Study of the Understanding of Gestural Communication in Children with Intellectual Disabilities in the Dynamics of Psychological Impact
Bibliographic record
Abstract
Objective: The purpose of the study is to investigate the specific features of non-verbal communication in children with intellectual disabilities in the dynamics of psychological impact. Background: Gestures are one of the most important components of non-verbal communication. The development of non-verbal communication in children with intellectual disabilities contributes to their normal social adaptation. Method: To study the current state and dynamics of the development of the ability to recognise and understand gestures in the process of psychological influence, factor analysis was used by the principal component method with the use of varimax rotation. To verify the applicability of factor analysis to the selected variables, the Kaiser-Meier-Olkin measure of sample adequacy and Bartlett's sphericity test were used. Results: The data of the study showed that, depending on the level of intelligence or, more precisely, on the diagnosis given to the child, there are differences in the dynamics of the development of the components of non-verbal communication. Children with mild mental retardation display lower results than children with mixed specific disorders of psychological development and children with a normative level of intellectual development. Conclusion: The results obtained in the process of this study can be applied in practice by teachers and psychologists when working with children with intellectual disabilities
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".