Convergence of corporate governance practices in the post‐Enron period: behavioral transformation or box‐checking exercise?
Bibliographic record
Abstract
Purpose The objective of the study is to analyze corporate governance practices of Canadian companies in the post‐Enron period. The attempt is to investigate whether the convergence phenomenon evidenced in prior studies is limited to the minimum mandatory requirements imposed by regulators or reflects a real behavioral transformation. Design/methodology/approach Changing governance structure might be slow except in times of financial crisis, increased public scrutiny and reforms. These conditions are met in the post‐Enron period (2002 to 2005) where major reforms have been launched including the Sarbanes‐Oxley Act (SOX) in the USA and Bill 198 in Canada. The authors expect changes in corporate governance to be more important during this period, therefore, enhancing the robustness and reliability of their results. They measure corporate governance on a global scale, relying on the ROB index published by the Globe and Mail. The index distinguishes between four blocks of corporate governance, namely, board composition, compensation, shareholder rights, and disclosure. Findings The present results show signs of convergence. However, Canadian companies improved their corporate governance practices in the post‐Enron period mainly in areas mandated by regulation. This includes provisions related to the composition, attributes and working of the board of directors and board committees. No significant improvement is found in non‐regulated governance best practices. Research limitations/implications Overall, the findings suggest a lack of real behavioral change in corporate leaders. Instead, convergence in corporate governance appears to be the result of a box‐checking exercise. Practical implications If corporate governance is about ethical conduct and stems from the culture and mindset of management, these results show that corporate governance cannot be regulated by legislation alone. Originality/value This study goes beyond the minimum mandatory requirements and looks into compliance of non‐regulated provisions as well. Examining the evolution of corporate governance practices on these two fronts helps to further investigate the extent and nature of convergence.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".