A quest for questions: The JUSTRA as a matrix for navigating just food system transformations in an era of uncertainty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A just food system transformation is imperative to meet this century's goals of environmental sustainability, economic fairness, and equitable social well-being. While considerations of justice are beginning to inform food system transformation debates, there remains a lack of conceptual and practical integration of these two historically separate disciplinary perspectives. This perspective therefore proposes the just transformation matrix (JUSTRA), which integrates justice and transformation concerns using an interrogative approach. Interrogatives probe the historical, present, and future intersections of justice with specific food system elements. If used conscientiously, the JUSTRA can assist a wide spectrum of food system actors in strategizing, implementing, and monitoring just food system transformations. It can also help stakeholders to more thoughtfully engage with power imbalances both among users and in the food system more broadly—if used "in bona fides." Thus, while further testing is necessary to fully realize the potential of the JUSTRA, the matrix can become a powerful tool in multi-stakeholder dialogues to navigate unpredictable, diverse, and power-laden complexities of just food system transformations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it