Competition Law in EU Free Trade and Cooperation Agreements (And What the UK Can Expect after Brexit)
Bibliographic record
Abstract
This paper outlines the system of concentric circles of cooperation in competition law enforcement around the European Union (EU). It examines the intergovernmental and inter-agency agreements which the EU concluded in order to address the complexities of the transnational economy of the 21st century. It then turns to a development that does not fit this neat picture of ever-increasing cooperation at all: Brexit and its implications. National competition law enforcers face an increasingly transnational economy. The increase in free trade and competition advocacy has resulted in a proliferation of national competition law regimes. The patchwork of multiple unilateral enforcement by individual states leads to enforcement gaps and enforcement overlaps. While some call for global solutions to global problems and advocate a global competition agency (or appointing a lead jurisdiction), it is questionable if such centralisation would be desirable and at any rate it does not seem politically feasible. The intermediate path between pure unilateral enforcement and a centralised global enforcer consists in unilateral enforcement tempered by cooperation and coordination of enforcement activities. Regional cooperation leads to internally relatively homogeneous clusters, and reduces complexity on the global scale. The extremely close cooperation in such regional cooperation agreements is supplemented by a second layer of reciprocal cooperation links, which are characterised by a slightly lower but still high degree of internal homogeneity, and accordingly cooperation that does not go quite as far as the one in the central region. As we move in concentric circles further away from the centre, heterogeneity of competitive conditions or interests increases and the depth of cooperation decreases. This results in regional clusters. Within each cluster, issues of gaps and overlaps can be reduced to the greatest possible extent. Some of the clusters are interconnected among each other by bilateral links (such as CETA between the EU and Canada). Between clusters, the weaker cooperation and coordination may not resolve all gaps and overlaps, but as global heterogeneity of views on competition policy decreases through the work of international organisations (such as the OECD, the ICN or APEC), gradual progress is made here as well. Brexit will take the United Kingdom (UK) out of the EU, and most likely the European Economic Area (EEA) and the Customs Union as well. This means that the UK will have to negotiate not only its competition cooperation with the EU and its Member States, but also needs to replicate the links to the many jurisdictions to which the UK had links by virtue of its EU membership.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.019 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.014 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".