MétaCan
Menu
Back to cohort
Record W2186115016 · doi:10.5897/ajbm.9000137

Comparative legal perspectives on international models of corporate governance

2010· article· en· W2186115016 on OpenAlexaboutno aff
Niculae Feleag, Liliana Feleag, Voicu D. Dragomir

Bibliographic record

VenueAFRICAN JOURNAL OF BUSINESS MANAGEMENT · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceContext (archaeology)Divergence (linguistics)Convergence (economics)AccountingDiversity (politics)Emerging marketsInterpretation (philosophy)BusinessAgency (philosophy)European unionPolitical scienceCorporate lawEconomicsInternational tradeLawSociologyFinanceMacroeconomicsSocial science

Abstract

fetched live from OpenAlex

The present paper aims to provide an interpretation of leading corporate governance paradigms, through several case studies involving four developed economies (that is, the US, the UK, Canada and France) that have implemented either principle-based or rule-based corporate governance systems. A supplementary case study involving Romania, an emerging country, seeks to provide valuable insight into the inconsistencies of applying such a refined corporate governance system to an emerging market. From a methodological standpoint, preeminence is given to a comparative and critical approach. Finally, we ask the following question: which are the most appropriate ways to insure the crystallization of legal aspects concerning corporate governance, in the context of international diversity and, sometimes, divergence?   Key words: Corporate governance, comparative approach, international evidence, United Kingdom, European Union convergence, financial markets, agency theory.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0020.016
Scholarly communication0.0090.010
Open science0.0010.003
Research integrity0.0020.003
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 head0.029
GPT teacher head0.225
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueAFRICAN JOURNAL OF BUSINESS MANAGEMENTSame topicCorporate Finance and GovernanceFrench-language works237,207