Convergence Versus Divergence, Global Corporate Governance at the Crossroads: Governances Norms, Capital Markets & OECD Principles for Corporate Governance
Bibliographic record
Abstract
There is growing debate as to whether international corporate governance practices can or should converge. Effective corporate governance has been linked to the ability of corporations to compete in global capital markets. Corporations operating in diverse economies have capital structures that are the result of public and private choices, and the corporate governance issues that arise reflect these structures. There is market pressure for convergence of corporate governance norms. The OECD has formulated Principles aimed at setting standards for corporations as they seek to attract capital. While the shareholder protections proposed are helpful in articulating norms that will attract long-term investment capital, the Principles fail to fully appreciate some of the current tensions between shareholder rights and obligations of corporate officers. Moreover, while the Principles suggest that corporations comply with laws regarding obligations to stakeholders, they fail to adequately discuss why shareholder rights are elevated to a universal norm, whereas accountability to other parties implicated in the corporation, such as creditors and workers, is not.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".