Governance and Efficiency of Zakah Distributions Based on the Dire Necessities of Maqasid Al-Syariah
Bibliographic record
Abstract
The study examines the governance and efficiency of zakah distributions based on the fulfilment of five dire necessities (daruriyyat) of Maqasid al-Syariah. There were about 500 questionnaires distributed to zakah beneficiarys of Asnaf Business Assistance program governed by one of Malaysian State Religious Council. 456 respondents responded, contributing to 89 per cent rate of response. Structural Equation Modelling with the use of Partial Least Square was used to analyse the data. Based on the findings, it can be concluded that the more likely the five elements of dire necessities namely faith, physical self, knowledge, family, and wealth being fulfilled, the more likely is the efficiency of zakah distributions. The study provides useful insights to zakah institutions to formulate strategies in relation to 5 elements of dire necessities to ensure competent distribution of the fund to recipients. The results would also provide comprehensive insights to other empirical studies in this area which will not only be applicable to Muslim countries but to non-muslim countries as well.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".