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Record W2791957275 · doi:10.1075/sibil.54.04whi

Formal linguistics and second language acquisition

2018· book-chapter· en· W2791957275 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

VenueStudies in bilingualism · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsLinguisticsApplied linguisticsClinical linguisticsComputer scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper motivates formal linguistic approaches to second language (L2) acquisition, particularly approaches grounded in generative grammar, and provides an overview of how such approaches have developed over time. The role of the mother tongue grammar and Universal Grammar (UG) in shaping the acquisition of linguistic representations is examined, starting with early debates on the effects of principles and parameters of UG in L2 (the UG access debate). This focus has been replaced with more nuanced analyses of the nature of interlanguage representations, for example, the nature of the initial state, the status of functional categories and features in L2 grammars, as well as potential problems at the linguistic interfaces. Discrepancies between underlying L2 competence and L2 performance are discussed, focusing on research that addresses the question of how representations are accessed and used in real time processing.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.062
GPT teacher head0.325
Teacher spread0.263 · 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