Twenty Years of Rising Inequality in U.S. Lifetime Labour Income Values
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Bibliographic record
Abstract
In this paper we study the evolution of lifetime labour income inequality by constructing present value life cycle measures that incorporate both earnings and employment risk. We find that, even though lifetime income inequality is 40% less than earnings inequality, the total increase in lifetime income inequality over the past 20 years is the same as earnings inequality. While the total increase is the same, the pathways there differ with earnings inequality experiencing a steady increase and lifetime income inequality increasing in spurts particularly in the latter half of the 1990s. Finally, we find the changes in lifetime income inequality are primarily driven by changes in earnings mobility and changes in the earnings distribution itself, changes in employment risk and the composition of the sample, such as the shift toward attaining more education and the ageing population, do not play a large role. Copyright 2004, Wiley-Blackwell.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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