Adaptation of object descriptions to a partner under increasing communicative demands: a comparison of children with and without autism
Bibliographic record
Abstract
This study compared the object descriptions of school-age children with high-functioning autism (HFA) with those of a matched group of typically developing children. Descriptions were elicited in a referential communication task where shared information was manipulated, and in a guessing game where clues had to be provided about the identity of an object that was hidden from the addressee. Across these tasks, increasingly complex levels of audience design were assessed: (1) the ability to give adequate descriptions from one's own perspective, (2) the ability to adjust descriptions to an addressee's perspective when this differs from one's own, and (3) the ability to provide indirect yet identifying descriptions in a situation where explicit labeling is inappropriate. Results showed that there were group differences in all three cases, with the HFA group giving less efficient descriptions with respect to the relevant context than the comparison group. More revealing was the identification of distinct adaptation profiles among the HFA participants: those who had difficulty with all three levels, those who displayed Level 1 audience design but poor Level 2 and Level 3 design, and those demonstrated all three levels of audience design, like the majority of the comparison group. Higher structural language ability, rather than symptom severity or social skills, differentiated those HFA participants with typical adaptation profiles from those who displayed deficient audience design, consistent with previous reports of language use in autism.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".