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Record W2253970805

An Analysis of Enabling vs. Mandatory Corporate Governance Structures Post Sarbanes-Oxley

2005· article· en· W2253970805 on OpenAlexafffund
Anita Anand

Bibliographic record

VenueTSpace (University of Toronto) · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaQueen's UniversityFondation pour la recherche juridique
KeywordsCorporate governanceAccountingIncentiveIssuerBusinessYield (engineering)Compliance (psychology)ScholarshipSarbanes–Oxley ActEconomicsFinancePolitical scienceMarket economyLaw
DOInot available

Abstract

fetched live from OpenAlex

I argue that firms have incentives to adopt corporate governance practices in the absence of a legal requirement to do so. I further contend that a partially enabling governance regime, and particularly one coupled with mandatory disclosure of a firm's governance practices, is likely to yield a high level of compliance at lower direct costs to the issuer than a wholly mandatory regime. While a wholly mandatory structure may yield slightly better compliance, its other benefits are uncertain and its costs are likely much higher. I seek to push the boundaries of existing comparative corporate governance scholarship by arguing that the enabling/mandatory dichotomy informs analyses of corporate governance regimes across countries.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.013
GPT teacher head0.205
Teacher spread0.192 · 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 designObservational
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

Citations20
Published2005
Admission routes2
Has abstractyes

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