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Effects of Input Properties, Vocabulary Size, and L1 on the Development of Third Person Singular –<i>s</i> in Child L2 English

2012· article· en· W2156906445 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

VenueLanguage Learning · 2012
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInflectionPsychologyLexiconLinguisticsLanguage acquisitionVocabulary developmentVocabularyPerspective (graphical)Language developmentPhonological developmentFirst languageSecond languagePhonologyDevelopmental psychologyMathematics educationArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

This study was designed to investigate the development of third‐person singular (3SG) – s in children who learn English as a second language (L2). Adopting the usage‐based perspective on the learning of inflection, we analyzed spontaneous speech samples collected from 15 English L2 children who were followed over a 2‐year period. Assessing the contribution of a wide range of predictors, we show that word frequency, allomorph, lexicon size, inflectional properties of the first language (L1), and months of exposure to English all have impact on English L2 children's use of 3SG – s in obligatory contexts. This study enhances both our understanding of the development of 3SG – s and of child L2 acquisition. The outcomes support a usage‐based approach to learning inflection and emphasize the importance of a multifactorial analysis of language development.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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