Advancing an Integrative Framework to Evaluate Sustainability in National Dietary Guidelines
Bibliographic record
Abstract
The food system is responsible for some of society’s most pressing sustainability challenges. Dietary guidelines are one policy tool to help address the multiple sustainability challenges associated with food systems through dietary recommendations that better support environmental and human wellbeing. This article develops and applies a sustainability framework scoring tool comprised of four key dimensions (environmental, economic, human health, and sociocultural and political) and 32 sub-dimensions of sustainable food systems for the analysis and modification of national dietary guidelines. Two coders pilot tested the framework to quantify the occurrence of sustainability dimensions and sub-dimensions in national/regional dietary guidelines of 12 randomly selected high-income and upper-middle income countries including Albania, Australia, Brazil, the Grenadines, Grenada, Qatar, Netherlands, Nordic Countries, St. Vincent, Sweden, Thailand, the United Kingdom, and the United States. Sustainability Dimension Scores (SDS) were calculated as a percentage of the occurrence of the 8 sub-dimensions comprising each sustainability dimension and Total Sustainability Scores (TSS) were calculated as a percentage of the occurrence of the 32 sub-dimensions in each guideline. Inter-rater reliability of TSS and SDS indicated high validity of applying the sustainability framework for dietary guidelines. SDS varied between the four sustainability dimensions with human health being the most represented in the dietary guidelines examined, as hypothesized (average SDS score of 83%; range from 50-100%). Significant differences (p < 0.0001) were found in mean SDS between the four sustainability dimensions. Overall, results indicate that the ecological (average SDS score of 31%; range from 0-100%) economic (average SDS score of 29%; range from 0-100%), and socio-cultural and political (average SDS score of 44%; range of 0-100%) dimensions of sustainability are underrepresented in the examined national dietary guidelines with significant differences in SDS between guidelines (p < 0.0001). TSS varied by country between 12% to 74% with a mean score of 36% ( 20%). Brazil had the highest TSS (74%) followed by Australia (69%). The sustainability framework presented here can be applied by policy makers, researchers, and practitioners to identify gaps and opportunities to modify national dietary guidelines and associated programs for transforming food systems through diets that support planetary health.
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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 | 0.150 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.021 | 0.016 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".