Multi-scalar policy uptake of the six-dimensional food security framework
Bibliographic record
Abstract
In 2022, along with colleagues, we proposed a six-dimensional food security framework in a Food Policy viewpoint article that argued for the need to expand the commonly cited four pillar approach (availability, access, utilization and stability) by adding two additional dimensions: agency and sustainability. The proposal was not just for a new conceptual framework for scholarly analysis, but also for its application in policy settings. Over three years later, we are humbled to see widespread uptake of our call to embrace agency and sustainability as dimensions of food security in multiple tyles of policy settings at different scales. This brief policy comment outlines the growing recognition and application of the six-dimensional framework for food security in policy contexts from the global to the local level. We are hopeful that the growing application of this idea will help to make improvements in the global quest to end hunger.
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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 | 0.043 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".