Linking biodiversity, diet and health in policy and practice
Bibliographic record
Abstract
Simplification of human diets associated with increased accessibility of inexpensive agricultural commodities and erosion of agrobiodiversity leads to nutrient deficiencies and excess energy consumption. Non-communicable diseases are growing causes of death and disability worldwide. Successful food systems in transition effectively draw on locally-available foods, food variety and traditional food cultures. In practice this process involves empirical research, public policy, promotion and applied action in support of multi-sectoral, community-based strategies linking rural producers and urban consumers, subsistence and market economies, and traditional and modern food systems. Implementation of the International Plant Genetic Resources Institute's Global Nutrition Strategy in Sub-Saharan Africa offers a useful case study. Relevant policy platforms, in which biodiversity conservation and nutrition are and should be linked, include the Millennium Development Goals, Millennium Ecosystem Assessment, Convention on Biological Diversity, Global Strategy on Diet, Physical Activity and Health, Food-Based Dietary Guidelines, Right to Adequate Food and UN Human Rights Commission's Permanent Forum on Indigenous Issues. The largely unexplored health benefits of cultivated and wild plants include micronutrient intake and functions related to energy density, glycaemic control, oxidative stress and immuno-stimulation. Research on the properties of neglected and underutilized species and local varieties deserves higher priority. In tests of the hypothesis that biodiversity is essential for dietary diversity and health, quantitative indicators of dietary and biological diversity can be combined with nutrition and health outcomes at the population level. That traditional systems once lost are hard to recreate underlines the imperative for timely documentation, compilation and dissemination of eroding knowledge of biodiversity and the use of food culture for promoting positive behaviours.
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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 | 0.069 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.027 | 0.025 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.024 | 0.020 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".