Common Law Securities Misrepresentation Claims — Still with us in the Post- <i>Green</i> Era?
Bibliographic record
Abstract
Part XXIII.1 of the Ontario Securities Act provides a statutory right of action for misrepresentations or omissions affecting the price of securities on the secondary market. Recently, the Supreme Court of Canada released its decision in CIBC v Green, wherein it considered whether common law securities misrepresentation claims may be certified alongside misrepresentation claims commenced pursuant to Part XXIII.1. While the Supreme Court decision in Green indicates that certain common issues relating to common law misrepresentation claims may be certified in conjunction with a Part XXIII.1 claim, it does not suggest that this will be appropriate in all cases. The Green decision raises the question as to what meaningful benefit class members will obtain from this practice. The certification of some but not all common issues relating to common law misrepresentation claims is unlikely to meaningfully advance the resolution of such claims when issues relating to reliance and damages must be dealt with by way of individual trials. In light of these and other complex issues that were not addressed in Green, one may expect further commentary on the issue of parallel common law claims by appellate courts.
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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 | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".