Verbal fluency in bilingual children with Autism Spectrum Disorders
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".