Forests, law and customary rights in Indonesia: Implications of a decision of the Indonesian Constitutional Court in 2012
Bibliographic record
Abstract
This paper reviews the emerging effects of the 2012 decision of the Constitutional Court of Indonesia relating to the customary management of Indonesia's traditional forests. It focuses on the challenge of moving from legal to political and societal recognition of Indigenous peoples’ rights. In its advocacy of customary land rights, Aliansi Masyarakat Adat Nusantara (AMAN) successfully applied to the Constitutional Court for judicial review of the Forest Law 41 1999. It argued the law breached the constitutional rights of its members in permitting the state to permit exploitation and development rights over traditional forest without their consent. The flow‐on effect of allocating such rights included widespread deforestation and land use change without agreement from customary communities that have used and occupied these forests for centuries, thus ignoring traditional customary law that regards these forests as the property of such communities. The paper reflects critically on international experience in the interface between legal recognition of Indigenous peoples’ rights, and their translation into sustainable and meaningful societal transformation.
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 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.018 |
| 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".