MétaCan
Menu
Back to cohort
Record W2264519194

Change in Health Expectancy in the Canadian Population: 1994/95 - 2000/01

2003· article· en· W2264519194 on OpenAlexaffabout
Ruolz Ariste

Bibliographic record

VenueSSRN Electronic Journal · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversité LavalUniversité du Québec en Outaouais
Fundersnot available
KeywordsLife expectancyPopulation healthGerontologyDemographyPopulationQuality of life (healthcare)Index (typography)Health indicatorHealth and Retirement StudyMedicineNational Health Interview SurveyPsychologyEnvironmental healthSociology
DOInot available

Abstract

fetched live from OpenAlex

With increasing life expectancy, lengthening working life may be an attractive idea for young seniors, as well as appealing to policymakers concerned with an increasing dependency ratio of non-workers to workers, if Canadians can expect to live in good health significantly beyond the age of retirement. Using a dichotomous health-related quality of life (HRQOL) measure such as prevalence of disability at 65 years to weight life-years lived, some studies find that disability levels are quite low and decreasing, suggesting that health expectancy at 65 is increasing. Using new longitudinal data from four cycles of the National Population Health Survey (NPHS), we test whether this trend is apparent for all age groups, and when using a polychotomous HRQOL measure such as Health Utility Index. As expected, health expectancy is still increasing for both sexes. These findings apply to both the younger and the older population, although to a much less extent to older females. We also found some compression of morbidity for males, but some expansion of morbidity for older females.

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)0.004
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 score0.051
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.135
GPT teacher head0.406
Teacher spread0.271 · 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

Citations0
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicRetirement, Disability, and EmploymentFrench-language works237,207