Correlation between break fee and asset purchase option regulation in Canada and its empirical effects
Bibliographic record
Abstract
This thesis focuses on break fee and asset purchase option regulation in Canada and the empirical effects of that regulatory regime. The structure of this thesis is divided into three broad sections. The first section of the thesis (Chapter 2) assesses the Canadian general corporate and securities law related to directors’ duties imposed on target directors when implementing any defensive tactic. These general directors’ duties affect the implementation of all defensive tactics and thus form a significant part of the regulatory scheme governing break fees and asset purchase options. The second section of this thesis (Chapter 3) considers the specific directors’ duties applicable exclusively to break fees and asset purchase options. This second section then analyses the doctrine underlying the complete Canadian regulatory framework, governing break fees and asset purchase options. The third and final section of the thesis (Chapter 4) analyses the empirical economic effects created by the Canadian regulatory regime of directors’ duties governing the use of break fees and asset purchase options. This analysis draws its empirical evidence on the effects of Canadian break fees, from a crucial study by P. Andr´e, S. Khalil and M. Magnan, (2007) “Termination Fees in Mergers and Acquisitions”. Past research has focussed exclusively on describing the regulatory regime, or on providing substantive data on the effect of break fees and asset purchase options. The key novel element provided in this thesis is that it establishes a logical correlation between the regulatory framework of directors’ duties imposed on the use of break fees and asset purchase options and the empirical effects of the regulatory framework. In this regard, I argue that the empirical effects of break fees and asset purchase options are strongly tied to the regime regulating its implementation. Secondly, I argue that much of the “positive” empirical findings on the effects of break fees and asset purchase options correlate with the “broad director welfare function” approach to regulatory design (developed in Chapter 3). Finally, this thesis proposes limited changes to this regulatory regime governing break fees and asset purchase options while maintaining the “broad director welfare function” as the underlying doctrine.
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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 | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".