The species-specific role of wildlife in the Amazonian food system
Bibliographic record
Abstract
We examine ways in which the role of wild animals in the Amazonian food system may be socially differentiated and species-specific. We combine a hybrid framework of food choice preferences and theorizing on access to natural resources with fieldwork in Brazilian Amazon, where social and environmental challenges coalesce around the role of wildlife in feeding a growing urban population. Based on 798 household surveys across four towns, we found that consumption of, and taste preferences for, selected species of mammals, fishes, birds, and reptiles are related to variation in means of access (e.g., level of social trust - the basis of reciprocity and informal urban safety nets), and having rural cultural origins (marginal to migrants’ other socioeconomic differences). The likelihood of eating particular species was associated with taste preferences and household experiences of food insecurity. Hunting and fishing households consumed many wild species; it is unclear if they depend heavily on any in particular. Vulnerable species, including manatee, tortoise, and river turtle, were eaten mainly by relatively privileged households, and less so by other households (e.g., rural-urban migrants). Rural origins increased by 90% the likelihood of a strong wild meat preference, compared to other households. Evidently, wildlife consumption is a rural tradition that influences migrants’ dietary practices in towns, through the interplay of preferences, means of access, and context. Finally, severe and moderate food insecurity was associated with eating howler monkey and catfishes (barred and redtail) and not eating manatee and turtle. Hence, urban consumption of some, but not all, wild species is associated with household disadvantage and food insecurity. Amazonian town-dwellers consume many wild species, drawing on diverse means of access, which are species-specific and reflect social inequalities. Species-specific governance of wildlife consumption may help balance the risks of overharvesting against the well-being of Amazonia’s vulnerable town-dwellers.
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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 | 0.001 | 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".