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Record W2065381405 · doi:10.1177/1010539510376663

Healthy Life Expectancy in the Context of Population Health and Ageing in India

2010· article· en· W2065381405 on OpenAlexaff
Robin Lau, Shanthi Johnson, T.J. Kamalanabhan

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2010
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsSaskatchewan HealthShastri Indo-Canadian InstituteUniversity of Regina
Fundersnot available
KeywordsLife expectancyContext (archaeology)Population ageingGerontologyDemographyGovernment (linguistics)PopulationEpidemiological transitionPopulation healthEpidemiologyPublic healthMedicineEnvironmental healthGeographySociology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.071
GPT teacher head0.427
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2010
Admission routes1
Has abstractyes

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