Vocational Rehabilitation for Persons With Visual Impairment at the Community: A Case Study in Dong Da District, Hanoi City, Vietnam
Bibliographic record
Abstract
Work has been emphasized by the WHO, ILO, and UNESCO for years as to how individuals can escape poverty, secure the necessities and improve his/her economic and social status. In this sense, vocational rehabilitation is regarded as the means for persons with disabilities to access work. However, in the absence of either these programs or full respect for their right to work, they have been encountering different barriers in employment accessibility. This happens more seriously in developing countries, including Vietnam. Through mixed methods of desktop reviews, a survey with 110 persons with visual impairment in the community, and in-depth interviews with 10 key stakeholders, the article aims at briefing an overview on current situations of their employment as well as vocational rehabilitation services and support for occupations in Dong Da District, Hanoi City. Several key findings indicate that they have been coping with unemployment or low-tech and low-paid jobs. There is an intensive gap between needs and service supplies in physical, cognitive, and psychosocial components. In the community, available programs target supporting them in terms of physical aspects rather than cognitive and social components. Finally, the authors discuss more various vocational programs, capacity building to other potential providers, and awareness-raising.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".