Coordination and Monitoring in Changes of Control: The Controversial Role of “Wolf Packs” in Capital Markets
Bibliographic record
Abstract
Given recent empirical work suggesting that Canada is one of two countries in which outcomes favourable to shareholder activists are more likely than in the United States, one might wonder whether shareholders in Canadian public companies have become too empowered. This concern takes on particular significance in light of controversies arising from the emergence of “wolf packs”: loose networks of parallel-minded shareholders (typically hedge funds) that act together to effect change in a given corporation without disclosing their collective interest. This article analogizes the role of wolf packs in the corporation to that of a blockholder. It isolates certain conditions that facilitate the formation of wolf packs such that wolf packs are able to overcome the coordination costs that can ordinarily impede shareholders from forming de facto blocs to monitor a corporation’s directors and management. At the same time, however, they are able to circumvent the disclosure rules that typically apply to such groups. Because wolf packs are able to wield significant influence in corporate affairs without disclosing their collective interest to other investors, this article argues that the disclosure rules relating to wolf packs in Canada should, as a first step, be clarified.
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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 | 0.001 |
| 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".