Legal Recognition and Protection of Indigenous Land Rights: Analysis of the Legal Framework to Achieve Sustainable Development Goals
Bibliographic record
Abstract
The recognition and protection of customary land rights are crucial for the sustainable management of natural resources and the achievement of the Sustainable Development Goals (SDGs). Despite existing regulations such as the Basic Agrarian Law (UUPA No. 5/1960), the implementation of customary land rights remains hindered by legal ambiguities and conflicts with other sectors such as agriculture, mining, and infrastructure development. This study employs a qualitative approach to analyze the challenges in the legal recognition of customary land rights and examines practices from countries such as Canada, Australia, New Zealand, and Brazil. The findings suggest that the legal recognition of customary land rights must be strengthened through more inclusive reforms, allowing indigenous people to actively contribute to the achievement of SDGs, particularly in the areas of climate action and environmental conservation. The study recommends improving legal access for indigenous peoples, enhancing their empowerment in natural resource management, and integrating customary land rights into national sustainable development policies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".