A major step in developing Mainland China's cross‐border insolvency law
Bibliographic record
Abstract
Abstract Section 5 of Mainland China's Enterprise Bankruptcy Law provides that, in the absence of treaties, Chinese courts may recognise foreign insolvency proceedings based on reciprocity. The meaning of reciprocity is very uncertain, and no rules have been laid down on how recognition or assistance may be given to foreign insolvency proceedings. The Mainland has not entered into any treaty or arrangement on the matter with another jurisdiction. On 14 May 2021, the Mainland signed an agreement with Hong Kong, under which the Mainland issued an Opinion on the rules for the recognition of and assistance to Hong Kong insolvency proceedings. This article argues that this is a momentous development for both the Mainland and Hong Kong. It explains how the Opinion adapted provisions and ideas from the UNCITRAL Model Law on Cross‐Border Insolvency with modifications to suit the Mainland's needs and the objectives it wanted to achieve; in particular, the Mainland's concern with mitigating the risks arising from the Opinion's implementation. At the same time, however, cases decided after the coming into force of the arrangement revealed the hurdles posed by the corporate structure that Chinese groups in Hong Kong adopted to the utility of the arrangement, foreshadowing dynamic developments in practice and debate in the doctrinal and theoretical spheres.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".