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The Convergence of Disclosure and Governance Practices in the World’s Largest Firms*

2007· article· en· W2029796898 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCorporate Governance An International Review · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsCorporate governanceConvergence (economics)AccountingAnglo saxonBusinessControl (management)Empirical evidenceMechanism (biology)Best practiceEmpirical researchPolitical scienceEconomicsFinanceLawManagementEconomic growth

Abstract

fetched live from OpenAlex

Many studies discuss convergence of cross‐border governance and governance‐related disclosure practices, but provide little empirical evidence to support their arguments and analysis. Our study examines the governance and disclosure practices of the world’s largest transnational firms. Using a unique dataset of 75 large firms in two time periods, 1995 and 2002, we examine both the governance practices, and disclosures regarding those governance practices, across Anglo‐Saxon and non‐Anglo‐Saxon firms. Results indicate that non‐Anglo‐Saxon firms have developed their governance practices towards promoting an independent mechanism of control, namely a mechanism that is more similar to an Anglo‐Saxon governance regime. In regard to governance‐related disclosure practices, results indicate that for both Anglo‐Saxon and non‐Anglo‐Saxon groups, disclosure practices have been evolving and converging towards more disclosures regarding governance matters.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.303
Teacher spread0.252 · 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