Of Magnets and Centrifuges: The US and EU Federal Systems and Private International Law
Bibliographic record
Abstract
This chapter is part of a tribute to Professor Alberta Sbragia upon her retirement at the University of Pittsburgh. Professor Sbragia, a political scientist, has contributed much to to the understanding of the development of the European Union and its institutions. She has been a wonderful colleague. In my tribute to her, I consider the federal systems in the United States and the European Union as viewed through the lens of private international law. While some may be hesitant to refer to the European Union as a “federal” system, when viewed in the context of private international law it becomes apparent that the EU system is both more centralized and more predictably developed than is its counterpart in the United States. I have referred to this comparison in the past as resulting in the EU magnet and the US centrifuge. In this chapter, I trace my personal experience in dealing with the development of private international law for over 25 years at the Hague Conference on Private International Law. This experience has provided the opportunity for first-hand observation of the evolution of EU competence in private international law and its effect on global developments. Using my personal experience in the process, I review the developments which have led to centralization of private international law within the European Union, consider how the federal system in each of the United States and the European Union has influenced this area of the law, and draw conclusions about how each has used its own federal approach in this area of the law to influence global development of the law.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".