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Record W3145965401 · doi:10.1080/03461238.2021.1895299

A law of uniform seniority for dependent lives

2021· article· en· W3145965401 on OpenAlex
Christian Genest, Nikolai Kolev

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScandinavian Actuarial Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsMcGill University
FundersFundação de Amparo à Pesquisa do Estado de São PauloNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsAnnuityMathematicsSeniorityEconometricsClosure (psychology)Extension (predicate logic)Bilinear interpolationMarginal distributionLife annuityMathematical economicsActuarial scienceEconomicsLawStatisticsComputer scienceRandom variablePolitical science

Abstract

fetched live from OpenAlex

The law of uniform seniority is an actuarial principle which justifies the replacement of an annuity on joint lives of unequal ages by an annuity on a single life, often computed at a different rate. Gompertz's law of mortality is a prime example of distribution which meets this condition. This paper proposes an extension of this principle to the case of two dependent lives and relates it to aging concepts. In the important special case of a bilinear averaging function, it is shown that the lifetimes have a dependence structure which is Archimedean and marginal distributions from the same scale family. This leads to both functional and stochastic representations for these models, which enjoy closure properties with respect to some common operations. The dependence and aging properties of the models are then discussed. The challenges involved in a multivariate extension are also mentioned.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.319
Teacher spread0.295 · 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