THE RESEARCH PROGRAM OF THE AUSTRIAN SCHOOL 2011-2020: RECENT TRENDS AND DEVELOPMENTS
Bibliographic record
Abstract
Los trabajos publicados en las revistas académicas de la Escuela Austriaca de Economía se utilizan para posicionar a académicos e instituciones por productividad de investigación en Economía Austriaca en el periodo que comprende la década de 2011 a 2020. Las revistas incluidas en este estudio son Procesos de Mercado: Revista Europea de Economía Política, Quarterly Journal of Austrian Economics, Review of Austrian Economics, Cosmos + Taxis, Advances in Austrian Economics, y Journal des Économistes et des Études Humaines. La metodología se ha desarrollado para posicionar programas porproductividad de investigación convencional en las ciencias sociales pero ha sido adaptada para enfocarse exclusivamente en revistas sobre la Escuela Austriaca. El ejercicio de posicionamiento ofrece la oportunidad de evaluar y valorar el progreso de la Escuela Austriaca a lo largo de la última década. Se sugieren implicaciones a futuro.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".