Income Packaging and Economic Well-Being at the Income Last Stage of the Working Career
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".