MétaCan
Menu
Back to cohort
Record W2518712057 · doi:10.1075/lab.15023.gon

Verbal fluency in bilingual children with Autism Spectrum Disorders

2016· article· en· W2518712057 on OpenAlexafffund
Ana Maria Gonzalez‐Barrero, Aparna Nadig

Bibliographic record

VenueLinguistic Approaches to Bilingualism · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaCentre for Research on Brain, Language and Music
KeywordsVerbal fluency testPsychologyFluencyAutismNeuroscience of multilingualismTypically developingAutism spectrum disorderDevelopmental psychologyNonverbal communicationCognitionNeuropsychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract We examine the impact of bilingualism on verbal fluency in four groups of school-age (5 to 10 years-old) children: 13 Typically-developing (TYP) monolingual children, 13 TYP bilingual children, 13 monolingual children with Autism Spectrum Disorders (ASD) and 13 bilingual children with ASD. Participants were matched on chronological age and nonverbal IQ. Verbal fluency was examined via the word association subtest of the Clinical Evaluation of Language Fundamentals (CELF-4; Semel et al., 2003 ). The bilingual ASD group performed unexpectedly well on the verbal fluency task, not differing from the typically-developing groups, but outperforming the monolingual ASD group with respect to number of correct words produced. These findings are in line with previous research on bilingual children with ASD (e.g., Hambly & Fombonne, 2012 ) and taken together suggest that bilingualism does not have a negative impact on the lexical-semantic skills of children with ASD.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.275
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations64
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueLinguistic Approaches to BilingualismSame topicAutism Spectrum Disorder ResearchFrench-language works237,207