Conceptualization of The Alternative Zakat and Ushr Based Poverty Allviation and Sustainable Development Model: An Empirical Case Study in Bangladesh
Bibliographic record
Abstract
The purpose of this research is to investigate the role of ‘Zakat and Ushr’ as a key tool to achieve sustainable development in Bangladesh. The study also proposes an alternative model for Zakat distribution analyzing drawbacks and challenges of prevailed Zakat distribution system. The present study used qualitative approach with intensive interview on about zakat practices in Bangladesh. The study finding from the literature surveys about Zakat distribution affirm that an alternative model for Zakat distribution system can ensure sustainable development through decreasing the rate of poverty based on the Umar bin Al Khattab (RA) and Ummar bin Abdul Aziz poverty model. The study shows that Zakat providers in Bangladesh distribute Zakat in an unplanned and unstructured way which is not the purpose of Zakat according to the direction of Quran and Sunnah. In the prevailed system, Zakat providers distribute Zakat mainly in the month of Ramadan and individual Zakat providers divide whole portion of individual Zakat amount among mass people which are being helpful for poor people to run their family for a very short period of time. Therefore, based on above findings the present study proposes an alternative model for distributing Zakat in Bangladesh considering the direction of Al-Quran and Hadith. This proposed model suggests engaging local leaders, Imam of mosques, Zakat providers and Zakat receivers that can ensure building community-based Zakat funds to develop individual poor people for a long period of time.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".