Global Governance from the Amazon: Leaving Oil Underground in Yasuní National Park, Ecuador
Bibliographic record
Abstract
This article explores the saga of the campaign to save the Ishpingo-Tambococha-Tiputini (ITT) block of the Yasuní National Park in Ecuador's Western Amazon, a story of the complex transnational networks and global governance mechanisms that have emerged to create post-Kyoto solutions for the planet. Ecuador's Yasuní-ITT Initiative to keep nearly 900 million barrels of oil underground in exchange for global contributions for avoided emissions presents an alternative norm for global environmental governance in line with the indigenous concept of buen vivir, or the good life. This means living in harmony with nature, and is embodied in the Ecuadorian Constitution of 2008. These changes, however, are not without pressures and inconsistencies at the domestic and international levels. Ultimately, the Yasuní-ITT Initiative and subsequent UNDP Yasuní Trust Fund offer replicable models for other fossil fuel dependent and megadiverse countries in the developing world.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".