The UNCITRAL <i>Model Law on Cross‐border Insolvency</i> and the Rule of Law
Bibliographic record
Abstract
Abstract The rule of law is a concept that was often considered in the context of national legal systems. However, it is now commonly being promoted as significant in the transnational context. This paper addresses its importance within the transnational economic and commercial context, in particular in response to cross‐border insolvencies. It examines how the UNCITRAL Model Law on Cross‐border Insolvency and its Guide to Enactment and Interpretation promote key tenets of the rule of law in transnational disputes arising out of businesses in financial distress. In particular, some examples are provided of cases from the Asia‐Pacific region in which the Model Law has been applied to demonstrate how the rule of law may be promoted in an insolvency context. Finally, the paper concludes that the adoption of the UNCITRAL Model Law on Cross‐border Insolvency promotes transparency, accountability and predictability, which in turn support stability in financial systems and credit relationships and thus trade within a global market. This is a direct result of adherence to elements of the rule of law principle. Copyright © 2016 INSOL International and John Wiley & Sons, Ltd. Copyright © 2016 INSOL International and John Wiley & Sons, Ltd
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.026 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".