Unfinished Business: An Analysis of Stones Unturned in ADGA Systems International v. Valcom
Bibliographic record
Abstract
The recent Ontario Court of Appeal case, ADGA Systems International v. Valcom Ltd., is an important decision on corporate directors’ personal liability for torts. The court in this case interpreted the Said v. Butt exception to personal liability for a tort narrowly. Rather than concluding that a director is not liable whenever she commits a tort that is in the best interests of the corporation, the court concluded that the director is not liable for the tort of inducing her own corporation to breach a contract, and only for this tort, if she acts in the best interests of the corporation. In the author’s view, the court in ADGA accepted two premises without examining fully the implications of either. First, the court in accepting even the narrow Said v. Butt exception implicitly accepted the premise that costly overdeterrence of torts is an important consideration. However, there is no principled reason to conclude that overdeterrence is relevant only to the tort of inducing the director’s corporation to breach a contract. Yet the court adopts a narrow exception to personal liability for tort without considering overdeterrence more broadly. Secondly, while the court accepts that the principle of limited liability raises issues distinct from those relevant to personal liability of directors, the author shows that it does not fully consider the implications of this distinction in discussing the policy surrounding personal liability for directors.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.022 | 0.025 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".