Sustainable Agri-Food Systems: Environment, Economy, Society, and Policy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agri-food systems (AFS) have been central in the debate on sustainable development. Despite this growing interest in AFS, comprehensive analyses of the scholarly literature are hard to find. Therefore, the present systematic review delineated the contours of this growing research strand and analyzed how it relates to sustainability. A search performed on the Web of Science in January 2020 yielded 1389 documents, and 1289 were selected and underwent bibliometric and topical analyses. The topical analysis was informed by the SAFA (Sustainability Assessment of Food and Agriculture systems) approach of FAO and structured along four dimensions viz. environment, economy, society and culture, and policy and governance. The review shows an increasing interest in AFS with an exponential increase in publications number. However, the study field is north-biased and dominated by researchers and organizations from developed countries. Moreover, the analysis suggests that while environmental aspects are sufficiently addressed, social, economic, and political ones are generally overlooked. The paper ends by providing directions for future research and listing some topics to be integrated into a comprehensive, multidisciplinary agenda addressing the multifaceted (un)sustainability of AFS. It makes the case for adopting a holistic, 4-P (planet, people, profit, policy) approach in agri-food system studies.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it