Recognition, Expression, and Understanding Facial Expressions of Emotion in Adolescents With Nonverbal and General Learning Disabilities
Bibliographic record
Abstract
Children with nonverbal learning disabilities (NVLD) have been found to be worse at recognizing facial expressions than children with verbal learning disabilities (LD) and without LD. However, little research has been done with adolescents. In addition, expressing and understanding facial expressions is yet to be studied among adolescents with LD subtypes. This study examined abilities of adolescents with NVLD, with general learning disabilities (GLD), and without LD to recognize, express, and understand facial expressions of emotion. Adolescents were grouped into those with NVLD, with GLD, and without LD using the Wechsler Intelligence Scale for Children-Third Edition (short form) and Wide Range Achievement Test-Third Edition. The adolescents completed neuropsychological, recognition, expression, and understanding measures. It is intriguing that the GLD group was significantly less accurate at recognizing and understanding facial expressions compared with the NVLD and NLD groups, who did not differ. Implications are explored with regard to the need to consider possible deficits in recognition and understanding of emotion in adolescents with LD in schools.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".