Bibliographic record
Abstract
Abstract A major challenge for food scholars is how they can explain the evolution of a global food system where distant social actors, ecologies, and places have complex, and often contradictory, relations. In particular, scholars face the difficult task of providing an account of food system change that is at once theoretically sophisticated, historically grounded, and holistic in its perspective. A leading example of this type of approach is food regimes analysis, which is anchored in historical political economy. The food regimes approach views agriculture and food in relation to the development of capitalism on a global scale, and argues that social change is brought about by struggles among social movements, capital, and states. The concept of food regimes was introduced by Harriet Friedmann and Philip McMichael in an article in which they addressed the changing role of food and agriculture in the development of global capitalism since 1870. Food regimes analysis combines two strands of macro-sociological theory: regulationism and world-systems theory. This article examines the theoretical, empirical, and methodological contributions of food regimes analysis, and looks at some of the latest developments in food regime theorizing and research.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".