Creditors' treatment under the new <scp>Italian</scp> “<scp>Concordato Preventivo</scp>” and directive (<scp>EU</scp>) 2019/1023: A comparison with chapter 11
Bibliographic record
Abstract
Abstract This article compares the treatment of creditors in Italy under the “new” judicial composition with creditors (CWC) (“concordato preventivo”) procedure (as recently amended by the new Italian Business Crisis and Insolvency Code of 2022) with Chapter 11 of the US Bankruptcy Code, focusing on two main issues. The first issue analyses the impact of the Directive (EU) 2019/1023, which aims to remove barriers to fundamental freedoms and promote market efficiency by introducing, among others, preventive restructuring frameworks (PRFs). The Directive's guidelines on the treatment of creditors, including the requirement to allocate restructuring proceeds on the basis of the “relative priority rule (RPR)”, are examined. The second issue discusses Italy's new Business Crisis and Insolvency Code of 2022, which introduces several innovations to judicial CWC proceedings. These include facilitations for CWC on a going concern basis, a mandatory division of creditors into classes, a new voting and cramdown system, and significant changes to the distribution of restructuring proceeds, also to comply with Directive (EU) 2019/1023.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".