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Record W2130116026 · doi:10.1037/1528-3542.7.2.388

Stability of laboratory-assessed temperamental emotionality traits from ages 3 to 7.

2007· article· en· W2130116026 on OpenAlexaff
C. Emily Durbin, Elizabeth P. Hayden, Daniel N. Klein, Thomas M. Olino

Bibliographic record

VenueEmotion · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern University
Fundersnot available
KeywordsTemperamentEmotionalityPsychologyDevelopmental psychologyStability (learning theory)PersonalitySocial psychology

Abstract

fetched live from OpenAlex

A key component of temperament models is the presumed temporal stability of temperament traits. Although a substantial literature using parent report measures has addressed this claim, very few investigations have examined the stability of temperament using alternative measurement strategies, particularly those that involve direct assessment of emotional expressions. This study reports on the relative stability and heterotypic continuity of temperament traits measured via laboratory tasks and maternal report in a sample of children assessed at ages 3, 5, and 7, focusing on Positive Emotionality and Negative Emotionality. Relative stability of Positive Emotionality and Negative Emotionality traits ranged from moderate to high for laboratory and maternal report measures. Measures of emotional expressions exhibited levels of stability comparable to or higher than traits defined by other behavioral patterns (e.g., sociability and engagement).

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)0.004
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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

Citations197
Published2007
Admission routes1
Has abstractyes

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