"Like an abandoned son": Clientelism, assistentialism, and state failure in Amazon oil benefit sharing policies
Bibliographic record
Abstract
Local benefit sharing is a highly relevant and unresolved topic in natural resources policy and research. This study examines local de facto outcomes of Ecuador's 2010 hydrocarbon policy reform in which the state legally assumed welfare responsibilities of communities affected by oil drilling, a role that oil companies had prior occupied in the country's emerging oil boom. Using political ecology lenses, this paper reveals how local clientelist and assistentialist relationships between oil companies and Indigenous Waorani communities have predominated in the region and affected the intended outcomes of the policy reform. These political dynamics enabled de facto arrangements of benefit sharing, wherein Waorani actors received continuing benefits from oil companies despite the reform's formal cancelling of these provisions. Moreover, the study shows how clientelist relationships continued through the state's policy reform as the state also failed to fulfill its reform promise to provide benefits at the local level. Drawing on an extended empirical fieldwork data set of interviews, document reviews, and participant observation at local, regional, and national levels, the case study illustrates local realities of extractive policy implementation in the Yasuni Amazon rainforest, which offers valuable empirical lessons on unintended de facto outcomes of benefit-sharing policy efforts at the intersection of resource extractive conflicts, Indigenous interests, and conservation goals.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".