Income Inequality as a Canadian Cohort Ages
Why this work is in the frame
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Bibliographic record
Abstract
Survey of Consumer Finances cross-sectional data from 1973 to 1996 are used in this article to examine Canadian trends in income inequality over the middle and later stages of the life course of a synthetic cohort born between 1922 and 1926. Using Gini coefficients, the findings show that income inequality decreases within a cohort as it grows old; that is, the Canadian retirement income system smoothes out (levels) the distribution of income in later life. The observed decrease in inequality corresponds with a decrease in income from earnings and an increase in dependency on state benefits. The progressive nature of public pension programs in Canada increases the relative income share and the average income of the poorest seniors. Moreover, cross-national comparisons of income inequality show that Canada exhibits a more equal distribution of income in old age compared to countries with similar old-age welfare systems, such as the United States.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.033 |
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