculating within-person standard deviations across tasks. Results showed that (1) there is substantial variability in children’s personality states, (2) children who are variable in one personality domain tend to be variable in other domains, and (3) more variable children are described by their parents as being less competent, less agreeable, less conscientious, and more neurotic. However, associations with parent-rated external criterion were generally small in magnitude, and key psychometric properties of the thin slice personality variability index are not well-established. Our study adds tentative but promising evidence that individual differences in cross-situational personality variability are not only present in childhood, but may be consequential.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".