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Record W4414137171 · doi:10.1002/iir.70013

Cross‐border Insolvency in Hong Kong: Developments and Updates 2025

2025· article· en· W4414137171 on OpenAlexvenueno aff
Patrick Yung

Bibliographic record

VenueInternational Insolvency Review · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInsolvencyPosition (finance)Mainland ChinaCommon lawMainland

Abstract

fetched live from OpenAlex

Abstract In 2022, the author surveyed the extensive common law framework of providing recognition of and assistance to foreign insolvency practitioners in Hong Kong and argued that the development was intended to achieve two objectives, namely harmonizing the Hong Kong common law position with the relevant principles under the UNCITRAL Model Law on Cross‐border Insolvency, and strengthening the implementation of the mutual recognition framework on corporate insolvency proceedings between the Mainland and Hong Kong. Three years have passed, and the Hong Kong court has continued to develop the relevant jurisprudence. This article aims to review the relevant authorities between 2022 and 2025 and discuss how some new issues may be resolved in light of these two objectives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.223
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.019
GPT teacher head0.344
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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