Local Food Systems under a Global Influence: How Should We Holistically Assess Evolving Food Systems?
Bibliographic record
Abstract
In order to comprehend the impact of globalization on local food systems, it is crucial to consider sociohistorical, socioeconomic, and sociocultural trajectories, accompanied by long-term and cross-sectional monitoring. To achieve this objective, it is necessary to develop research protocols that enable the comparative evaluation of diets from the perspective of dietetics and nutrition, as well as local representations of food. Within the framework of an interdisciplinary and international OHM (Human-Environment Observatories) research network, a multidisciplinary team of researchers specializing in ethnoecology, health, nutrition, ecotoxicology, anthropology, and sociology was assembled. The network’s role is to conduct long-term studies on human-influenced ecosystems that are susceptible to socio-ecosystemic crises, such as those related to food and health. The consortium comprised researchers working within five OHMs, namely Estarreja (Portugal), Téssékéré (Senegal), Littoral-Caraïbes (Guadeloupe, France), Oyapock (French Guiana, France), and Nunavik (Québec, Canada), which focus on five distinct socio-ecosystems. Results: A cross-sectional data collection protocol was developed, consisting of a two-part questionnaire. Part 1 involves a structured 24 h dietary recall (24HR) that deviates from standard 24 h questionnaires by excluding portion sizes, instead focusing on food acquisition strategies and the degree of food item transformation. Part 2 encompasses a semi-structured interview guide that explores the concept of "eating well," barriers and facilitators to achieving it, changes in diet and dietary habits, and the connection between diet and health. This questionnaire captures, in a single session, the food items that individuals consumed the previous day, including their origin and level of transformation, as well as the associated perceptions regarding those food items and the overall diet. This approach enables the collection of data that facilitate the assessment of factors influencing diet from both the researchers’ point of view (i.e., etic perspective) and that of local populations (i.e., emic perspective). The questionnaire thus adopts a holistic approach, enabling us to analyze the links that populations establish between the socio-ecosystemic crises they have undergone (or are currently undergoing), their health and the evolution of their food systems.
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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 | 0.019 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.013 | 0.025 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".