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Record W2541359813 · doi:10.1075/lllt.38.14fri

Chapter 10. Control and representation in bilingualism

2013· article· en· W2541359813 on OpenAlexaff
Deanna C. Friesen, Ellen Bialystok

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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

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 designTheoretical or conceptual
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

Citations0
Published2013
Admission routes1
Has abstractyes

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