Income Inequality over the Later-Life Course: a Comparative Analysis of Seven OECD Countries
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT This paper examines income inequality over stages of the later-life course (age 45 and older) and systems which can be used to mitigate this inequality. Two hypotheses are tested: (1) levels of income inequality decline during old age because public benefits are more equally distributed than work income; and (2) because of the progressive nature of government benefits, countries with stronger public income security programmes are better able to reduce income inequalities during old age. The analysis is performed by comparing age groups within seven OECD countries (Canada, Germany, the Netherlands, Norway, Sweden, the United Kingdom, and the United States of America) using Luxembourg Income Study data from around 2000. Both hypotheses are supported. Several conclusions are drawn from the findings.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it