Pandemic State Failure, Hydrocarbon Control, and Indigenous Territorial Counteraction in the Peruvian Amazon
Bibliographic record
Abstract
During the COVID-19 pandemic, the Peruvian government failed to protect its sparsely populated Amazon region. While infections were still rising, resource extraction was quickly approved to continue operations as a declared essential service that permitted an influx of workers into vulnerable indigenous territories despite weak or almost absent local healthcare. This article analyzes territorial counteraction as an indigenous response to pandemic national state failure, highlighted in a case of particularly conflictive stakes of resource control: Peru’s largest liquid natural gas extraction site Camisea in the Upper Amazon, home to several indigenous groups in the Lower Urubamba who engaged in collective action to create their own district. Frustration with the state’s handling of the crisis prompted indigenous counteraction to take COVID-19 measures and territorial control into their own hands. By blocking boat traffic on their main river, they effectively cut off their remote and roadless Amazon district off from the outside world. Local indigenous control had already been on the rise after the region had successfully fought for its own formal subnational administrative jurisdiction in 2016, named Megantoni district. The pandemic then created a moment of full indigenous territorial control that openly declared itself as a response and replacement of a failed national state. Drawing on political ecology, we analyze this as an interesting catalyst moment that elevated long-standing critiques of inequalities, and state neglect into new negotiations of territory and power between the state and indigenous self-determination, with potentially far-reaching implications on state-indigenous power dynamics and territorial control, beyond the pandemic.
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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 | 0.000 | 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 | 0.000 |
| 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".