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Record W2068091139 · doi:10.1207/s15326942dn2802_4

Assessment of Hot and Cool Executive Function in Young Children: Age-Related Changes and Individual Differences

2005· article· en· W2068091139 on OpenAlexafffund
Donaya Hongwanishkul, Keith Happaney, Wendy S. C. Lee, Philip David Zelazo

Bibliographic record

VenueDevelopmental Neuropsychology · 2005
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPsychologyCognitionDevelopmental psychologyTemperamentPrefrontal cortexTask (project management)Executive functionsDorsolateral prefrontal cortexWorking memoryCognitive psychologyNeuroscienceSocial psychologyPersonality

Abstract

fetched live from OpenAlex

Although executive function (EF) is often considered a domain-general cognitive function, a distinction has been made between the "cool" cognitive aspects of EF more associated with dorsolateral regions of prefrontal cortex and the "hot" affective aspects more associated with ventral and medial regions (Zelazo and Mller, 2002). Assessments of EF in children have focused almost exclusively on cool EF. In this study, EF was assessed in 3- to 5-year-old children using 2 putative measures of cool EF (Self-Ordered Pointing and Dimensional Change Card Sort) and 2 putative measures of hot EF (Children's Gambling Task and Delay of Gratification). Findings confirmed that performance on both types of task develops during the preschool period. However, the measures of hot and cool EF showed different patterns of relations with each other and with measures of general intellectual function and temperament. These differences provide preliminary evidence that hot and cool EF are indeed distinct, and they encourage further research on the development of hot EF.

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)0.003
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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

Citations649
Published2005
Admission routes2
Has abstractyes

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