JUST WHAT THE DOCTOR ORDERED? A LOOK AT THE SIDE EFFECTS OF THERATECHNOLOGIES ON SECONDARY MARKET LIABILITY IN CANADA
Bibliographic record
Abstract
The recent decision of the Supreme Court of Canada in Theratechnologies Inc. v 121851 Canada Inc. (“Thera”) goes to the heart of the debate on the place of the public and private enforcement methods in the Canadian securities regulation regime. Fundamentally, the case concerns the application of the statutory civil liability regime for the secondary securities market enacted in the mid-2000s by provincial legislators across the country. The regime provides a remedy to investors who have suffered a loss because of the failure of an issuer to comply with the applicable disclosure requirements. In Thera, the Supreme Court was called upon to determine the threshold of the statutory leave test, which applies to the remedy in addition to any other requirements governing class actions. The objective of this paper is to offer a critical review of the interpretation of the leave test threshold proposed by the Supreme Court in Thera. The paper argues that the decision imposes a stringent threshold for the leave test because, on the one hand, the Court overestimated the risk of strike suits and, on the other hand, did not appreciate the role of the mitigating mechanisms built-in the statutory regime to address this risk. Following Thera, the effectiveness of the regime appears greatly hampered by the combined effect of the mitigating mechanisms and the leave threshold. Hence, this raises the question as to whether the overall effect will render the remedy ineffective for investors, and bring us back to the situation that prevailed under common law and civil law where recourses were largely illusory. This preoccupation is not merely speculative; it is reflected quite clearly in the post-Thera case law, as our analysis of said case law demonstrates. If the perceived trend were to persist, this would mean that Thera will have marginalized private enforcement in the secondary market, thereby requiring more vigorous public enforcement in order to ensure the quality of disclosure on the secondary market.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".