The Limits of Derivative Actions: The Application of Limitation Periods to Derivative Actions
Bibliographic record
Abstract
Limitation periods are an integral and significant aspect of the litigation process in Canada. Although the application of limitation periods may often seem harsh, they are generally considered to be beneficial by bringing stability to society and by providing an incentive to plaintiffs not to “sleep on their rights.” However, in corporate derivative actions (actions brought by a shareholder against directors or officers of the corporation on the corporation’s behalf), the application of a limitation period presents certain issues that could result in such goals not being advanced. Specifically, two main issues arise, namely; who is the claimant for the purposes of limitation periods, and how do limitation periods apply to leave applications? The authors propose that the Canadian judiciary should adopt the adverse domination doctrine, applying the majority test, and explicitly hold that the filing of the leave application is sufficient to bring the derivative action within the limitation period. This approach would be consistent with the separate corporate existence principle and the purposes underlying limitation periods, as well as providing certainty and predictability to the adjudication of derivative action claims.
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".