Multiple Discourses on Crisis: Farm, Agricultural, and Rural Policy Implications
Bibliographic record
Abstract
The terms farm crisis, agricultural crisis, and rural crisis have been invoked in political and policy discourse to characterize significant disruptions in or threats to rural–farm livelihoods. Although these expressions reflect a general sense of concern over the state of agriculture and rural existence, they lack clear and concise meaning. Academic research and policy development are obfuscated by the lack of definitional consensus or, at minimum, some shared understanding of the core aspects of farm‐related crisis. Much of the debate revolves around four main themes: farm financial difficulties (low or unstable incomes, indebtedness, and increasing reliance on nonfarm revenue), structural changes in agriculture (increasing scale, concentration, and consolidation), rural livelihoods (dwindling communities, institutions, and services), and international dimensions (market fluctuations, trade regulations, and disputes). The examination of these interrelated levels of analysis offers a valuable framework for interpreting the multifold contexts, meanings, and responses to crisis. This paper explores varied representations of farm–agricultural crisis, with particular emphasis on the presumed causes (or precipitating factors), conditions, and related policies and programs. Les expressions ≪ crise agricole ≫ et ≪ crise rurale ≫ sont évoquées dans le discours politique pour caractériser des perturbations ou des menaces importantes aux moyens de subsistance en milieu rural et agricole. Bien que ces expressions traduisent certaines inquiétudes concernant la situation des secteurs agricole et rural, leur signification manque de clarté et de concision. Les chercheurs universitaires et les élaborateurs de politiques sont déconcertés par le manque de consensus définitionnel ou, du moins, par le manque de vision commune des aspects fondamentaux de la crise agricole. Une grande partie du débat tourne autour de quatre thèmes principaux: les difficultés financières de l’exploitation agricole (revenu faible ou instable, endettement et dépendance accrue aux revenus non agricoles); les changements structurels dans le secteur agricole (augmentation de l’échelle de production, concentration et regroupement); les moyens de subsistance en milieu rural (diminution du nombre de collectivités, d’institutions et de services); les dimensions internationales (fluctuations du marché, règlements concernant les échanges commerciaux, différends). L’examen de ces niveaux d’analyse interreliés offre un outil précieux pour interpréter les multiples contextes, significations et réactions aux crises. Le présent article analyse les diverses représentations de la crise dans le secteur agricole et se penche particulièrement sur les causes présumées (ou facteurs déclenchants), les conditions ainsi que les politiques et programmes connexes.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.017 | 0.049 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".