MétaCan
Menu
Back to cohort
Record W2996724622 · doi:10.3390/jrfm13010002

Managing Shariah Non-Compliance Risk via Islamic Dispute Resolution

2019· article· en· W2996724622 on OpenAlexvenueno aff
Maria Bhatti

Bibliographic record

VenueJournal of risk and financial management · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArbitrationIslamCompliance (psychology)Islamic financeBusinessCorporate governanceDispute resolutionAccountingRisk managementFlexibility (engineering)ShariaIslamic bankingResolution (logic)FinanceLawEconomicsPolitical scienceManagementComputer science

Abstract

fetched live from OpenAlex

This article discusses Shariah non-compliance risk as a form of operational risk intending to ensure that operations in the Islamic and banking finance industry comply with Shariah procedures. In the field of Islamic finance, Shariah non-compliance risk refers to the possibility that Islamic finance transactions may be challenged based on Shariah non-compliance. This article uses a comparative and normative approach as well as a legal analysis of the case of Beximco. The article proposes the management of Shariah non-compliance risk by augmenting the effectiveness of Shariah governance systems with Islamic banking and finance arbitration; arbitration should be an enforced part of Islamic finance institutional arrangements—as it always has been classically—to provide flexibility for dispute resolution. To this end, the article examines contemporary implementations of Shariah arbitration rules to assess how Shariah non-compliance risk can be better managed via Islamic dispute resolution procedures.

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)0.027
metaresearch head score (Gemma)0.041
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: none
Teacher disagreement score0.027
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.007
Scholarly communication0.0080.007
Open science0.0030.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of risk and financial managementSame topicIslamic Finance and Banking StudiesFrench-language works237,207