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Record W4380520888 · doi:10.6000/1929-4409.2020.09.34

The Assistance Model of the Baitul Mal in Promoting The Community of Home Industry

2022· article· en· W4380520888 on OpenAlexvenueno aff
Sabirin, Masriza, Muslim Zainuddin, Teuku Zulyadi, Nurul Husna, Syazwani Drani

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessManagementOperations managementEngineeringEconomics

Abstract

fetched live from OpenAlex

Baitul Mal as an institution for collecting and distributing zakat, infaq, and shadakah among Muslims, has not yet developed community economic programs, especially home industries. Although the community economic development program has been implemented, the assistance model provided so far has not been able to provide increased income for the community. This article responds to the view that Baitul Mal in carrying out its programs is only consumptive in nature and has not been able to develop productive programs related to the community's economy by providing venture capital for home industry players. This qualitative research in finding a model of Baitul Mal assistance was done through observation, interviews, and documentation. The data obtained is used to strengthen the research objectives in supporting the assistance model for the assistance of Baitul Mal Aceh. This study found that the Baitul Mal Aceh program was more dominant in the field of consumptive zakat, while the assistance model of Baitul Mal assistance in the form of productive zakat had not been able to provide maximum results for the economic development of the community, especially in the home industry sector. So in the future, there needs to be an improvement, as an initial solution in introducing the Baitul Mal Aceh assistance model to the community.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.094
GPT teacher head0.348
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes1
Has abstractyes

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