Rescue!: The Companies' Creditors Arrangement Act, 2nd ed.
Bibliographic record
Abstract
The going-forward solution to a firm's financial distress depends on the reasons for insolvency, the firm's capital structure, viability of its business plan, effectiveness of its directors and officers, and the availability of capital to refinance or purchase the business. Rescue! The Companies Creditors Arrangement Act, Second Edition is an indispensable guide to navigating the complexities of Canadian insolvency restructuring law. This book offers a comprehensive analysis of current and expected developments in this important area of law and practice and helps the reader gain an edge with insight into the latest decisions and developments shaping the Companies Creditors Arrangement Act (CCAA). With this book, you can Rely on the expertise of a leading insolvency authorityJanis Sarra is an insolvency authority, a leading law professor, and Editor-in-Chief of the Annual Review of Insolvency Law. In this convenient resource, she identifies and meticulously analyzes the most recent and most significant decisions to shape the CCAA to give an expert understanding of the issues that will affect your next proceeding. Reduce research timeThe author zeroes in on all cases relevant to the CCAA and sheds fresh light on their impact. You'll anticipate new issues that could arise at every stage of the proceeding, and learn how to navigate them effectively. Avoid commonly overlooked issuesWhen the case law so dominates the legislation, it can be challenging to ensure you've done absolutely everything to your client's advantage. This resource takes you through every step of proceedings under the CCAA, highlights the cases that impact each step, offers practical advice, and gives you valuable practice tools, such as model orders and a sample plan of arrangement. [From Rescue! The Companies Creditors Arrangement Act, Second Edition | Thomson Reuters]
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.023 |
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".