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Record W2170267637 · doi:10.1017/s1366728907003227

The development of two types of inhibitory control in monolingual and bilingual children

2008· article· en· W2170267637 on OpenAlexaff
MICHELLE M. MARTIN-RHEE, Ellen Bialystok

Bibliographic record

VenueBilingualism Language and Cognition · 2008
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsYork University
Fundersnot available
KeywordsStroop effectInhibitory controlTask (project management)Response inhibitionPsychologyCognitive psychologyControl (management)PerceptionNegative primingSelective attentionDevelopmental psychologyComputer scienceCognitionArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Previous research has shown that bilingual children excel in tasks requiring inhibitory control to ignore a misleading perceptual cue. The present series of studies extends this finding by identifying the degree and type of inhibitory control for which bilingual children demonstrate this advantage. Study 1 replicated the earlier research by showing that bilingual children perform the Simon task more rapidly than monolinguals, but only on conditions in which the demands for inhibitory control were high. The next two studies compared performance on tasks that required inhibition of attention to a specific cue, like the Simon task, and inhibition of a habitual response, like the day–night Stroop task. In both studies, bilingual children maintained their advantage on tasks that require control of attention but showed no advantage on tasks that required inhibition of response. These results confine the bilingual advantage found previously to complex tasks requiring control over attention to competing cues (interference suppression) and not to tasks requiring control over competing responses (response inhibition).

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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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

Citations602
Published2008
Admission routes1
Has abstractyes

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