States and new markets: the novelty problem in the IPE of finance
Bibliographic record
Abstract
Finance has changed, and the study of finance needs to change with it. Previously marginal actors—hedge funds, index providers, tech firms, etc.—have become lynchpins in the global financial system. Likewise, the traditional subjects of international political economy (IPE)—states, international organizations, banks, central banks, etc.—are engaging in once-peripheral spheres. Yet, these novel trends have been largely ignored in mainstream political science and international relations venues for IPE scholarship. We demonstrate this through a discussion of two trends—the rise of shadow banking and central bank involvement in climate change—and an analysis of publications in top international relations and political science journals. While previous commentaries identify a methodological and epistemological divide in IPE, our results suggest an empirical one. We then construct a practical framework to remedy this problem by returning to the work of Susan Strange. Strange’s approach embodied a radical ontology, a focus on structures and their interaction, and an analytical eclecticism that provided keen insights into the politics of finance. We argue that these principles, often embraced in Review of International Political Economy, should be applied more broadly by IR scholars to better contribute to debates on emerging political economic issues.
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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 | 0.000 | 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) | 0.000 | 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".