Review of policy action for healthy environmentally sustainable food systems in sub-Saharan Africa
Bibliographic record
Abstract
Many sub-Saharan African (SSA) countries are experiencing multiple burdens of malnutrition. Rising overweight/obesity coexist alongside persistent burdens of under-nutrition and multiple micronutrient deficiencies. Poverty and social inequity remain key drivers of unhealthy diets and malnutrition. Diets in SSA are increasingly transitioning towards unhealthy (energy-dense, nutrient-poor and unsafe) and environmentally unsustainable diets. Healthy, sustainable food systems are required to deal with these considerable challenges equitably, so policy action needs to balance the health, environmental and economic dimensions of diets and food systems. We review evidence in recent literature for which policy actions have the best chance of success in SSA by appraising their likely impact, relevance, cost/affordability and feasibility to help guide policymakers and researchers in their development and evaluation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".