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Record W3167209000 · doi:10.5267/j.ac.2021.5.005

The effectiveness of the internal corporate governance mechanism and the ownership of the government and agencies

2021· article· en· W3167209000 on OpenAlexvenueno aff
Khaled Salmen Aljaaidi

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceBusinessAccountingGovernment (linguistics)Context (archaeology)Finance

Abstract

fetched live from OpenAlex

This paper examines the impact of the government and its agencies’ ownership on the effectiveness of one the main internal governance mechanisms, namely; board of directors, for a sample of 140 energy and petrochemical Saudi listed firms over 2012-2019. The Saudi Arabia provides an interesting context due to the domination of government-linked corporations’ ownership. This setting arranges for the impact of such ownership on the board of directors’ monitoring and advisory roles. The board of directors’ effectiveness is measured as an interaction term of the board size and meetings of the board of directors. The study finds that government-linked energy and petrochemical corporations’ ownerships are inversely related to the board of directors’ effectiveness. This result is sensitive to the measurement of the board of directors’ effectiveness as each variable consisting of the board of directors’ effectiveness was examined individually. The study also finds that government-linked corporations’ ownership had a strong negative impact on the board size. In contrast, the proposed model does not provide any evidence supporting the relationship of the government-linked corporations’ ownerships with board meetings. Overall, the evidence supports the substitution hypothesis on the relationship of government-linked corporations and board of directors’ effectiveness.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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