Contradictory distributive principles and land tenure govern benefit-sharing of payments for ecosystem services (PES) in Chiapas, Mexico
Bibliographic record
Abstract
Abstract Payments for Ecosystem Services (PES) are incentive-based instruments that provide conditional economic incentives for natural resources management. Research has shown that when economic incentives are parachuted into rural communities, participation and benefits are collectively negotiated and shared. However, we know little about how benefit-sharing evolves over time in community-based PES. To address this gap, we examine distributional justice in four communities of the state of Chiapas, Mexico, which participate in a PES programme, and we assess how local justice principles compare with the programme’s goals. Our analysis reveals patterns of both continuity and change in how communities share PES benefits, which reflect a suite of contradictory justice principles, including entitlement, merit, need, and equality. The studied communities distribute PES benefits by providing differentiated compensation to diverse groups of landholders via private cash payments, whilst also attending non-landed community members through public infrastructure investments. We show that benefit-sharing is strongly influenced by pre-existing land tenure features and associated norms, which in the study area include three different types of individual and common-property. Yet, we also show that communities continuously adjust benefit-sharing arrangements to navigate distributional challenges emerging from programme engagement. Overall, we provide novel insights on the evolution, diversity, and complexity of distributive justice in community-based PES and we advocate for a context-sensitive, nuanced, and dynamic account of justice in incentive-based conservation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".