MétaCan
Menu
Back to cohort
Record W4205933473 · doi:10.1017/s0008413100000669

Missing Inflection in L2 Acquisition: Defective Syntax or LI-Constrained Prosodic Representations?

2003· article· en· W4205933473 on OpenAlexaff
Heather Goad, Lydia White, Jeffrey Steele

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2003
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsInflectionMandarin ChineseLinguisticsPhonologySyntaxInterlanguageAdjunctionRule-based machine translationGrammarComputer sciencePsychologyNatural language processingMathematicsPhilosophyPure mathematics

Abstract

fetched live from OpenAlex

Abstract It is proposed that failure to consistently produce inflectional morphology by Mandarin-speaking learners of English is due to properties of the LI prosodic phonology which are transferred into the interlanguage grammar. While English requires inflection to be adjoined to the Prosodic Word, Mandarin does not permit this structure. Inflection in Mandarin is instead incorporated into the PWd of the stem to which it attaches. It is shown that Mandarin speakers fall into two groups in their treatment of English inflectional morphology. One group of learners is sensitive to the need for a unified analysis of inflection. They recognize that English does not permit a stem-internal analysis of this morphology, but as their grammars do not permit adjunction, inflection is deleted across-the-board. For the other group, inflection surfaces variably, for those stimuli where the shape of the stem enables it to be incorporated into the PWd, as in the L1.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.334
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicPhonetics and Phonology ResearchFrench-language works237,207