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Record W2159504266 · doi:10.1080/13504850500425261

Convergence of life expectancy in the European Union: a Markov approach

2007· article· en· W2159504266 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Economics Letters · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsInstitute of Health Economics
Fundersnot available
KeywordsConvergence (economics)Life expectancyEuropean unionMember statesPaceMarkov chainMarkov processEconometricsEuropean integrationEconomicsInternational economicsGeographyEconomic growthMathematicsStatisticsSociologyDemographyPopulation

Abstract

fetched live from OpenAlex

Given efforts of integration within the European Union (EU), convergence of life expectancies in member-states should be observed. A Markov approach classifying 15 EU member-states is applied to OECD data covering 1980 to 1989 and 1989 to 1998. The dynamics of cross-sectional distributions and the pace of their transitional processes are analyzed. In the 1980s slow convergence can be observed, whereas in the 1990s convergence is close to non-existent. Markov modelling shows that EU member states did not continue to converge in life expectancy following 1989, suggesting that efforts of socio-economic integration do not affect this public health indicator.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.522
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.321
Teacher spread0.287 · 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