Disability rights advocacy and employment: A qualitative study of the National Centre for the Employment of Disabled People (NCPEDP) in India
Bibliographic record
Abstract
In India, the low rate of employment of people with disabilities is a large problem in the growing economy. Looking at one advocacy group's strategies for influencing the private sector and lobbying the Indian government for more responsive employment policies, this article focuses on NCPEDP's holistic approach to increasing employment of people with disabilities as an example of notable, innovative practice. The article examines NCPEDP's strategies towards the private sector, public policy, and civil society, including its Disability Awards (highlighting inclusive workplaces), the 2001 and 2011 Census campaigns' efforts for people with disabilities to become accurately counted, and its networks of disability organizations that disseminate relevant information and campaign for greater equality across the nation. The benefits and limitations of these strategies are then assessed for lessons regarding the strategies available to small nongovernmental organizations seeking to influence employment, the private sector and public policy in other settings.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".