Bibliographic record
Abstract
Egalitarian Capitalism: Jobs, Incomes and Growth in Affluent Countries. By Lane Kenworthy. New York: Russell Sage Foundation, 2004. 222p. $32.50. Two decades of rising wage and household earnings inequality in the world's wealthiest nations make the guiding question of Lane Kenworthy's book both timely and important: “[M]ust we give up on the vision of a dynamic and productive yet relatively egalitarian form of capitalism?” (p. 1). To answer this question, Kenworthy presents a careful comparative analysis of income inequality in the countries of northwestern Europe, North America, and Australia during the 1980s and 1990s. He shows that there is not necessarily a trade-off between equality and income growth, although there may be a trade-off between equality and some categories of employment growth. Hence, he argues that with an updated, pro-employment version of the welfare state, we need not give into growing disparity in advanced capitalist societies. Whether this will be desired by all and achieved remains to be seen; nevertheless, the book is an important antidote to the “there is no alternative” type of thinking that pervades much contemporary discourse on economic globalization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".