Corporate Governance and Business Ethics in North America: The State of the Art
Bibliographic record
Abstract
All three corporate governance systems in North America are currently embroiled in fundamental transformations. Most of Mexico’s corporations are run by a small group of controlling shareholders and operate in an economic system rife with corruption. Recent political reforms and a desire to tap global equity markets have heightened their interest in improving corporate governance structures. United States corporations face a dispersed ownership base that has tended toward inattentiveness, allowing such infamous scandals as Enron to rock the global investing community. A backlash against the ensuing, restrictive Sarbanes-Oxley legislation is now underway. Like Mexico’s, Canada’s major corporations are led by a handful of controlling shareholders, but corruption is uncommon. New corporate governance guidelines are under debate, and the Ontario Securities Commission is wresting control from the Toronto Stock Exchange. Although these three corporate governance systems vary in terms of ownership dispersion, level of corruption, and legislative intervention, they currently share a common focus on fundamental reform.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".