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Record W2047972883 · doi:10.1075/ml.3.2.06sch

Language switching in bilingual speech production

2008· article· en· W2047972883 on OpenAlex

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

VenueThe Mental Lexicon · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsRobustness (evolution)Computer scienceFluencyInhibitory controlNatural language processingLanguage productionVerbal fluency testArtificial intelligenceSpeech productionPsychologySpeech recognitionCognitionBiology

Abstract

fetched live from OpenAlex

Recent research on language production suggests that bilinguals shift from using inhibitory control mechanisms to a language-specific selective mechanism during development (Costa, Santesteban, & Ivanova, 2006). Costa et al. argue that the robustness of the L2 lexical representations may be critical to the functionality of a language-specific selective mechanism. Accordingly, in the present study we measured the lexical robustness of a group of 54 English dominant learners of Spanish using a verbal fluency task and investigated its effect on their performance in a picture-naming task with language switches. The results suggest that L2 lexical robustness predicts the shift to a language-specific selective mechanism during speech production. Moreover, we demonstrate a specific threshold of lexical robustness necessary to engage the mechanism.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.011
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.040
GPT teacher head0.296
Teacher spread0.255 · 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