The Language Abilities of Bilingual Children With Down Syndrome
Bibliographic record
Abstract
Children with Down syndrome (DS) have cognitive disabilities resulting from trisomy 21. Language-learning difficulties, especially expressive language problems, are an important component of the phenotype of this population. Many individuals with DS are born into bilingual environments. To date, however, there is almost no information available regarding the capacity of these individuals to acquire more than 1 language. The present study compared the language abilities of 8 children with DS being raised bilingually with those of 3 control groups matched on developmental level: monolingual children with DS (n = 14), monolingual typically developing (TD) children (n = 18), and bilingual TD children (n = 11). All children had at least 100 words in their productive vocabularies but a mean length of utterance of less than 3.5. The bilingual children spoke English and 1 other language and were either balanced bilinguals or English-dominant. English testing was completed for all children using the following: the Preschool Language Scale, Third Edition; language sampling; and the MacArthur Communicative Development Inventories (CDI). Bilingual children were also tested in the second language using a vocabulary comprehension test, the CDI, and language sampling. Results provided evidence of a similar profile of language abilities in bilingual children as has been documented for monolingual children with DS. There was no evidence of a detrimental effect of bilingualism. That is, the bilingual children with DS scored at least as well on all English tests as their monolingual DS counterparts. Nonetheless, there was considerable diversity in the second-language abilities demonstrated by these individuals with DS. Clinical implications are addressed.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".