Masyarakat Adat, Difference, and the Limits of Recognition in Indonesia's Forest Zone
Bibliographic record
Abstract
‘We will not recognize the Nation, if the Nation does not recognize us’ This statement was made by AMAN (Aliansi Masyarakat Adat Nusantara), the Alliance of Indigenous People of the Archipelago, at their inaugural congress in Jakarta, March 1999. The congress was organized by a consortium of Jakarta-based NGOs, and funded by international donors (USAID, CUSO, and OXFAM among others). Building upon a process of mobilization that began with the International Year of Indigenous People in 1993, the Congress marked the formal entry of masyarakat adat (literally, people who adhere to customary ways) as one of several groups staking claims and seeking to redefine its place in the Indonesian nation as the political scene opened up after Suharto's long and repressive rule. AMAN and its supporters assert cultural distinctiveness as the grounds for securing rights to territories and resources threatened by forestry, plantation and mining interests backed by police and military intimidation. Their attempt to place the problems of masyarakat adat on the political agenda has been remarkably successful. While seven years ago the head of the national land agency declared that the category masyarakat adat, which had some significance in colonial law, was defunct or withering away (Kisbandono 18/02/93), the term now appears ever more frequently in the discourse of activists, parliamentarians, media, and government officials dealing with forest and land issues.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.019 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".