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Record W4290600800 · doi:10.3390/jrfm15080347

Reforms of Corporate Governance Codes in Bangladesh: Developments and Future Directions

2022· article· en· W4290600800 on OpenAlexvenueno aff
Md Tariqul Islam, Mahfuzur Rahman, Shrabani Saha

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsRemunerationCorporate governanceNominationIndependence (probability theory)AccountingBusinessCode (set theory)Diversity (politics)Code of conductEmerging marketsPolitical scienceFinanceLawComputer science

Abstract

fetched live from OpenAlex

This research investigates corporate governance (CG) norms in Bangladesh, a developing nation. This study assesses the codes’ key aspects and how they have evolved since the first code was released in 2006. This analysis shows that BSEC changed its recommendations from voluntary to mandatory in the subsequent revisions in 2012 and 2018. The modified versions increased board independence compared to the original code, although it is still lower than in some other emerging nations. Recent changes to the rules include conditions on the nomination and remuneration committees, along with some other amendments. However, critical governance components, such as choosing an independent board member as chair, improving board independence, and assuring gender diversity, could be implemented in future code development. It is believed that investors would be more interested in Bangladesh’s capital market if the policymakers could make the proposed modifications in accordance with the distinctive institutional features of an emerging economy.

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)0.004
metaresearch head score (Gemma)0.010
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: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.186
Teacher spread0.177 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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