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Three Profiles of Language Abilities in Toddlers With an Expressive Vocabulary Delay: Variations on a Theme

2010· article· en· W2071441732 on OpenAlexaff
Chantal Desmarais, Audette Sylvestre, François Meyer, Isabelle Bairati, Nancie Rouleau

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsVocabularyPsychologyLinguisticsTheme (computing)Vocabulary developmentExpressive languageLanguage developmentLanguage delayDevelopmental psychologyLanguage acquisitionCognitive psychologyComputer scienceMathematics education

Abstract

fetched live from OpenAlex

PURPOSE: The presence of an expressive vocabulary delay (EVD) in the context of otherwise harmonious development has been the main criterion used to define language delay in 2-year-olds. To better understand the communicative functioning of these children, other variables must be considered. In this study, the aim was to delineate and characterize clusters of 2-year-olds with EVD by measuring other language variables in these children. METHOD: Language and related variables were measured in 68 francophone children with EVD. RESULTS: In a cluster analysis, 2 language variables--(a) language expression and engagement in communication and (b) language comprehension--yielded 3 clusters ranging from weak language ability to high scores on both variables. Further differences were found between these clusters with regard to 2 correlates of lexical acquisition--namely, size of the expressive vocabulary and cognitive development. CONCLUSION: These results shed new light on the notion of heterogeneity in toddlers who present with an EVD by proposing subgroups among them. A follow-up investigation of these participants is ongoing.

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)0.000
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.046
GPT teacher head0.376
Teacher spread0.330 · 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

Citations38
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Speech Language and Hearing ResearchSame topicLanguage Development and DisordersFrench-language works237,207