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Record W2152620767 · doi:10.1017/s1366728912000478

Degree of conversational code-switching enhances verbal task switching in Cantonese–English bilinguals

2012· article· en· W2152620767 on OpenAlex
Odilia Yim, Ellen Bialystok

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBilingualism Language and Cognition · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsYork University
Fundersnot available
KeywordsCode-switchingTask switchingVerbal fluency testTask (project management)FluencyPsychologyNonverbal communicationConversationCognitive psychologyComputer scienceLinguisticsCommunicationCognitionNeuropsychology

Abstract

fetched live from OpenAlex

The study examined individual differences in code-switching to determine the relationship between code-switching frequency and performance in verbal and non-verbal task switching. Seventy-eight Cantonese–English bilinguals completed a semi-structured conversation to quantify natural code-switching, a verbal fluency task requiring language switching, and two non-verbal switching tasks. Participants who engaged in more conversational code-switching showed smaller costs in verbal task switching than those who switched languages less frequently. Participants performed similarly to bilinguals in previous studies on non-verbal switching tasks, but in this case performance was not linked to the degree of conversational code switching. The difference in the influence of code-switching for verbal and non-verbal executive control tasks indicates a dissociation between domains for the mechanism of task switching.

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.

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 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 score0.053
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.037
GPT teacher head0.298
Teacher spread0.261 · 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