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Record W33987025 · doi:10.7717/peerj.11357

The implementation of Corporate Governance in Germany and Brazil: A Comparative Case Study

2014· dissertation· en· W33987025 on OpenAlexaboutno aff
Patrick Kohlmann

Bibliographic record

VenuePeerJ · 2014
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governancePolitical scienceComparative caseAccountingGeographyRegional scienceBusinessLinguisticsPhilosophyFinance

Abstract

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The recent promotion of best corporate governance standards by several different government institutions and non-for profit organizations resulted in the implementation of more sophisticated governance mechanisms. As consequence to the separation of ownership and control the concept of agency theory arose. Agency theory argues that without out proper control mechanism managers would behave exploit owners due to information asymmetry. Regulators have promoted corporate governance mechanisms in order to address this issue. This paper aims to contrast the implementation of best corporate governance practices in Germany and Brazil on the example of two practical examples. With this purpose in mind, this paper analyzed two companies listed in the main stock exchange in Germany and Brazil throughout a period of 5 years. In order to measure the degree of corporate governance practices implemented 3 different parameters have been chosen. In line with great part of the literature the parameters considered to be relevant are; composition, procedures and deviation from the local corporate governance code. The comparison of the data revealed that board composition in the two analyzed companies is similar regarding the proportion of independent representatives but does distinguish in size. While committees are related to the same topics it can be implied that Natura’s board is more involved in the actual management of the company. Lastly, Beiersdorf has been able to comply to a larger extend with the recommendations of the local German code than Natura to the recommendations published by Brazilian code of the IBGC.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.406

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.309
Teacher spread0.280 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

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