Bibliographic record
Abstract
Citation (2016), "List of Contributors", Studies in Austrian Macroeconomics (Advances in Austrian Economics, Vol. 20), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S1529-213420160000020016 Publisher: Emerald Group Publishing Limited Copyright © 2016 Emerald Group Publishing Limited Peter J. Boettke Department of Economics, George Mason University, Fairfax, VA, USA George Bragues University of Guelph-Humber, Toronto, Canada Nicolás Cachanosky Department of Economics, Metropolitan State University of Denver, Denver, CO, USA Mark Cohen Department of Economics, Kenyon College, Gambier, OH, USA Thomas L. Hogan Johnson Center for Political Economy, Troy University, Troy, AL, USA Steven Horwitz Department of Economics, St. Lawrence University, Canton, NY, USA Peter Lewin Naveen Jindal School of Management, University of Texas at Dallas, Dallas, TX, USA William J. Luther Department of Economics, Kenyon College, Gambier, OH, USA G. P. Manish Johnson Center for Political Economy, Troy University, Troy, AL, USA Robert F. Mulligan School of Business & Economics, Indiana University East, Richmond, IN, USA Patrick Newman George Mason University, Fairfax, VA, USA Liya Palagashvili Faculty of Economics, Purchase College, State University of New York, Purchase, NY, USA Alexander W. Salter Department of Economics, Rawls College of Business, Texas Tech University, Lubbock, TX, USA Andrew T. Young Department of Economics, College of Business and Economics, West Virginia University, Morgantown, WV, USA Book Chapters Studies in Austrian Macroeconomics Advances in Austrian Economics Studies in Austrian Macroeconomics Copyright Page List of Contributors About the Contributors Introduction: Money, Cycles, and Crises in the United States and Canada Part I: Austrian Monetary and Business Cycle Theory Financial Foundations of Austrian Business Cycle Theory The Optimal Austrian Business Cycle Theory Hayek on the Neutrality of Money On the Empirical Relevance of the Mises–Hayek Theory of the Trade Cycle Expansionary Monetary Policy at the Federal Reserve in the 1920s Part II: The US and Canadian Experience Compared The Political Regime Factor in Austrian Business Cycle Theory: Historically Accounting for the US and Canadian Experiences of the 2007–2009 Financial Crisis An Empirical Comparison of Canadian-American Business Cycle Fluctuations with Special Reference to the Phillips Curve Canadian versus US Mortgage Markets: A Comparative Study from an Austrian Perspective Part III: The Political Economy of Regulation and Crisis Banking Regulation and Knowledge Problems The Comparative Political Economy of a Crisis Policy Design and Execution in a Complex World: Can We Learn from the Financial Crisis?
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.126 | 0.009 |
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; both teacher heads 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".