Playing Into the Hands of the Powerful: Extracting “Success” by Mining for Evidence in a Payments for Environmental Services Project in Matiguás-Río Blanco, Nicaragua
Bibliographic record
Abstract
Payments for Environmental Services (PES) are premised upon the provision of monetary incentives to induce land-use practices viewed to be beneficial for advancing tropical conservation. A recent article published by Pagiola et al. in this journal claims that PES successfully transitioned land-use from agricultural use in Matiguás-Río Blanco, Nicaragua to silvopastoralism through afforestation and hence associated improvements in carbon sequestration and biodiversity conservation. Building on contrasting perspectives from peasants and local organizations in the region for more than a decade, we illustrate why viewing relations like payment provision and adoption of land-use outcomes that disregard parallel voices of implicated actors is not only analytically imprecise, but risks being anti-ecological if such a decontextualized connection is used to show evidence that tropical conservation is being advanced. We argue that the effect of payments must be contextualized with: a) increasingly globalized and expanding commodity frontiers for which PES programs may actually further advance to the detriment of tropical conservation; and b) the assumptions made in the methodological approaches adopted to determine causality. In sum, we highlight the dangers of uncritically portraying narratives of “success” to scale up investment to further proliferate decontextualized conservation projects that may not ensure long-term outcomes. We propose responding to these potential dangers through more open, horizontal, and long-term engagement on both the criteria and the consequences of defining success in tropical conservation interventions with actors whose lives are directly affected by them.
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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 | 0.025 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.016 | 0.028 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| 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".