Food sovereignty, food security and health equity: a meta-narrative mapping exercise
Bibliographic record
Abstract
There has been growing policy interest in social justice issues related to both health and food. We sought to understand the state of knowledge on relationships between health equity--i.e. health inequalities that are socially produced--and food systems, where the concepts of 'food security' and 'food sovereignty' are prominent. We undertook exploratory scoping and mapping stages of a 'meta-narrative synthesis' on pathways from global food systems to health equity outcomes. The review was oriented by a conceptual framework delineating eight pathways to health (in)equity through the food system: 1--Multi-Scalar Environmental, Social Context; 2--Occupational Exposures; 3--Environmental Change; 4--Traditional Livelihoods, Cultural Continuity; 5--Intake of Contaminants; 6--Nutrition; 7--Social Determinants of Health and 8--Political, Economic and Regulatory context. The terms 'food security' and 'food sovereignty' were, respectively, paired with a series of health equity-related terms. Combinations of health equity and food security (1414 citations) greatly outnumbered pairings with food sovereignty (18 citations). Prominent crosscutting themes that were observed included climate change, biotechnology, gender, racialization, indigeneity, poverty, citizenship and HIV as well as institutional barriers to reducing health inequities in the food system. The literature indicates that food sovereignty-based approaches to health in specific contexts, such as advancing healthy school food systems, promoting soil fertility, gender equity and nutrition, and addressing structural racism, can complement the longer-term socio-political restructuring processes that health equity requires. Our conceptual model offers a useful starting point for identifying interventions with strong potential to promote health equity. A research agenda to explore project-based interventions in the food system along these pathways can support the identification of ways to strengthen both food sovereignty and health equity.
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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 | 0.044 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".