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Record W2479133563 · doi:10.1075/lllt.38.15sch

Chapter 11. Language selection, control, 
and conceptual-lexical development 
in bilinguals and multilinguals

2013· book-chapter· en· W2479133563 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

VenueLanguage learning and language teaching · 2013
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSelection (genetic algorithm)LinguisticsCognitionControl (management)Computer sciencePsychologyContext (archaeology)Artificial intelligenceHistory

Abstract

fetched live from OpenAlex

This chapter presents recent developments in the cognitive underpinnings of bilingual speech production. Upon close observation of the theories explaining how speakers of non-native languages are able to select the language in which to speak and control cross-linguistic interference from non-target words competing for selection, it is apparent that these abilities – and more generally, the cognitive processes of bilingual speech production – take shape in the context of a dynamic conceptual and lexical framework that is adaptable to accommodate various functionalities during non-native language development. This chapter also addresses the effects of language acquisition beyond two languages and highlights the implications for teaching and learning of non-native languages by advocating for immersion experiences and pedagogical considerations that foster conceptual and lexical development.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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