Spaces and Places: A Systems Theory Approach to Regulatory Competition in European Company Law
Bibliographic record
Abstract
Abstract: This article takes issue with the longstanding oppositional themes of harmonisation versus regulatory competition in European company law. Instead of embracing one approach over the other in exclusivity, the article draws attention to the persisting mixture of approaches to an emerging European‐wide law regulating the business corporation. Against the background of an ongoing struggle over identifying the goals and taboos of the European legislator's mandate in regulating the company, the argument put forward here is that this very struggle is reflective of the nature of the evolution of company law in an ‘integrating Europe and a globalising world’. European attempts of developing European company law as part of a larger initiative of improving the Union's potential for innovation and competition are thus likely to meet with the challenges that contemporary Nation States are facing when adapting their modes of regulation and representation to the demands of an increasingly complex and decentralised fields of market activities. Situating the law of the business corporation within the larger theme of European integration on the one hand, and of issues of market regulation, domestic, transnational, and international, on the other, suggests the adoption of a systems theory‐based approach to understanding the boundaries of law in this multilevel and multipolar process.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".