Is Rising Income Inequality Inevitable? A Critique of the Transatlantic Consensus
Bibliographic record
Abstract
This chapter addresses one of the most important economic issues facing our societies and the world as a whole: rising income inequality. There is a widely held belief that rising inequality is inevitable. Increased inequality is the result of forces, such as technological change, over which we have no control, or the globalization of trade, which people believe, despite historical evidence to the contrary, to be irreversible. Kuznets (1955) suggested that income inequality might be expected to follow an inverse-U shape, first rising with industrialization and then declining. Today, the Kuznets curve is commonly believed to have doubled back on itself: the period of falling inequality has been succeeded by a reversal of the trend. Seen in this way, the third quarter of the twentieth century was a Golden Age not just for growth and employment, but also for its achievement in lowering economic inequality. On this basis, the marked rise in wage and income inequality observed in the United States and the United Kingdom in recent decades will unavoidably be followed by rises in other countries, and indeed worldwide. Policy can make little difference.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".