Bibliographic record
Abstract
BACKGROUND: The ability to repair communicative breakdown is an important pragmatic language skill, yet very little is known about it in the population of children with autism spectrum disorder (ASD). Previous investigations have shown that people with ASD, across a variety of ages and language levels, recognized communicative breakdown and responded to requests for clarification (RQCLs) with a wide variety of repair strategies. No previous work has assessed the repair abilities of speakers with ASD when faced with a persistent communicative breakdown indicated by a stacked series of RQCLs. AIMS: The present paper aimed to determine whether school-aged, high-functioning children with ASD responded to a stacked series of RQCLs in a way similar to children matched for language age. METHODS & PROCEDURES: Nine school-aged, high-functioning children with ASD were recruited and matched to nine control group children based on language level. During conversation, an unfamiliar examiner engineered 10 episodes of communicative breakdown. Each consisted of a stacked series of three RQCLs ('What?', 'I don't understand', 'Tell me another way'). Verbal and non-verbal responses to each RQCL were coded. Responses were analysed by a series of repeated measures analyses of variance with diagnostic group and RQCL type/position as independent variables and type of repair as the dependent variable. OUTCOMES & RESULTS: Children with ASD were similar to language age-matched control children in responding to RQCLs and employing a variety of repair strategies. In addition, their pattern of responding over the series of RQCLs was very similar to the controls in varying the repair strategy by adding increasingly more information as the breakdown persisted, i.e. as the sequence of RQCLs progressed. Children with ASD, however, were significantly more likely than language age-matched controls to respond to an RQCL with an inappropriate response. CONCLUSIONS: The ability to repair communicative breakdown successfully raises questions about some of the currently popular theories about the source and nature of social and communicative deficits in autism. In addition, the presence of significantly more inappropriate utterances in the group with ASD poses both theoretical and clinical challenges. In theoretical terms, several possible explanations are proposed, but future work will need to test these hypotheses. Clinically, it is important to focus on utterances that disrupt the conversational flow and that generate severe social penalties for the speaker 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".