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Record W2140041017 · doi:10.1017/s1366728914000856

Executive control in fluent and lapsed bilinguals

2014· article· en· W2140041017 on OpenAlexaff
Cari A. Bogulski, Michael Rakoczy, Michelle S. Goodman, Ellen Bialystok

Bibliographic record

VenueBilingualism Language and Cognition · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyNeuroscience of multilingualismWorking memoryTask (project management)Control (management)Cognitive psychologyCognitionComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Previous research showing a bilingual advantage on a variety of executive control tasks has typically compared monolinguals and fluent bilinguals. No study to date, however, has examined whether these effects endure for bilingual individuals who revert to monolingualism (‘lapsed bilinguals’). We investigated this question by testing monolinguals, full bilinguals, and lapsed bilinguals on a flanker task and a working memory task. Fully fluent bilinguals exhibited significantly more accurate performance than monolinguals on the working memory task, with lapsed bilinguals performing between the other two groups. Thus, continued bilingual experience appears necessary to maintain these cognitive advantages at a high level.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.265
Teacher spread0.252 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations27
Published2014
Admission routes1
Has abstractyes

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