Evaluating Interactive Language for Children with Autism Spectrum Disorder (ASD) in Different Contexts
Bibliographic record
Abstract
Autism spectrum disorder (ASD) is characterized by impairments in the use of appropriate interactive language (including structural language and pragmatic skills) in social contexts. However, the phenotype and causes of interactive language deficits in children with ASD, in different contexts, are still unclear. In this study, we examined the structural language and pragmatic skills of children with ASD in four contexts: playing, drawing, reading, and free talking. We found that while children with ASD did not exhibit deficits in structural language (e.g., vocabulary and utterance), they clearly exhibit deficits in pragmatic skills. We, also, found that contexts played a key role in the use of interactive language by children with ASD. For example, the reading context had a significant impact on the diversity of vocabulary, while the playing and drawing contexts made an important contribution to the formation of complex utterances. The free talking context, on the other hand, contributed to producing more turns. Furthermore, Spearman's rank correlation analysis was used to examine the relationships between maternal input and children's language output. We found that the correlations between structural language and maternal input in children with ASD were not as high as revealed in previous studies, while a, relatively, obvious relationship was found between pragmatic skills and maternal input. Specifically, the total number of turns (TNT) for a child with ASD is related to their mother's TNT, as are the total number of words (TNW) and number of different words (NDW). These results suggest that (1) assessment of pragmatic skills should be included in the evaluation of children with suspected ASD (2) the influence of context on pragmatic skills needs to be taken into account, when assessing the pragmatic development of children with ASD; and (3) the impact of maternal language on children's language use is of great importance, for children with ASD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".