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Record W2622768147 · doi:10.1075/bpa.6.04sai

The bilingual mental lexicon

2017· book-chapter· en· W2622768147 on OpenAlexaff
Ladan Ghazi Saidi, Tanya Dash, Ana Inés Ansaldo

Bibliographic record

VenueBilingual processing and acquisition · 2017
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsMental lexiconLexiconAphasiaNeuroscience of multilingualismLinguisticsPsychologyFunctional magnetic resonance imagingComputer scienceCognitive psychologyNatural language processingNeuroscience

Abstract

fetched live from OpenAlex

Several theoretical accounts have been developed to describe the nature of the bilingual mental lexicon. In the last decades, functional magnetic resonance studies have provided some insight into the neural basis of lexical processing in healthy bilinguals and in bilinguals with aphasia. This chapter will discuss the bilingual mental lexicon as a complex knowledge system, which behaves dynamically as a function of various factors, including L1 and L2 proficiency level (exposure and use), psycholinguistic (semantic and phonological) characteristics of words within and across the spoken languages, learning methods, and the environment where learning happens (formal vs. informal), which in turn have an impact on the type of memory processing (implicit vs. explicit) involved in word storage. The bilingual mental lexicon is revealed as even more complex when phonological and semantic similarities and differences within and across languages are taken into account.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.798
Threshold uncertainty score1.000

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 studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.302
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreOther

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

Citations13
Published2017
Admission routes1
Has abstractyes

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