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Record W2541359813 · doi:10.1075/lllt.38.14fri

Chapter 10. Control and representation in bilingualism

2013· article· en· W2541359813 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
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsYork University
Fundersnot available
KeywordsNeuroscience of multilingualismRepresentation (politics)Control (management)PsychologyCognitionIsolation (microbiology)Cognitive psychologyDisadvantageCognitive scienceLinguisticsMental representationLexical accessComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The bilingual advantage in executive functioning is often contrasted with a disadvantage in lexical access, but the two are based on different processes. The former entails fluid operations used for intentional processing (i.e., cognitive control) and the latter involves crystallized knowledge (i.e., representations). On this view, the processes associated with control and representation are interactive systems responsive to different developmental factors rather than mutually exclusive alternatives. Nonetheless, the majority of research in bilingualism has investigated either control or representation in isolation by minimizing participants’ reliance on the other factor. This chapter will review research investigating the interaction between these processes by bilinguals during language processing tasks and discuss how this relationship can provide new insights to pedagogy.

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 categoriesInsufficient 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 score0.197
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.264
Teacher spread0.254 · 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