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Record W2911268898 · doi:10.24042/adalah.v14i2.1967

Optimalisasi Pengelolaan Wakaf (Studi di Kabupaten Demak)

2018· article· en· W2911268898 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAL- ADALAH · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsWaqfProsperityEmpowermentGovernment (linguistics)PopulationPovertyIslamIndonesianShariaPolitical scienceLawInstitutionEconomic growthPublic administrationSociologyBusinessEconomicsGeography

Abstract

fetched live from OpenAlex

Waqf, as one of the Islamic social and economic institutions has enormous potentials in encouraging efforts to improve people’s economy. As a country with a huge population and the Muslim majority, Indonesia needs to explore and develops the potential of this religious institution. The combination of religious orders and social values can be utilized as a strong ideological backdrop for the government in managing waqfs so as to grow and be productive. This study tries to examine the status of land endowed in wakaf in Demak district before and after the enactment of Waqaf Law Number 41/ 2004 as well as to identify factors supporting and hindering efforts to optimize wakaf empowerment. This research used a socio-normative approach and it was conducted in several locations within Demak Regency. This study reveals that wakaf institutions in Demak Regency have not been able to improve the welfare of the community. This is because a lot of wakaf land in the area are not managed professionally and productively. Therefore, in the future, it is necessary to develop the professionalism of the Nazir (curator) so that Wakaf institutions can be developed optimally and innovatively to achieve the prosperity of muslim society.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.032
GPT teacher head0.339
Teacher spread0.308 · 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