Indigenous peoples, local communities, and Payments for Ecosystem Services
Bibliographic record
Abstract
Payments for Ecosystem Services (PES) programs are reshaping the governance of ecosystems and natural resources around the world. These programs often occur in spaces that are unceded, contested, or otherwise not legally recognized as Indigenous homelands, customary areas, and territories. Building on the discourses of Indigenous self‐determination, nationhood, and cultural responsibilities, this paper examines how PES programs produce unique outcomes for Indigenous peoples as ecosystem services providers. Our findings demonstrate and substantiate three themes that impact Indigenous ecosystem services providers uniquely: (1) the internationally recognized right to Free, Prior and Informed Consent for Indigenous peoples; (2) the reinforcement of settler colonial jurisdiction; and (3) mismatches between Indigenous knowledges and PES‐type approaches. The ways that PES programs run the risk of reifying and reducing Indigenous knowledges have not yet been adequately considered within current PES approaches. Our findings enable a conceptualization of PES as a new conservation tool within ongoing histories of land management and dispossession by settler colonial governments. We assess the strengths and challenges of PES programs as a departure from previous conservation modalities.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".