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Record W4415405132 · doi:10.1007/s11205-025-03710-x

Measuring the Long and Healthy Lives of a Nation: the Health, Aging and Gender Nexus

2025· article· en· W4415405132 on OpenAlexaff
Gordon Anderson, Tongtong Hao

Bibliographic record

VenueSocial Indicators Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLife expectancyNexus (standard)Quality of Life ResearchLife course approachPublic healthHuman geography

Abstract

fetched live from OpenAlex

That a nation’s populace lives Long and Healthy Lives (LHL) is essential for its economic functioning and wellbeing. The United Nations Development Program (UNDP)’s life expectancy at birth focused LHL Index, contrary to current evidence on the health-age relationship and the health-longevity gender paradox, assumes constant health outcomes over life stage and gender divides and usually finds intertemporal improvements with superior results for women in most nations. Here, techniques that respond to ordinal data scaling critiques are developed and employed to provide indices that incorporate life stage health information. The indices are introduced in 21st Century applications to China, UK, and USA. In accord with current evidence, much variation in health outcomes over life stage and gender divides is revealed and the usual UNDP findings are reversed with intertemporal deterioration in LHL and inferior results for women, a composition effect largely the consequence of an aging population.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.320
GPT teacher head0.572
Teacher spread0.252 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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