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Record W2885412554 · doi:10.3386/w24929

The Evolution of Longevity: Evidence from Canada

2018· report· en· W2885412554 on OpenAlexafffundabout
Kevin Milligan, Tammy Schirle

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typereport
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of British Columbia
FundersNational Taiwan UniversityEmployment and Social Development CanadaDalhousie UniversityWilfrid Laurier University
KeywordsLongevityEconomicsBiologyGenetics

Abstract

fetched live from OpenAlex

We find a steep earnings-longevity gradient using fifty years of administrative data from Canada, with men in the top ventile of earnings living eight years (11 percent) longer than those in the bottom ventile.For women, the difference is 3.6 years.Unlike the United States, this longevity gradient in Canada has shifted uniformly through time, with approximately equal gains across the earnings distribution.We compare our results using cross-sectional and cohort-based methods, finding similar trends but a steeper gradient when using cohorts.For middle-aged men, we find a cessation of mortality improvements in recent years, comparable to changes observed in the United States.Changes in income do not explain cross-time or cross-country differences.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.022
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.014
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.582
GPT teacher head0.650
Teacher spread0.068 · 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

Citations16
Published2018
Admission routes3
Has abstractyes

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