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Record W2753158659 · doi:10.12735/jfe.v6n1p1

Addressing Longevity’ Heterogeneity in Pension Scheme Design

2017· article· en· W2753158659 on OpenAlex
Mercedes Ayuso, Jorge Miguel Bravo, Robert Holzmann

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Finance & Economics · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
FundersEuropean Regional Development FundBanco Bilbao Vizcaya ArgentariaMinisterio de Economía y CompetitividadUniversity of New South WalesWorld Bank Group
KeywordsLongevityPensionScheme (mathematics)Actuarial scienceLongevity riskEconomicsComputer scienceMedicineGerontologyMathematicsFinance

Abstract

fetched live from OpenAlex

This paper demonstrates that the link between heterogeneity in longevity and lifetime income across countries is mostly high and often increasing; that it translates into an implicit tax/subsidy, with rates reaching 20 percent and higher in some countries; that such rates risk perverting redistributive objectives of pension schemes and distorting individual lifecycle labor supply and savings decisions; and that this in turn risks invalidating current reform approaches of a closer contribution-benefit link and life expectancy-indexed retirement age. The paper suggests and explores a number of interventions in the accumulation, benefit determination, and disbursement stages to address longevity' heterogeneity.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.344
GPT teacher head0.499
Teacher spread0.155 · 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