A Proposed Model for Efficient Shariah Governance of Islamic Financial Institutions
Bibliographic record
Abstract
The Islamic banking and finance sector has predominantly relied on self-regulation for Shariah governance. Despite existing regulatory bodies like the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) and the Islamic Financial Services Board (IFSB), Islamic financial institutions largely remain self-regulated, as resolutions from these bodies are generally non-binding unless voluntarily adopted. Some countries have implemented Shariah-governance-related regulations, but these regulations often do not extend beyond the requirement to establish Shariah-compliance oversight bodies, which are typically controlled by the same operating banks. Conflicts between these regulatory authorities and Fiqh academies further complicate matters. This study addresses these challenges by identifying the deficiencies in the current system and then proposing necessary reforms to establish an effective Shariah governance framework. Such reforms are crucial for safeguarding the industry's integrity from within and facilitating its pursuit of its objectives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".