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Record W3184974555 · doi:10.6000/1929-4409.2021.10.144

Permanent Grant of Land Certificate for Adat People, is it Possible?

2021· article· en· W3184974555 on OpenAlexvenueno aff
Yusuf Saepul Zamil, Supraba Sekarwati, Yani Pujiwati, Ida Nurlinda

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsCertificateLand tenureLand lawGovernment (linguistics)HomelandLand registrationPopulationLawAgrarian societyIndonesianBusinessEconomic growthPolitical scienceGeographySociologyPoliticsEconomicsAgriculture

Abstract

fetched live from OpenAlex

Adat peoples mean the original inhabitants or the first inhabitants of a country or the earliest population's descendants lived in the area. All this time, adat people in Indonesia have always been marginalized and banished from their homeland. Companies that acquired investment permits from the government often dismiss the adat peoples for their interests. This dismissal occurs due to the absence of proof for the collective land ownership (ulayat land), which is used and utilized collectively and communally. This article discusses the possibility of permanently grant the land certificates to provide legal protection for the adat peoples. Granting a certificate of land rights is possible if the government changes the land registration system from the negative to the positive system (torrens system). Adat peoples may acquire land certificates if they are considered as a legal entity. According to Indonesian law, only individuals or legal entities can register ownership of land. To make adat people a legal entity is by making regulations by the Minister of Agrarian and Spatial Planning which states that adat people in certain areas who have met the requirements are declared as legal entities.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.114
GPT teacher head0.306
Teacher spread0.193 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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