Group concerns and communication and cooperation between practitioners under the European Insolvency Regulation (Part <scp>II</scp>)
Bibliographic record
Abstract
Abstract In this article, the author examines with a specific focus on the insolvency practitioner to what extent the Recast European Insolvency Regulation's provisions on communication, cooperation and coordination between the main actors in group companies' insolvency proceedings allow for efficient restructurings of those group companies. In doing so, the author will, at points, compare the provisions in Chapter V of the Recast European Insolvency Regulation to—and draw inspiration from—the German provisions on groups of companies that were adopted into the German Insolvency Act (Insolvenzordnung) and the United Nations Commission on International Trade Law's Model Law on Enterprise Group Insolvency. The author also aims to outline, among other things, the various forms of (cross‐border) communication, cooperation and coordination that the Recast European Insolvency Regulation obligates insolvency practitioners of groups of companies to engage in, how they should implement those forms of ‘CoCo’ and what would happen if they neglect to comply with those obligations. This article is Part II of a diptych on this topic; Part I was published in an earlier issue of this journal.
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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 | 0.027 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".