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Record W3003410132 · doi:10.1017/s1366728920000036

Continuous effects of bilingualism and attention on Flanker task performance

2020· article· en· W3003410132 on OpenAlexaff
Ashley Chung-Fat-Yim, Geoffrey B Sorge, Ellen Bialystok

Bibliographic record

VenueBilingualism Language and Cognition · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsCollege of Physicians and Surgeons of OntarioYork University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsNeuroscience of multilingualismPsychologyTask (project management)Affect (linguistics)Selective attentionDevelopmental psychologyCognitive psychologyCognitionCommunicationNeuroscience

Abstract

fetched live from OpenAlex

Both bilingualism and attention contribute to the development of executive functioning (EF), with higher levels of both leading to better outcomes. The present study treats bilingualism and attention as continuous variables to investigate their impact on EF. Eighty-two 9-year-olds who were attending a French school in an anglophone community completed a flanker task. Children's progress in French represented their level of bilingualism, and attention was assessed through a standard standardized instrument. Degree of bilingualism and degree of attention were both positively related to performance, but exposure to a third language in the home did not further affect outcomes.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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

Citations17
Published2020
Admission routes1
Has abstractyes

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