Conflicts of interest, intra‐group financing and procedural coordination of group insolvencies
Bibliographic record
Abstract
Abstract Modern insolvency law instruments recognise the specificity of enterprise group insolvencies, premised on the existence of close operational and financial links between group members. It is widely accepted that maximisation of insolvency estate value and procedural efficiency depend on coordination of insolvency proceedings opened with respect to group entities. Such coordination is prescribed in the European Insolvency Regulation (recast), the United Nations Commission on International Trade Law (UNCITRAL) Model Law on Enterprise Group Insolvency and the recently reformed German insolvency law. Yet in insolvency, group members retain their own insolvency estates and pools of creditors. This is based on the traditional company law principle of entity shielding. Active communication and cooperation between insolvency practitioners and courts do not sit well with the separate (atomistic) nature of insolvency proceedings, as well as different and oftentimes conflicting interests of creditors in such proceedings. As a result, communication and cooperation may be restricted in a situation of conflicts of interest. This article explores how in the context of group distress the risks arising from conflicts of interest can be controlled and mitigated, while ensuring efficient cross‐border cooperation and communication to the maximum extent possible. It analyses three cutting‐edge coordination mechanisms, namely (a) cross‐border insolvency agreements or protocols, (b) special (group coordination and planning) proceedings and (c) the appointment of a single insolvency practitioner. It concludes that both the likelihood and significance of conflicts of interest correlate with the degree of procedural coordination. Therefore, conflict mitigation tools and strategies need to be tailor‐made and targeted at a specific level and coordination mechanism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".