Study of Pragmatic Skills of Persian-speaking Adults with Autism Spectrum Disorder Based on the Persian Version of Montreal Protocol for the Evaluation of Communication (P.M.E.C.)
Bibliographic record
Abstract
Background: Various studies have shown that individuals with autism spectrum disorder (ASD) experience significant cognitive impairments during childhood. Individuals often experience various language disorders that can manifest in different ways. There are also studies indicating that these impairments persist into adulthood for individuals with ASD. This study aimed to evaluate and identify cognitive impairments among Persian-speaking adults with ASD. Methods: This research is of a quantitative nature and has been conducted using an experimental method in which two subtests from the Persian Version of the Montreal Protocol for the Evaluation of Communication (P.M.E.C.), including the Metaphor Interpretation and Speech Act Interpretation subtests, were utilized. Thirteen Persian-speaking men with ASD participated in this research, with ages ranging from 25 to 44 years (mean age 32.84, standard deviation 4.17), whose educational levels varied from primary school to 20 years of formal education. The control group consisted of 26 healthy Persian-speaking men who were matched in terms of age and educational level with the ASD group. The Kolmogorov-Smirnov test and a paired t-test were used to compare the two groups. Results: = 0.033) compared to the healthy control group, suggesting cognitive impairments in their abilities. Conclusion: The findings of this research can be valuable for assessment and intervention purposes in rehabilitation centers, as well as in academic and research settings.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| 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".