LONG RUN TRENDS IN INCOME INEQUALITY IN THE UNITED STATES, UK, SWEDEN, GERMANY AND CANADA: A BIRTH COHORT VIEW
Bibliographic record
Abstract
This paper examines the level and distribution of equivalent after tax, after transfer money income in Canada, the United States, the UK, Germany and Sweden using micro-data from the Luxembourg Income Study from 1969/70 to 1994/95. It concentrates on inequality within and between birth cohorts. At any point in time, less than 11% of aggregate income inequality is due to intergenerational inequality. Although median income growth of different birth cohorts over the period has varied widely across countries, there has been a general trend to greater income inequality within cohorts since 1980. The five countries studied differ in the trends observed in aggregate income, poverty, polarization and income inequality. In the United States and the UK, the incomes of the top decile of each cohort have risen dramatically, but the incomes of the bottom quintile have stagnated. In Canada and Sweden both the top and bottom deciles of each cohort have experienced similar trends. Germany is an intermediate case.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".