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Record W2313127143 · doi:10.1017/s0305000915000562

Chinese L1 children's English L2 verb morphology over time: individual variation in long-term outcomes

2016· article· en· W2313127143 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

VenueJournal of Child Language · 2016
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrammaticalityMorphemePsychologyVariation (astronomy)LinguisticsVerbVocabularyLanguage acquisitionVocabulary developmentLanguage developmentTerm (time)Developmental psychologyGrammarMathematics education

Abstract

fetched live from OpenAlex

This study examined accuracy in production and grammaticality judgements of verb morphology by eighteen Chinese-speaking children learning English as a second language (L2) followed longitudinally from four to six years of exposure to English, and who began to learn English at age 4;2. Children's growth in accuracy with verb morphology reached a plateau by six years, where 11/18 children did not display native-speaker levels of accuracy for one or more morphemes. Variation in children's accuracy with verb morphology was predicted by their English vocabulary size and verbal short-term memories primarily, and quality and quantity of English input at home secondarily. This study shows that even very young L2 learners might not all catch up to native speakers in this time frame and that non-age factors play a role in determining individual variation in child L2 learners' long-term outcomes with English morphology.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.993

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.005
GPT teacher head0.277
Teacher spread0.272 · 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