How to Fish With Respect: A Transformation of Human‐Fish Relations in Riverside Amazonia
Bibliographic record
Abstract
ABSTRACT Riverside inhabitants of the Middle Xingu River Basin, in the Brazilian Amazonia, frequently say that it is important to respect animals and the forest spirits who protect them. In recent decades, however, the development of an iced fish industry in the region has changed what respect means and how it is expressed when it comes to fishing. This article analyzes shifting attitudes toward fish by focusing on the transformation of the notion of panema , a word that denotes an acquired state in which one becomes incapable of hunting and fishing. I argue that the commodification of fresh fish has not altered the animistic principle that fish are imbued with an interior state of mind and other markers of personhood. Commodification, however, has decreased the importance of spirit owners and increased the importance of the mental state of the fishers in their accounts of their activities. I pose that such transformation can only be properly accounted for by breaking down the analytical distinction between political economy and ontology and focusing on how the riverside inhabitants see it as a normative issue, measured in regard to respect.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".