Bibliographic record
Abstract
Books reviewed: David Coates. Models of Capitalism: Growth and Stagnation in the Modern Era. David Coates. Models of Capitalism: Debating Strengths and Weaknesses: Volume 1, Capitalist Models: Divergence and Convergence; Volume 2, Capitalist Models under Challenge; Volume 3, The Ascendancy of Liberal Capitalism Peter Ackers and Adrian Wilkinson. Understanding Work & Employment: Industrial Relations in Transition. Gregory K. Dow. Governing the Firm: Workers’ Control in Theory and Practice. Mario Baldassarri. How to Reduce Unemployment in Europe. Paul Edwards. Industrial Relations: Theory and Practice. Richard N. Block, Karen Roberts and R. Oliver Clarke. W. E. Labour Standards in the United States and Canada. Charlotte Rayner, Helge Hoel and Gary Cooper. Workplace Bullying: What We Know, Who Is to Blame, and What Can We Do? Ståle Einarsen, Helge Hoel, Dieter Zapf and Cary L. Cooper. Bullying and Emotional Abuse in the Workplace: International Perspectives in Research and Practice Michael Hogg and Deborah J. Terry. Social Identity Processes in Organizational Contexts Gabrielle Meagher. Friend or Flunkey? Paid Domestic Workers in the New Economy
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.539 | 0.501 |
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".