The Great Separation:Top Earner Segregation at Work in High-Income Countries
Bibliographic record
Abstract
Analyzing linked employer-employee panel administrative databases, we study the evolving isolation of higher earners from other employees in eleven countries: Canada, Czechia, Denmark, France, Germany, Hungary, Japan, Norway, Spain, South Korea, and Sweden. We find in almost all countries a growing workplace isolation of top earners and dramatically declining exposure of top earners to bottom earners. We compare these trends to segregation based on occupational class, education, age, gender, and nativity, finding that the rise in top earner isolation is much more dramatic and general across countries. We find that residential segregation is also growing, although more slowly than segregation at work, with top earners and bottom earners increasingly living in different distinct municipalities. While work and residential segregation are correlated, statistical modeling suggests that the primary causal effect is from work to residential segregation. These findings open up a future research program on the causes and consequences of top earner segregation.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".