Health Inequities and the Shifting Paradigms of Food Security, Food Insecurity, and Food Sovereignty
Bibliographic record
Abstract
Global hunger, food insecurity, and malnutrition are on the rise, partly resulting in furthering health inequities between classes and groups of peoples among and within countries. A systematic understanding of the links between inequities in food politics and health issues is a challenge, and it is partly complicated by the presence of 3 contending and shifting paradigms in food politics, namely, food security, food insecurity, and food sovereignty. These paradigms suggest competing views as to the causes of and solutions to hunger, food insecurity, and malnutrition. We argue that food sovereignty offers a better alternative for understanding and responding to food issues in relation to the challenge of tackling health inequities. However, the ways in which and the degree to which the issues of health inequities are incorporated in the current narratives and practices of food sovereignty is rather thin, and vice versa. Our concluding argument is that an interactive dialogue in research and social actions between food sovereignty, on the one hand, and health inequity, on the other hand, can mutually enrich and strengthen both fields of research and spheres of social actions.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.078 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".