Food sovereignty: an alternative paradigm for poverty reduction and biodiversity conservation in Latin America
Why this work is in the frame
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Bibliographic record
Abstract
Strong feedback between global biodiversity loss and persistent, extreme rural poverty are major challenges in the face of concurrent food, energy, and environmental crises. This paper examines the role of industrial agricultural intensification and market integration as exogenous socio-ecological drivers of biodiversity loss and poverty traps in Latin America. We then analyze the potential of a food sovereignty framework, based on protecting the viability of a diverse agroecological matrix while supporting rural livelihoods and global food production. We review several successful examples of this approach, including ecological land reform in Brazil, agroforestry, milpa, and the uses of wild varieties in smallholder systems in Mexico and Central America. We highlight emergent research directions that will be necessary to assess the potential of the food sovereignty model to promote both biodiversity conservation and poverty reduction.
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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 | 0.000 |
| 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 | 0.001 |
| 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