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Record W2098500198 · doi:10.1017/s1366728907002908

Neural plasticity in speech acquisition and learning

2007· article· en· W2098500198 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

VenueBilingualism Language and Cognition · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOptimal distinctiveness theoryTimelinePsychologyLanguage acquisitionNeuroplasticityComputer scienceCognitive scienceCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Neural plasticity in speech acquisition and learning is concerned with the timeline trajectory and the mechanisms of experience-driven changes in the neural circuits that support or disrupt linguistic function. In this selective review, we discuss the role of phonetic learning in language acquisition, the “critical period” of learning, the agents of neural plasticity, and the distinctiveness of linguistic systems in the brain. In particular, we argue for the necessity to look at brain–behavior connections using modern brain imaging techniques, seek explanations based on measures of neural sensitivity, neural efficiency, neural specificity and neural connectivity at the cortical level, and point out some key factors that may facilitate or limit second language learning. We conclude by highlighting the theoretical and practical issues for future studies and suggest ways to optimize language learning and treatment.

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)0.001
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 score0.053
Threshold uncertainty score0.604

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 head0.018
GPT teacher head0.285
Teacher spread0.267 · 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