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Record W1957724129 · doi:10.1002/icd.1902

Measuring Preschoolers' Inhibitory Control Using the Black/White Stroop

2015· article· en· W1957724129 on OpenAlexaff
Corrie Vendetti, Deepthi Kamawar, Gal Podjarny, Andrea Astle

Bibliographic record

VenueInfant and Child Development · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsStroop effectInhibitory controlPsychologyWhite (mutation)Inhibitory postsynaptic potentialDevelopmental psychologyTask (project management)Control (management)Response inhibitionAudiologyCognitive psychologyCognitionNeuroscienceMedicine

Abstract

fetched live from OpenAlex

The Day/Night Stroop is a widely used measure of inhibitory control with preschoolers that requires them to respond ‘day’ to a picture of a moon and ‘night’ to a picture of a sun (Gerstadt, Hong, & Diamond, 1994). However, we argue that the nature of the relation between the stimuli and required responses requires more than inhibitory control. In the present study we compared 51 three‐ to five‐year‐olds' performance on the Day/Night and the Black/White Stroop alongside other measures of Executive Function and language. As predicted, we found that children make inhibitory errors on the Black/White, while they make both inhibitory and memory errors on the Day/Night. As a result, the Day/Night Stroop underestimates the inhibitory control abilities of some children. Further, we also found that performance on the Black/White task was strongly related to performance on another inhibitory control task, while performance on the Day/Night was not. Copyright © 2015 John Wiley & Sons, Ltd.

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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.159
GPT teacher head0.312
Teacher spread0.153 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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