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Record W4399170827 · doi:10.1037/pspp0000506

Cross-situational variability in childhood personality states.

2024· article· en· W4399170827 on OpenAlexfundno aff
Whitney R. Ringwald, Allison N. Shields, Shauna C. Kushner, Kathrin Herzhoff, Jennifer L. Tackett

Bibliographic record

VenueJournal of Personality and Social Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSocioemotional selectivity theoryPsychologySituational ethicsPersonalityDevelopmental psychologyConstruct (python library)Social psychologyBig Five personality traitsPersonality development

Abstract

fetched live from OpenAlex

= 9.92) completing 15 standardized tasks and rated youth's Big Five personality states. Cross-situational variability in each personality state was estimated by calculating within-person standard deviations across tasks. Results showed that (a) there is substantial variability in children's personality states; (b) children who are variable in one personality domain tend to be variable in other domains; and (c) 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. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.047
GPT teacher head0.411
Teacher spread0.364 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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