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Record W2912948958 · doi:10.5539/ass.v15n2p164

Land Ownership Reform in Islam

2019· article· en· W2912948958 on OpenAlexvenueno aff
Ridwan Ridwan

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamAgrarian societyLand tenurePublic ownershipState (computer science)Agrarian reformCertaintyLawEconomic JusticeShariaDistribution (mathematics)Land reformLegal certaintyHumanismLaw and economicsSociologyPolitical scienceEconomicsMarket economyGeographyEpistemologyPhilosophyAgricultureTheology

Abstract

fetched live from OpenAlex

This article shows that Islam has laid the foundations of agrarian law reform or land reform, from the oppressive and exploitative pre-Islamic system of land ownership towards the fair, equitable and humanist-religious-based distribution of land ownership. The purpose of agrarian reform cannot be separated from the objectives of the law in general, that is to create justice, expediency and law certainty which describe the legal values either juridical, sociological or philosophical. To explain the idea of agrarian reform in Islamic law, there are some discussions proving the existence of the notion of land ownership reform in terms of the process of land right ownership and patterns of land distribution by the State based on the historical data, especially early history of Islam. Shifting paradigm from the feudalist pre-Islamic ownership system to the communalist-religious Islamic ownership system under the single authority of the head of state on the basis of the principle of fairness rests on the spirit to realize the ideals of public benefit.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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 designTheoretical or conceptual
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

Citations1
Published2019
Admission routes1
Has abstractyes

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