Healthy Life Expectancy in the Context of Population Health and Ageing in India
Bibliographic record
Abstract
This study examines life expectancy (LE) and healthy life expectancy (HLE) in India longitudinally over the period 2007 to 2020, providing projections into the future. Specifically, the Indian Healthy Life Expectancy Projection model was developed based on epidemiological data (mortality, disability rates) obtained from the World Health Organization and the Government of India. The current model contributed to 4 key findings: decreases in mortality but not in all age and gender groups; increasing disability in the Indian population over time; increase in LE and HLE into the future in all age and gender groups; and the largest gains in LE and HLE are in the older age bands starting from the 70+ age band in women and 65+ age band in men. This study sheds some light on the population health measures needed to improve the understanding of the determinants of health for the efficient allocation of resources and to inform policy in the planning of health and social services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".