From subordination to parity: an international comparison of equity securities law claims in insolvency proceedings
Bibliographic record
Abstract
Abstract Securities law claims in insolvency proceedings raise important questions of allocation of risk and remedies. In the ordinary course of business, equity claims come last in the hierarchy of claims during insolvency. What is less clear is whether this should encompass claims arising from the violation of public statutes designed to protect equity investors. Discerning the optimal allocation of risk is a complex challenge if one is trying to maximize the simultaneous advancement of securities law and insolvency law public policy goals. From a securities law perspective, there must be confidence in meaningful remedies for capital markets violations if investors are to continue to invest. From an insolvency perspective, creditors make their pricing and credit availability choices based on certainty regarding their claims and shifting those priorities may affect the availability of credit. The critical question is the nature of the claim advanced by the securities holder and whether subordination of securities law claims gives rise to inappropriate incentives for corporate officers within the insolvency law regime. A comparative analysis reveals that the U.S. has provided a limited statutory exception to complete subordination through the fair funds provision of the Sarbanes‐Oxley Act by allowing SEC claims for penalties and disgorgement to rank equally with unsecured claims even though the funds are distributed to shareholders. The U.K. and Australian schemes permit shareholders to claim directly as unsecured creditors for fraudulent acts and misrepresentation by the issuer. In contrast, Canadian law is underdeveloped in its treatment of such claims. The paper canvasses the policy options available to reconcile securities law and insolvency law claims, including a discussion of the appropriate gatekeeping role for regulatory authorities and the courts, and the need for a framework that offers fair and expeditious resolution of such claims. If the public policy goal of both securities law and insolvency law is to foster efficient and cost‐effective capital markets, it seems that the systems need to be better reconciled than currently. The paper also examines the codified response to the time and resources consumed in various common law tracing claims by customers in a securities firm insolvency. Copyright © 2007 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 | 0.013 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".