Biocultural Diversity in the Sustainability of Developing-Country Food Systems
Bibliographic record
Abstract
The policy implications of a model of contemporary food systems for developing countries that integrates nutrition, reduction of disease risk, culture, income generation, and biodiversity are reviewed within a theoretical and empirical examination of the relevance of nutrition to the priorities put forward at the World Summit on Sustainable Development in Johannesburg, South Africa, 2002. Agricultural, health, economic, and social policies with local reach are necessary responses to the increase in noncommunicable disease associated with the globalization of food systems. Nutrition offers a nexus for the changes in individual behavior and motivation essential for fundamental shifts in production and consumption patterns. Mutual consideration of biocultural diversity and nutrition can guide policy, research, promotion, and applied action in developing countries. Benefits from enhanced use of biodiversity must legitimately flow to the undernourished poor, while potential negative consequences must be minimized and mitigated. Quality and quantity of food need not be mutually exclusive. Functions related to energy density, glycemic control, oxidative stress, and immunostimulation define important research priorities. Tests of the hypothesis that biodiversity equates with dietary diversity and health might combine quantitative indicators of dietary and biological diversity with nutrition and health outcomes. Biodiversity, where it is part of traditional agricultural and food systems, can be best conserved and enhanced through rational use within a broad-based developmental focus on small-scale and low-input production. The fact 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 behaviors.
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.
How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".