The State of Local Food Systems and Integrated Planning and Policy Research: An Application of the Climate, Biodiversity, Health, and Justice Nexus
Bibliographic record
Abstract
Food systems are difficult to model, given the challenge of defining socially desirable food system outcomes. Research that aims to advance agri-food systems must reveal opportunities for integrated food systems planning and assess its outcomes. The climate, biodiversity, health, and justice (CBHJ) nexus provides such a lens, and it is a potentially useful tool for understanding how (or whether) food systems planning and policy studies employ a systems-based, integrated perspective. Further, it may be used to identify how agri-food systems planning and policy engage with local objectives and co-benefits related to climate change adaptation and mitigation, biodiversity conservation, community health, and social justice. This research proposes an indicator framework to operationalize the CBHJ nexus, by undertaking a scoping review of over one hundred local agri-food planning and policy studies. Outcomes from this work reveal the nature and degree to which agri-food systems research adopts a systems lens that comprehensively models resilience, sustainability, and justice. Outcomes related to biodiversity, procedural justice, and mental wellbeing were not common in the dataset. Recommendations from the work include guidance on how the nexus can broaden the quantitative and qualitative data-driven measurements of food system outcomes. Future work is required to define appropriate CBHJ outcomes and their possible measurements across scales beyond just local levels.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".