Shari’a Governance in Bahrain: Analysing the Islamic Banking Industry’s Implementation of the Newly Issued Regulatory Shari’a Governance Module
Bibliographic record
Abstract
Shari’a governance is considered a crucial element of the Islamic banking industry. As recent as 2017, Islamic banks in the Kingdom of Bahrain were required by the regulator to have only a Shari’a Supervisory Board and an internal Shari’a function. In 2017, the Central Bank of Bahrain issued a new Shari’a Governance module (SG) in its rulebook, requiring all Islamic banks to have at least two internal Shari’a departments instead of one, mandated external Shari’a auditing, and maintaining the necessity of having a Shari’a Supervisory Board. In this study, through an empirical enquiry, we analyse how the Islamic banking industry implemented this new module. The empirical results revealed that there seems to be an implementation gap between Islamic retail and wholesale banks, where the former have fully implemented the new Shari’a governance requirements, while the latter were given exemptions to postpone its implementation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".