Which Skills Do Students with Intellectual Disabilities Need for Pursuing Leisure Activities After Graduation? A Survey among Vocational Rehabilitation Practitioners in Japan
Bibliographic record
Abstract
Background: Leisure activities contribute to the quality of life and continuation of employment for individuals with disabilities. However, education related to leisure activities is inadequate in special needs schools in Japan. Purpose: This study aimed to clarify which components of leisure guidance are considered important by vocational rehabilitation practitioners in Japan. Methods: An online survey was conducted in 337 branches of the Support Center for Employment and Livelihood of Persons with Disabilities in Japan. Results: Employment support practitioners recognized the importance of teaching students how to use their leisure time outside of working hours and helping them cultivate skills necessary to engage in leisure activities, regardless of whether they were still in school or had already graduated. In school, importance was placed on providing activities aimed at expanding leisure opportunities after graduation. For the period after graduation, the emphasis shifted to acquiring specific abilities necessary for engaging in leisure activities with other people, such as money management and securing means of transportation. Conclusion: This study provides a direction for optimizing the quality of leisure guidance for individuals with special needs. The findings can help improve teaching practices in special needs schools and enhance the effectiveness of transition support for students with 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".