Funding corporate rescue: the Impact of the financial crisis
Bibliographic record
Abstract
Abstract Insolvency reform across many jurisdictions over the last twenty years has focused on the development of legislation to facilitate business reorganizations. However, any regime which involves rescue requires a degree of support from the commercial environment. The rescue regimes may therefore be severely tested in situations where there is a general economic downturn such as the world has experienced in the last two years. This article evaluates empirically the perceived impact of the Global Financial Crisis on the opportunities for rescue on the basis of a survey we set out among insolvency professionals worldwide. Most of the 562 respondents to the survey from 56 jurisdictions agree that the credit crisis of 2007 stifled the access of distressed business to financial facilities so needed for successful restructuring. It retrenched the access to financial facilities and thus impacted negatively the prospects for preventing or even ending the bankruptcy procedure with reorganization instead of winding up of the estate assets. Several reasons that have been pointed out by the insolvency professionals in our survey are discussed in this article. We conclude that somewhat paradoxically just when rescue is needed the most, the practical reality may be that businesses will not be saved if there is insufficient support available either by way of additional credit or because other (funding) creditors are so financially stressed themselves that they are unable or unwilling to support any potential rescue. Copyright © 2010 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 | 0.005 | 0.018 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".