Bibliographic record
Abstract
Abstract Don Bellante Citation (2004), "Advisory Board", Kurrild-Klitgaard, P. (Ed.) The Dynamics of Intervention: Regulation and Redistribution in the Mixed Economy (Advances in Austrian Economics, Vol. 8), Emerald Group Publishing Limited, Bingley, p. xi. https://doi.org/10.1016/S1529-2134(05)08023-3 Publisher: Emerald Group Publishing Limited Copyright © 2005, Emerald Group Publishing Limited Don Bellante University of South Florida, USA James Buchanan George Mason University, USA Stephan Boehm University of Graz, Austria Peter J.Boettke George Mason University, USA Bruce Caldwell University of North Carolina, USA Jacques Garello Universit′ e d’Aix-Marseille, France Roger Garrison Auburn University, USA Jack High George Mason University, USA Masazuni Ikemoto Senshu University, Japan Richard N. Langlois The University of Connecticut, USA Brian Loasby University of Stirling, UK Ejan Mackaay University of Montreal, Canada Uskali M äki University of Helsinki, Finland Ferdinando Meacci Universit` a degli Studi di Padova, Italy Mark Perlman University of Pittsburgh, USA John Pheby University of Luton, UK Warren Samuels Michigan State University, USA Barry Smith State University of New York, USA Erich Streissler University of Vienna, Austria Martti Vihanto Turku University, Finland Richard Wagner George Mason University, USA Lawrence H. White University of Missouri, USA Ulrich Witt Max Planck Institute, Germany Book Chapters Contents List of Contributors Advisory Board Editor's Note Editor's introduction The Political Economy of the Dynamic Nature of Government Intervention: An Introduction to Potentials and Problems The Dynamics of Interventionism From Laissez-Faire to Zwangswirtschaft Austrian Economics, Praxeology and Intervention Regulation, more Regulation, Partial Deregulation, and Reregulation: The Disequilibrating Nature of a Rent-Seeking Society The Austrian Theory of the Business Cycle: Reflections on Some Socio-Economic Effects The Political Economy of Crisis Management: Surprise, Urgency, and Mistakes in Political Decision Making The Conflict About the Middle of the Road: The Austrians Versus Public Choice If Government is so Villainous, How Come Government Officials Don’t Seem Like Villains? With a New Postscript Ulysses and the Rent-Seekers: The Benefits and Challenges of Constitutional Constraints on Leviathan The Ongoing Growth of Government in the Economically Advanced Countries Interventionist Dynamics in the U.S. Energy Industry The Dynamics of Interventionism: A Case Study of British Land Use Regulation Harm Reduction and Sin Taxes: Why Gary Becker is Wrong Government Regulation of Behaviour: In Public Insurance Systems Interventionism and the Structure of the Nazi State, 1933–1939 Law and politics: Reflections upon the concept of a spontaneous order and the EU Professor Tullock on Austrian Business Cycle Theory The Austrian view of depressions
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.536 | 0.388 |
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".