The transaction avoidance regime in the recast European insolvency regulation: Limits and prospects
Bibliographic record
Abstract
Abstract In the last decade, transaction avoidance in insolvency law has been in the limelight of the academic discussions. In particular, the scholarship has highlighted how the European Insolvency Regulation gives rise to several private international law issues. Moreover, the scholarship has explored solutions to these issues and proposed to harmonise the regime of transaction avoidance at European Union level. However, the recent legislative developments on the cross‐border insolvency law seem resistant to the proposed harmonisation. This article focuses on the transaction avoidance regime in the Recast European Insolvency Regulation. In particular, it seeks to evaluate whether the Recast has solved the issues arising within the original European Insolvency Regulation in relation to transaction avoidance. Secondly, it questions the suitability of the private international law approach to transaction avoidance in cross‐border insolvency within the European Union framework. The research suggests that the efforts required to the private international law framework to deal efficiently with transaction avoidance make the harmonisation of the regime of transaction avoidance at the European Union level a more appealing option.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".