Economic Methodology: A Bibliometric Perspective
Bibliographic record
Abstract
Using tools from social network analysis, we study citation patterns since the early 1990s in the two most important journals in economic methodology (aka philosophy of economics). We mostly focus on assessing four historical claims in the existing interpretive literature. In agreement with the literature, we find that (1) it is sensible to split the field along three dimensions (corresponding to action theory, ethics and philosophy of science) and that (2) the interest for general philosophical questions (known as Big M) has steadily declined. Contra the literature, we find that (3) there is no move away from heterodox economics in the main journals: no significant interest was present to begin with. Finally, we update the literature regarding an alleged move toward the study of mainstream pluralism: (4) although this direction describes well the early 2000s, the field in the 2010s is better characterized as mainly fascinated by behavioral economics.
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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 | 0.018 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.086 | 0.118 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".