Correlates of wildlife hunting in indigenous communities in the Pastaza province, Ecuadorian Amazonia
Bibliographic record
Abstract
Abstract Wild meat is an important source of dietary protein and fat for many indigenous peoples in Amazonia. However, rates of wildlife harvest are often unsustainable, threatening not only biodiversity but also the food security of indigenous peoples. During the last decades, Ecuadorian Amazonia has undergone profound socioeconomic changes which have significantly altered peoples' livelihood strategies. Little is known, however, how such changes have affected wildlife hunting. Based on data from a household survey, this paper analyzes the socioeconomic drivers of wildlife hunting among indigenous peoples in Pastaza, in the Ecuadorian Amazonia. The results of a random‐effect tobit analysis reveal that, wealthier households which have higher shares of off‐farm and non‐farm employment tend to harvest smaller amounts of wild meat. A probable explanation to this is that having a permanent and well‐paid job implies an increased opportunity cost of time, leading to a decrease in the time spent hunting and, therefore, decreased wildlife harvests.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".