The European Commission Project Regarding Competition in Professional Services
Bibliographic record
Abstract
One goal of this article is to help EU Member States' policy-makers and citizens understand the broad-brush nature of the EU Initiative and remember that it was a call for further investigation by EU Member States. This article provides a detailed case study of the EU Initiative so that as many individuals as possible in the European Union can understand the issues at stake and participate in rigorous discussions about the justifications for, and costs and benefits of, particular lawyer regulation rules in particular countries. Although one goal of this article is to empower European stakeholders and policy-makers, it is not this article's only goal. The EU Initiative is certainly important because of the profound effect it has had and will continue to have on the regulation of the legal profession in Europe. There is an additional reason, however, why it is important. In a globalized world, regulatory changes that happen in one country are increasingly likely to be reproduced in some fashion in other countries.5 Thus, the European Union's legal profession antitrust initiatives are important because they have the potential to migrate and change the nature of the lawyer regulation debate in the United States. Other countries, including Canada, have launched similar inquiries. For this reason, it is useful for U.S. lawyers to be familiar with the EU Initiative. In my view, there is an important role to be served by a detailed case study that shows how and when the EU Initiative evolved so that U.S. lawyers can be better prepared to respond should a similar development "jump the pond" to the United States. This is particularly important in light of the EU Initiative's "tidal wave" momentum, which has been cited in OECD and EU studies and by countries such as Canada.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.018 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".