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Record W3201216174 · doi:10.1002/iir.1424

Directors' duties to prevent insolvent trading in a crisis: Responses to <scp>COVID</scp>‐19 in Australia and lessons from Germany

2021· article· en· W3201216174 on OpenAlexvenueno aff
Stacey Steele

Bibliographic record

VenueInternational Insolvency Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInsolvencyCreditorRestructuringStatutory lawDebtorBusinessBankruptcyLegislationForce majeureGermanFinancial crisisObligationLawFinanceEconomicsPolitical scienceDebt

Abstract

fetched live from OpenAlex

Abstract This article considers relief from directors' duties to avoid trading whilst insolvent during the COVID‐19 pandemic in Australia and Germany. Comparative insolvency law literature traditionally compares Australia to jurisdictions such as the United Kingdom and New Zealand. However, Germany has a track record of using insolvency law to manage social and economic crises. The German approach suggests solutions to critical issues not dealt with in the Australian safe harbour legislation, such as the failure to suspend other statutory duties to provide clear guidance to directors on the balancing of various interests, and the treatment of potential voidable transactions and new monies (i.e., new funding or credit). The responses in both jurisdictions suggest a change in priorities away from creditor protection, a key raison d'être for these types of duties, during a crisis. Similar to the German approach of turning the obligation to file for formal insolvency proceedings off and on, the further safe harbour adopted in Australia as part of a new restructuring procedure for small businesses, which commenced on January 1, 2021, suggests that the use of safe harbours could become a permanent crisis‐management tool in Australia too, with potential consequences for the balance between debtor and creditor interests.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.340
Teacher spread0.266 · 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 teacher head, not a consensus.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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