Pre-Keynesian and non-Keynesian British analysis of unemployment and real and money wages
Bibliographic record
Abstract
Volume 8 Pre-Keynesian and Non-Keynesian British Analysis of Unemployment 1. A. C. Pigou, 'Wage Policy and Unemployment,' Economic Journal, 37, September 1927, pp. 355-368, and Errata, 37, December 1927, p. 688 2. Henry Clay, 'Unemployment and Wage Rates,' economic Journal, 38, March 1928, pp. 1-14 3. Edwin Cannan, 'The Demand for Labour,' Economic Journal, 42, September 1932, pp. 357-370 4. W. H. Beveridge, 'An Analysis of Unemployment, Parts I-III,' Economica, New Series, 3, November 1936, pp. 357-386, 4, February 1937, pp. 1-17 and 4, May 1937, pp. 168-183 Real and Money Wages 5. Lorie Tarshis, 'An Exposition of Keynesian Economics,' American Economic Review, 38, Supplement, May 1948, pp. 261-272 6. Lorie Tarshis, 'Real Wages in the United States and Great Britain,' Canadian Journal of Economics and Political Science, 4, August 1938, pp. 362-376 7. Lorie Tarshis, 'Changes in Real and Money Wages,' Economic Journal, 49, March 1939, pp. 150-154 8. John T. Dunlop, 'The Movement of Real and Money Wage Rates,' Economic Journal, 48, September 1938, pp. 413-434 9. J. M. Keynes, 'Relative Movements of Real Wages and Output,' Economic Journal, 49, March 1939, pp. 34-51 10. Richard Ruggles, 'The Relative Movements of Real and Money Wage Rates,' Quarterly Journal of Economics, 55, November 1940, pp. 130-149 11. John T. Dunlop, 'Real and Money Wage Rates: Reply,' Quarterly Journal of Economics, 55, August 1941, pp. 683-691 12. Lorie Tarshis, 'Real and Money Wage Rates: Further Comment,' Quarterly Journal of Economics, 55, August 1941, pp. 691-697 13. Richard Ruggles, 'Rejoinder,' Quarterly Journal of Economics, 55, August 1941, pp. 697-700 14. James Tobin, 'A Note on the Money Wage Problem,' Quarterly Journal of Economics, 55, May 1941, pp. 508-516 15. Sho Chieh Tsiang, The Variations of Real Wages and Profit Margins in Relation to the Trade Cycle, London, Sir Isaac Pitman, 1947
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".