The interdisciplinarity of economics
Bibliographic record
Abstract
Abstract Economics has the reputation to be an insular discipline with little consideration for other social sciences and humanities (SSH). Recent research (Angrist et al., 2020) challenges this perception of economics: the perception would be historically inaccurate and especially at odds with the recent interdisciplinarity of economics. By systematically studying citation patterns since the 1950s in thousands of journals, we offer the best established conclusions to date on this issue. Our results do show that the discipline is uniquely insular from a historical point of view. But we also document an important turn after the 1990s that drastically transformed the discipline as it became more open, very quickly, to the influence of management, environmental sciences and to a lesser degree, a variety of the SSH. While this turn made economics less uniquely insular, as of today economics remains the least outward-looking discipline with management among all SSH. Furthermore, unlike in the other major social sciences, the most influential journals in economics have not significantly contributed to the recent increase in the interdisciplinarity of the discipline. While economics is changing, it is too soon to claim that it has completed an interdisciplinary turn.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".