Tolerance and social inclusion as a condition for successful rehabilitation of persons with disabilities
Bibliographic record
Abstract
The academic paper is devoted to studying the features of the attitude of teachers, parents, employers towards people from different social groups in need of social inclusion and rehabilitation. A survey of 120 people (40 primary school teachers, 40 parents of healthy children, 40 employees of the State Employment Service of Ukraine) was conducted on their attitude to people in need of social-psychological and social-labour rehabilitation. The survey was conducted in 2 stages. At the first stage, it has been found out whom exactly the respondents consider to be those who require social and psychological assistance and rehabilitation. In the second stage, a modification of the method of E. S. Bogardus has been applied in order to determine social distance. Teachers and parents believe that children with disabilities need rehabilitation, involvement in an inclusive school community and increased attention. Regarding the categories with other health disorders (ADHD and dysgraphia), the viewpoint of teachers is quite unanimous ‒ they know about these students and believe that they need above average teachers’ attention. However, while parents are aware of the presence of children with ADHD, they are almost unfamiliar with children with reading and writing disorders. Children with mental disorders, autism and ADHD have the greatest problems with integration into inclusive communities. They are ready to be perceived at the maximum social distance ‒ in a special school, in a boarding school, except sporadically on the playground. For employees of the employment service, the maximum social distance was for people with mental and psychological disorders. According to experts’ viewpoints, employers do not want to hire people with these disorders.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".