Weather, Leather, and the Obligation to Disclose: Kerr v. Danier Leather Inc.
Bibliographic record
Abstract
Is an issuer legally obliged to update its prospectus if a material event occurs following the receipt for the prospectus but prior to the closing of the offering? This is the crucial issue that is addressed in Kerr v. Danier Leather Inc., a case that has been heard at the trial and appeal levels in Ontario and that will be heard in 2007 by the Supreme Court of Canada. In this commentary, we argue that the Court of Appeal decision in the case overlooked crucial aspects of contemporary securities law and policy in holding that there is no obligation to disclose intra-quarterly results that cast doubt on the achievement of an earnings forecast in a prospectus. Further, although the Court of Appeal took into account the business judgment rule, there is no precedent for applying it in the context of an obligation to fulfill statutory disclosure requirements. Ultimately, this is a case in which courts squarely confront the balance between legal obligations imposed on issuers and the expectations of investors in the context of forward-looking information. This issue was not a feature of the disclosure landscape when the Ontario statute was originally enacted and, until this case, had not been litigated in this country. In Part II of this commentary, we explore the difference between material fact and material change and the meaning of section 57(1) of the Securities Act We also examine the policy rationales underpinning section 57(1) and section 130(1); we argue that if one reads these two sections together, changes in material facts as well as material changes must be disclosed if they arise following the issuance of a receipt for the prospectus but prior to the end of the distribution period. The notion of investor protection embedded in the Securities Act is severely undermined if investors are not provided -with information that they would consider to be material" regardless of whether the information is technically speaking a material "fact" or a material "change." In Part III, we turn to examine the business judgment rule: its history and development in Canada. We argue that the business judgment rule is inapplicable in a case such as Danier, which deals with the obligations under securities law to disclose material facts and material changes. We conclude the commentary in Part IV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".