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Record W2479381097 · doi:10.1075/aals.9.14ch11

Chapter 11. Electrophysiology of second language processing

2013· book-chapter· en· W2479381097 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

VenueAILA applied linguistics series · 2013
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEvent-related potentialCognitionComputer sciencePsychologyNeural correlates of consciousnessNatural language processingCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

This chapter reviews past and current contributions from event-related brain potential (ERP) research to the field of L2 processing. ERPs are able to measure cognitive brain processes at a very fine-grained temporal resolution and allow for determining when linguistic processes are occurring. The technique allows for investigations of whether L1 and L2 processing differences are mainly due to the fact that L2 processing takes longer or whether different neural procedures (as evidenced by different components being present) occur in L1 and L2 processing. Findings from studies of monolingual, bilingual and (where available) multilingual participants are reviewed to determine the effects of proficiency, age of acquisition and similarity between languages on the processing of languages learned later in life.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0280.000

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 head0.012
GPT teacher head0.205
Teacher spread0.192 · 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