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Record W2612089185

Income Packaging and Economic Well-Being at the Income Last Stage of the Working Career

2001· preprint· en· W2612089185 on OpenAlexaboutno aff
Martin Rein, Heinz Stapf-Finé

Bibliographic record

VenueEconstor (Econstor) · 2001
Typepreprint
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsPovertyDemographic economicsSocial securityGini coefficientEconomic inequalityWorking poorTotal personal incomeEconomicsInequalityGross incomeEconomic growthPublic economics
DOInot available

Abstract

fetched live from OpenAlex

First considered, at a point in time, is how cross-country differences in the mix of income sources are related to three measures of economic well-being. Poverty, defined as 50 percent of mean-adjusted household income; relative adjusted disposable income of aged households with heads over 55 years of age relative to those under 55; and inequality as measured by the gini coefficient. Second, the broader question, namely that if the institutions providing social benefits are changing, over time, what is the likely redistributive impact of this development is addressed. The analysis focuses on income sources in the last stages of the working career. Starting at age 55, four different five-year age groups are identified to describe the last stage of the working career. LIS data is used to analyze the experience of ten countries: Australia 1994, Canada 1997, Finland 1995, Germany 1994, Netherlands 1994, Norway 1995, Sweden 1995, Switzerland 1992, United Kingdom 1995 and United States 1997. Data for Finland are available, but difficult to interpret, since the mandated earnings-related public social security is administered by a private life insurance company making the distinction between public and private especially difficult to draw. These are the only countries which had usable data on occupational pensions at the time of this first analysis. In this analysis we were able to include trends over time, broadly from 1980 to 1995, but actual available years varied by country.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.323
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2001
Admission routes1
Has abstractyes

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