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Record W4399110626 · doi:10.5937/imcsm24067j

New corporate governance tendencies of supervisory boards in Europe

2024· article· en· W4399110626 on OpenAlexaboutno aff
Milan Jeličić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceAccountingSupervisory boardBusinessIndependence (probability theory)Dual (grammatical number)Diversity (politics)Corporate lawWork (physics)Control (management)Gender diversityPublic relationsManagementPolitical scienceEconomicsEngineeringLawFinance

Abstract

fetched live from OpenAlex

Corporate governance refers to the way in which a company is being organized, and contains laws, regulations, principles and codes which the organization is based on and guided by. Two primary systems of corporate management can be differentiated: the monistic model (one-tiered) which originates from and is used in the United Kingdom, USA and Canada, and the dual model (two-tiered) that is mostly implemented in the countries of Western Europe, and more recently in European countries in transition. This study will be dealing with the two-tier system of corporate governance, as well as the differences and similarities in its application in Europe through the course of challenging and unstable business conditions. The supervisory board as a management body is a control body that supervises, directs and controls the work of the executive board. Certain factors such as the size of the board, independence, composition and diversity of the supervisory board are considered crucial for successfully fulfilling its role. The contemporary approach to business encourages the constant need to review and redefine the role of supervisory boards and search for solutions that would contribute to efficient corporate governance.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.207
Teacher spread0.164 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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