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Record W4390700522 · doi:10.1017/s1366728923000883

Neural correlates of compound head position in language control: Evidence from simultaneous production and comprehension

2024· article· en· W4390700522 on OpenAlexaff
Shuang Liu, Junjun Huang, Zehui Xing, John W. Schwieter, Huanhuan Liu

Bibliographic record

VenueBilingualism Language and Cognition · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcMaster UniversityWilfrid Laurier University
Fundersnot available
KeywordsHead (geology)ComprehensionCued speechLinguisticsControl (management)PsychologyPhraseProduction (economics)Position (finance)Noun phraseComputer scienceNounCommunicationCognitive psychologyArtificial intelligenceBiology

Abstract

fetched live from OpenAlex

Abstract Compound words consist of two or more words which combine to form a single word or phrase that acts as one. In English, the head of compound words is usually, but not always, the right-most root (e.g., “paycheck” is a noun because the head, “check,” is a noun). The current study explores the effects of head position on language control by examining language switching performance through electroencephalography (EEG). Twenty-one pairs of Chinese (L1)–English (L2) bilinguals performed cued language switching in a simultaneous production and comprehension task. The results showed that bilinguals recognized the head position earlier both in production and comprehension. However, the language control of the head position during production occurred in the middle stage (N2), but in the late stage (LPC) during comprehension. These findings indicate that the head position in compound words exerts differential influences on language control.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.026
GPT teacher head0.303
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2024
Admission routes1
Has abstractyes

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