Corporate Governance and Statutory Derivative Actions: Comparative Approach to Shareholder Litigation
Bibliographic record
Abstract
This book is the first comprehensive study of the statutory derivative action in Australia, using the Australian model as a reference point and comparing it with the United Kingdom, Canada, Singapore, New Zealand, Hong Kong and USA counterparts. The book includes an empirical study covering over a 20-year period from the date the statutory framework came into operation, coupled with extensive case law analysis and comparisons with other jurisdictions. It informs the world about the uniqueness of Australia’s statutory derivative action, and what other countries can learn from it as shareholder protection and promotion of good corporate governance. While some countries have statutory derivative action, there are still countries that do not have the statutory framework that are considering introducing it into their corporate law. This book is also useful for countries that already have their local variants of the statutory derivative action that are considering revising their existing provisions. This book provides insights and suggestions for lawmakers, judges, litigation practitioners and corporate law and litigation researchers worldwide in reforming their existing model.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".