Changing labour market and income inequalities in Europe and North America: a parallel project to the IFS Deaton Review of Inequalities in the 21<sup>st</sup>century
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The evolution of labour market and disposable income inequalities over recent decades in high‐income countries has generated intense interest in academia and the wider public. The extent to which there have been common trends, or diverging experiences, across a broad range of different countries, remains relatively understudied. The papers in this two‐part special issue seek to provide the bases for consistent comparisons across 17 North American and European countries. In this Introduction we provide background for the cross‐country project, which has been conducted in parallel to the wider IFS Deaton Review of Inequalities. In addition, we provide brief summaries of key trends and findings in the four English‐speaking countries and four Nordic countries, as well as a companion paper on gender pay gaps across all 17 countries.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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