Bibliographic record
Abstract
Citation (2012), "Editorial Advisory Board", Polachek, S.W. and Tatsiramos, K. (Ed.) Research in Labor Economics (Research in Labor Economics, Vol. 36), Emerald Group Publishing Limited, Bingley, p. ix. https://doi.org/10.1108/S0147-9121(2012)0000036003 Publisher: Emerald Group Publishing Limited Copyright © 2012, Emerald Group Publishing Limited Book Chapters Research in Labor Economics Research in Labor Economics Research in Labor Economics Copyright Page List of Contributors Editorial Advisory Board Preface Institutions, Technological Change and Wage Differentials between Skilled and Unskilled Workers: Theory and Evidence from Europe Career and Wage Dynamics: Evidence from Linked Employer-Employee Data Position-Specific Promotion Rates and the “Fast Track” Effect The Effect of Variable Pay Schemes on Workplace Absenteeism Adverse Selection and Incentives in an Early Retirement Program The Mental Cost of Pension Loss: The Experience of Russia's Pensioners during Transition Can Long-Term Cohabiting and Marital Unions be Incentivized? Indian Entrepreneurial Success in the United States, Canada, and the United Kingdom
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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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.333 | 0.276 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".