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Record W2099084441 · doi:10.1080/02699200110116462

Verb argument structure weakness in specific language impairment in relation to age and utterance length

2002· article· en· W2099084441 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

VenueClinical Linguistics & Phonetics · 2002
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill University
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsArgument (complex analysis)VerbSpecific language impairmentUtteranceLinguisticsContext (archaeology)PsychologySyntaxCognitive psychologyPhilosophyMedicine

Abstract

fetched live from OpenAlex

In spite of the complexity of verb argument structure, argument structure errors are infrequent in the speech of children with specific language impairment (SLI). The study examined the spontaneous argument structure use of school-age children with SLI and with normal language (NL) (n = 100). The groups did not differ substantially in frequency of argument structure errors, particularly when pragmatic context was considered. However, children with SLI used significantly fewer argument types, argument structure types and verb alternations than age-matched children with NL. Further, significant differences between children with SLI and mean length of utterance-matched controls were found involving the use of three-place argument structures. The results show that children with SLI demonstrate mostly correct, but less sophisticated, verb argument structure use than NL peers, and that the difference is not merely attributable to production limitations such as utterance length. The possibility of incomplete argument structure representation is suggested.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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