The Social Question in the Twenty-First Century : A Global View (Edition 1)
Bibliographic record
Abstract
A free open access ebook is available upon publication. Learn more at www.luminosoa.org. Want, disease, ignorance, squalor, and idleness: first recognized together in mid-nineteenth-century Europe, these are the focus of the Social Question. In 1942 William Beveridge called them the “giant evils” while diagnosing the crises produced by the emergence of industrial society. More recently, during the final quarter of the twentieth century, the global spread of neoliberal policies enlarged these crises so much that the Social Question has made a comeback. The Social Question in the Twenty-First Century maps out the linked crises across regions and countries and identifies the renewed and intensified Social Question as a labor issue above all. The volume includes discussions from every corner of the globe, focusing on American exceptionalism, Chinese repression, Indian exclusion, South African colonialism, democratic transitions in Eastern Europe, and other phenomena. The effects of capitalism dominating the world, the impact of the scarcity of waged work, and the degree to which the dispossessed poor bear the brunt of the crisis are all evaluated in this carefully curated volume. Both thorough and thoughtful, the book serves as collective effort to revive and reposition the Social Question, reconstructing its meaning and its politics in the world today.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".