Re-envisioning global agricultural trade: time for a paradigm shift to ensure food security and population health in low-income countries
Bibliographic record
Abstract
In this commentary, we use examples from West Africa to highlight how the liberalization of global agricultural trade exacerbates population health inequalities by threatening the livelihoods and food security of communities in low-income settings. We highlight the exploitative nature of trade agreements with West African countries demonstrating how these agreements disincentivize local agricultural investment and take jobs away from small-scale farmers. Further, we link agricultural trade liberalization to increased food insecurity, malnutrition, and exposure to environmental contaminants. Finally, we propose a paradigm shift that advocates for food sovereignty and the right to food.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.019 | 0.031 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".