The Geoeconomics of the Single Market for Financial Services
Bibliographic record
Abstract
Abstract We discuss the geoeconomics of the Single Market in financial services in the European Union (EU). We examine three case studies that concern the EU and other major jurisdictions and that range from incipient geoeconomic use to outward weaponisation of the Single Market in finance. These cases are (1) the post‐2008 crisis transatlantic tug of war, whereby the EU leveraged its Single Market vis‐à‐vis the United States, seeking to set the rules for global finance; (2) the Brexit negotiations, when the EU acted as a bloc against the United Kingdom and successfully safeguarded the integrity of the Single Market; and (3) the fulsome war in Ukraine, during which the EU ‘weaponised’ its Single Market through the adoption of financial sanctions against Russia. We argue that a combination of external and internal factors accounts for this pattern: the evolution of the international economic and political system, in particular, the increasing challenges to the liberal international order, and intra‐EU developments, namely, the EU's ability to deploy its Single Market geoeconomically.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".