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Record W2623656870 · doi:10.1080/02699206.2017.1328706

Insensitivity to verb conjugation patterns in French children with SLI

2017· article· en· W2623656870 on OpenAlexafffund
Phaedra Royle, Ariane St-Denis, Patrizia Mazzocca, Alexandra Marquis

Bibliographic record

VenueClinical Linguistics & Phonetics · 2017
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound ResearchCentre for Research on Brain Language and Music
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et CultureUniversité de Montréal
KeywordsPsychologyVerbLinguisticsSpecific language impairmentDevelopmental psychologyPhilosophy

Abstract

fetched live from OpenAlex

Specific language impairment (SLI) is characterised by persistent difficulties that affect language abilities in otherwise normally developing children (Leonard, 2014). It remains challenging to identify young children affected by SLI in French. We tested oral production of the passé composé tense in 19 children in kindergarten and first grade with SLI aged from 5;6 to 7;4 years. All children were schooled in a French environment, but with different linguistic backgrounds. We used an Android application, Jeu de verbes (Marquis et al., 2012), with six verbs in each of four past participle categories (ending in -é, -i, -u, and other irregulars). We compared their results and error types to those of control children (from Marquis, 2012-2014) matched for gender, age, languages spoken at home, and parental education. Results show that children with SLI do not master the passé composé in the same way as typical French children do, at later ages than previously shown in the literature. This task shows potential for oral language screening in French-speaking children in kindergarten and first grade, independently of language background.

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 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)0.006
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 score0.013
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 head0.391
Teacher spread0.349 · 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 teacher head, 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

Citations5
Published2017
Admission routes2
Has abstractyes

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