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Record W2262679560

Convergence Versus Divergence, Global Corporate Governance at the Crossroads: Governances Norms, Capital Markets & OECD Principles for Corporate Governance

2001· article· en· W2262679560 on OpenAlexaff
Janis Sarra

Bibliographic record

VenueSSRN Electronic Journal · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCorporate governanceShareholderCorporationConvergence (economics)AccountabilityCapital marketBusinessAccountingShareholder primacyStakeholderDivergence (linguistics)CreditorShareholder resolutionCorporate lawEconomicsFinanceLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.025
GPT teacher head0.228
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2001
Admission routes1
Has abstractyes

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