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Record W2806717878 · doi:10.1017/s1366728918000524

Cognitive control among immersed bilinguals: Considering differences in linguistic and non-linguistic processing

2018· article· en· W2806717878 on OpenAlexafffund
Laura Sabourin, Santa Vīnerte

Bibliographic record

VenueBilingualism Language and Cognition · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsStroop effectPsychologyCognitionNeuroscience of multilingualismTask (project management)Control (management)Cognitive psychologyLinguisticsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

While several studies have shown a bilingual advantage in cognitive control, others have refuted such findings, leading to debates regarding the existence of bilingual benefits. The current study conducts two experiments to investigate this issue, focusing on the effect of the age of second language immersion in young adult non-immigrant bilinguals. We use a colour-word Stroop task to assess linguistic cognitive control, and an Attention Network Test to examine non-linguistic cognitive control. Results show significant differences between Simultaneous and Early Sequential bilinguals (typically grouped together as ‘early’) in the Stroop task, but these only become apparent when both languages are mixed. Simultaneous bilinguals also show improved Executive Control efficiency, particularly in the presence of alerting and orienting cues, suggesting enhanced attentional skills for this group. We discuss these findings with respect to participant grouping and task effects, noting the importance of the language environment.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.297
Teacher spread0.268 · 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.

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

Citations20
Published2018
Admission routes2
Has abstractyes

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