Bibliographic record
Abstract
This book addresses the legal framework in which corporate governance operates, and offers strategies for directors, officers, and other stakeholders as corporations seek to compete in global capital markets.This foreword sets the context for this discussion by giving an overview of various pragmatic aspects of corporate governance, based on my varied experience as chief executive officer (CEO), board chair, and director.In Canada, the Dey guidelines issued by the Toronto Stock Exchange (now TSX) and reports such as Beyond Compliance: Building a Governance Culture are helpful in defining good governance practices.1 While there continues to be debate about the extent to which corporate governance practices should be made mandatory, from a practical point of view, the guidelines do not necessarily fit all listed companies.Stock exchanges will experience pressure from companies in terms of their willingness to list if there are too many requirements, and the ease with which companies can move trading about makes these real concerns.In my view, two aspects should be mandatory.If companies are not conforming to a guideline, they should be required to specifically explain why they are not.Second, if a corporation does not have a nonexecutive chair of the board, it should be required to have an independent board leader or lead director.This would address potential conflicts of interest or the appearance of conflict that is created by having someone in the combined role of chair of the board and chief executive officer.The job content of the non-executive chair is extremely important; there should not be "two CEOs."Independent leadership and oversight are essential.The corporate board is key to good governance.A corporate board should consist of a diversity of interests, including women, leaders of nonprofit organizations, some individuals lower down in the ranks of another organization who are on their way up, and people with different perspectives of the world and from different geographic regions.I am involved with a company engaging in considerable business activity in Japan, China, and Korea, and having a director from one or more of these nations would be helpful.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.611 | 0.524 |
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".