Theorizing Food Sovereignty from a Class-Analytical Lens: The Case of Agrarian Mobilization in Argentina
Bibliographic record
Abstract
Where do the conceptual ambiguities of food sovereignty lie and how can they be overcome? This article identifies a total of five challenges that underlie these ambiguities, namely the challenge of determining how food sovereignty as a research framework can address the tensions between: (a) state–movement relationships, (b) local–national interests, (c) rural–urban conflicts, (d) individual–collective choices and (e) political intermittence–organizational continuity. Using the method of integrative review, I argue that these challenges could be overcome if the criteria for addressing these tensions were based on the interests of the classes of labour by re-envisioning food sovereignty as a social mobilization outcome that potentially leads to agrarian class formation. A class-analytical approach to food sovereignty is thus deployed to study the case of Argentina in order to contribute to a more in-depth theoretical refinement and resolution of the conceptual ambiguities of food sovereignty.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".