Ribā and Paying Off Non-stipulated Interest: The Capability to Become a Prevalent Custom (ʿUrf) in Islamic Society
Bibliographic record
Abstract
Abstract This article seeks to study ribā from a novel point of view. Paying off interest without preconditions is recommended strongly by the Prophet ( PBUH ). If Islamic society follows his advice, this will become a prevalent custom ( ʿurf ) among Muslims, which the title of the stipulated interest does not include. This article refers to the views of Islamic schools on ʿurf and how they comply with the custom in question formed hypothetically. This article finds that, according to Islamic schools, such custom is considered valid, legitimate, and necessary to follow. The last part of the article provides an important discussion on how to put this theory into practice and implement the model designed for this purpose in the Islamic financial system. This article concludes that the challenge of prohibiting ribā will be solved if non-stipulated interest can be made obligatory in Islamic society based on the juristic views on ʿurf .
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".