Concepts, Methods, and Parameters: A scoping review of tools for assessing food system sustainability
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
Despite increasing efforts to assess sustainability in food systems, methodological inconsistencies and gaps in comparability, transparency, and stakeholder participation persist. This scoping review maps and synthesizes conceptual models and methodological approaches underlying existing assessment tools, including life cycle assessment (LCA), sustainability indicators, and multicriteria analysis. A systematic search of four databases (Web of Science, Scopus, PubMed, and Embase) identified 1,487 documents, with 50 selected for in-depth analysis. The findings reveal regional disparities, with Europe leading holistic food system assessments, while Africa and Asia show a latent demand for context-specific approaches. Sustainability remains a polysemic concept, often lacking a clear definition. However, most frameworks integrate food security and nutrition, and sustainable diets as guiding concepts. At the national level, tools emphasize broad sustainability outcomes—such as food insecurity, poverty, greenhouse gas emissions, carbon and water footprints, animal welfare, and food loss and waste—while local-scale tools focus on supply chain processes, including production, resource and waste management, transportation, and food processing. Although indicators generally align with the environmental, social, economic, and health and nutrition domains, further refinement is needed for internal activities. The limited disclosure of criteria applied, types of stakeholders involved, and the scarce use of quantitative methods raise concerns about bias and reproducibility. This review defines minimal parameters to guide future sustainability assessment tools for food systems, revealing trade-offs in scale, level, and scope.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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