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Record W2022433615 · doi:10.1017/s1366728903001081

Fossilization in steady state L2 grammars: Persistent problems with inflectional morphology

2003· article· en· W2022433615 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 · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsMcGill University
Fundersnot available
KeywordsInflectionDefinitenessLinguisticsFossilizationRule-based machine translationGrammarContrast (vision)VerbMorphology (biology)TurkishComputer sciencePast tenseNatural language processingArtificial intelligencePsychologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

This paper provides a case study of the fossilized endstate L2 English grammar of an adult native speaker of Turkish. Results are presented from production data (over 3400 utterances, gathered over 2 time periods 18 months apart), concentrating on verbal and nominal inflection and associated syntactic properties; data from a number of other tasks are also presented. A high level of accuracy in suppliance of English tense and agreement morphology was found. In contrast, suppliance of definite and indefinite articles was significantly lower but nevertheless appropriate. Syntactic correlates (such as verb placement, presence of overt subjects, case assignment, definiteness effects) were all completely accurate, suggesting no underlying impairment to functional categories or features. There is some evidence for influence from the L1, which has rich inflection but lacks articles, but this appears to be an effect on suppliance of overt morphology and not on underlying representation, which shows properties appropriate to the L2.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.500

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 studies0.0000.000
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 head0.042
GPT teacher head0.371
Teacher spread0.329 · 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