Concepts, Methods, and Parameters: A scoping review of tools for assessing food system sustainability
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.
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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 | 0.117 | 0.281 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.054 | 0.046 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| 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".