The General Counsel, Gatekeeping, and the Investor Public: Uneasy Bedfellows?
Bibliographic record
Abstract
This thesis examines the role of the general counsel across Canadian and American comparisons, specifically with reference to Enron, Livent, and Hollinger cases of fraud.The General Counsel has been within a debate concerning their heightened role for disclosure in the American Sarbanes-Oxley Act.The General Counsel is in a unique position as both a business executive, and a law professional that can mediate their ethical obligations as a professional, as well as their fiduciary obligations as a corporate executive.Two models of responsibility will be examined: that of transaction engineer, and that of gatekeeper.Transaction engineer is primarily situated as a means of maximizing value for the corporation through the general counsel's legal expertise, and this can include "loophole lawyering".In such a context, Counsel may be failing to provide adequate representation for corporate fiduciary responsibilities, as well as their ethical responsibility to not undermine the law in the pursuit of aggressive competitive advantage and short-term profit.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".