International environmental law and the role of indigenous peoples in protected areas: hope for creative solutions in a setting of established incompatibility
Bibliographic record
Abstract
This article is an attempt at presenting the complex subject matter in three main parts, with an emphasis on recent developments and changes in international environmental legislation: (I) The first two sections briefly introduce indigenous peoples and a classification of those protected areas (PAs) where conflictual conditions arise, followed by an overview of international environmental law in section 3. (II) Section 4 draws up a typology of the problems, with selected case studies to illustrate the existing conflicts as well as possible solutions.(III) Sections 5 and 6 then explore the emerging paradigm shift and the way forward where the potential of indigenous peoples for better managing the world's natural resources is highlighted.The article ends with a cautiously optimistic conclusion.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.084 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".