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Record W4393308851 · doi:10.18280/ijsdp.190319

Assessing Land Rights in Indonesia's Protected Forests: A Case Study of Tormatutung Region

2024· article· en· W4393308851 on OpenAlexvenueno aff
Bahmid Bahmid, Gautam Kumar Jha, Siti Nurzannah, David Pradhan

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeographyLand rightsAgroforestryEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

The research aims to analyze the complexities of land tenure in the Tormatutung protected forest region, where the issuance of land ownership certificates does not guarantee possession due to overlapping designations as registered and protected forest zones.This anomaly restricts certificate holders from exercising their legal rights over the land.The study assesses Indonesian land tenure policies, focusing on individual land ownership rights granted by certificates.Using a normative research method with a legislative approach, it examines statutory provisions and land use planning policies by relevant agencies responsible for issuing certificates and implementing land rights.The key finding of the research reveals governmental passivity in upholding land ownership rights in protected forest areas, prioritizing global forest preservation over individual property rights.The implications highlight governmental failure to protect the legal rights of certificate holders, constituting a violation of property rights.The research concludes the lack of coordination among government bodies leads to contradictory decisions in the Tormatutung forest area, necessitating proactive measures such as area remapping, reforestation of certified or community-controlled land, and collaborative agreements for regulated land use.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.289

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.289
Teacher spread0.271 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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