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Record W2952306635 · doi:10.5430/ijfr.v10n5p191

Governance and Efficiency of Zakah Distributions Based on the Dire Necessities of Maqasid Al-Syariah

2019· article· en· W2952306635 on OpenAlexvenueno aff
Maheran Zakaria, Muhammad Saiful Anuar Yusoff, Zuraidah Mohd Sanusi

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceFaithDistribution (mathematics)Relation (database)BusinessPublic economicsEconomicsMathematicsFinanceTheologyComputer science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.305
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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