Bibliographic record
Abstract
Before the advent of Islam, trade was the primary occupation of the people in Makkah. However, their commercial dealings often lacked ethical principles, leading to widespread exploitation. Deception, fraud, misrepresentation, and adulteration were common practices, resulting in economic injustices and fueling tribal and familial conflicts. In such circumstances, the Prophet Muhammad ﷺ introduced significant economic reforms, declaring all forms of trade unlawful that involved individual or collective harm. His approach aimed not only at preventing economic exploitation but also at fostering social stability by promoting generosity and compassion through charity and welfare initiatives. The Prophet ﷺ prioritized intellectual and moral training in economic matters. He emphasized ethical trade practices and their positive impact on society, advocating contentment over greed and reinforcing the belief that sustenance is a divine provision. These aspects will be explored in the study. Additionally, the research will highlight the benefits of interest-free financial transactions and their role in sustainable economic development. The study will also delve into the Prophet’s ﷺ directives regarding debt management, workers' rights, and financial policies that supported public welfare. By analyzing these measures, the paper will illustrate how adopting these principles in the modern era can lead to economic prosperity and stability, mirroring the successes witnessed during the Prophetic period and the era of the Rightly Guided Caliphs.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.961 | 0.976 |
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".