Certifying Intellectual Disability Efficiently and Accurately in a Low-Health-Resource Setting: A Case Study
Bibliographic record
Abstract
[This article was written and submitted for peer review in 2020.]Certifying intellectual disability (ID) in low-health-resource countries with a high burden of ID is a challenge because the process must be both efficient and accurate. As a case study of this challenge, this article examines the certification guidelines that have been used in India since 2018, which define whether an individual qualifies for government benefits including a monthly pension. The section of the guidelines discussing the certification of ID has yet to be comprehensively assessed in the literature. To address this need, the present study establishes trends in expert opinion on the topic using informant interviews conducted with researchers and representatives of Organisations for Persons with Disabilities (n = 10). Three overall topics emerged from the interviews: the administrative process, the usage of psychometric instruments, and the relative importance of medical and social criteria. Despite disagreements in the first and third of these areas, there were overall trends in all three areas. The views of the participants were analysed using Cornia and Stewart’s framework of “E-mistakes” (excess coverage) and “F-mistakes” (failure to cover). This led to tentative recommendations for changes to the guidelines spanning all three areas from the results. The administrative process could be simplified by reducing the frequency with which a four-member medical board is consulted, by allowing community-based rehabilitation workers to conduct the certification, or by establishing co-operation with Organisations for Persons with Disabilities who keep records on disability. The psychometric criteria could be improved through the addition of the Indian Disability Evaluation and Assessment Scale and, where appropriate, developmental quotient in place of intelligence quotient. Social criteria like socioeconomic status could be included alongside medical criteria, in line with the biopsychosocial model of disability. This case study has implications for future revisions of the guidelines and for the certification of ID in other developing countries.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".