Bibliographic record
Abstract
Defining Ribā has proved to be a difficult task for scholars in the contemporary world. The present paper argues that the problem lies the flawed methodology of these scholars. Hence, the paper focuses on the methodology of the Muslim jurists who held that Ribā was a technical term (Mujmal) the meaning of which was elaborated by the Prophetic traditions about ribā. Hence, believing in the inseparability of the Qur’an and the Sunnah, the jurists connected the Qur’anic verses and the Prophetic traditions about Ribā and defined Ribā as: excess without a counter-value stipulated in a contract of exchange of property. The paper argues that this definition of Ribā answers all significant questions about the term, such as: whether bank-interest is included in the scope of Ribā; whether the prohibition of Ribā covers interest on credit raised for commercial purposes; whether paying interest is a lesser sin than receiving interest; whether indexation of loans is permitted in Islam; whether charging a higher price in credit-sale is permitted; whether Islamic law recognizes the concept of time-value of money; and so on. After answering these questions, the paper also examines some of the important arguments forwarded by various economists for justifying interest and concludes that these arguments do not carry any weight.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.975 | 0.980 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".