Political Ecologies of Global Health: Pesticide Exposure in Southwestern Ecuador's Banana Industry
Why this work is in the frame
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Bibliographic record
Abstract
Pesticide exposure in Ecuador's banana industry reflects political economic and ecological processes that interact across scales to affect human health. We use this case study to illustrate opportunities for applying political ecology of health scholarship in the burgeoning field of global health. Drawing on an historical literature review and ethnographic data collected in Ecuador's El Oro province, we present three main areas where a political ecological approach can enrich global health scholarship: perceptive characterization of multi-scalar and ecologically entangled pathways to health outcomes; critical analysis of discursive dynamics such as competing scalar narratives; and appreciation of the environment-linked subjectivities and emotions of people experiencing globalized health impacts. Rapprochement between these fields may also provide political ecologists with access to valuable empirical data on health outcomes, venues for engaged scholarship, and opportunities to synthesize numerous insightful case studies and discern broader patterns.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it