Factors Impacting Employment Opportunities and Outcomes for Individuals with Disabilities in Nepal
Bibliographic record
Abstract
This study was undertaken to analyze the factors impacting employment opportunities and outcomes of People with disabilities (PWDs). Also, to measure the satisfaction level of employed PWDs on their current work. The study has collected the required information and data from 200 PWDs using a purposive sampling method. Logistics regression analysis was carried out to analyze the factors impacting employment opportunities and outcomes of PWDs. Likert scale analysis was carried out to measure the satisfaction level of employed PWDs with their current work. The study found that the age at which disability onset, marital status, family size, years of schooling, severity, and access to assistive devices had a significant association with employment of PWDs. Fewer employed PWDs (7.7%) had permanent work status. However, most of the employed PWDs were satisfied with their current work. The family support and level of education of PWDs were the major predictors of employment. The study recommends providing counselling services to the families of PWDs along with sensitizing concerned stakeholders to improve the well-being and participation of PWDs.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".