Toward Agricultural Intersectionality? Farm Intergenerational Transfer at the Fringe. A Comparative Analysis of the Urban-Influenced Ontario's Greenbelt, Canada and Toulouse InterSCoT, France
Bibliographic record
Abstract
Peri-urban agriculture can foster the resilience of metropolitan areas through the provision of local food and other multifunctional agricultural amenities and externalities. However, in peri-urban areas, farming is characterized by strong social uncertainties, which slow the intergenerational transfer of farm operations. In this article, we tackle the beliefs that underlie farmers' decision-making to identify planning opportunities that may support farm intergenerational transfers. The design of an institutionalist conceptual framework based on Keynesian uncertainty and Commonsian Futurity aims to analyze farmers' beliefs associated with farm intergenerational transfer dynamics. The dataset of this comparative analysis includes 41 interviews with farmers involved in animal, cash-crop, and horticulture farming in the urban-influenced Ontario's Greenbelt, Canada, and Toulouse InterSCoT, France, during which farmers designed a mental model of their investment decision-making. The results highlight the dominance of a capital-intensive farm model framed by a money-land-market nexus that slows farm structural change. The subsequent access inequalities, which are based on characteristics of farmers and their farm projects, support the idea of the existence of an agricultural intersectionality. The results also highlight the positive role of the institutional context; when farmers' beliefs are well-aligned with the beliefs that shape their institutional environment, the frictions that slow farm structural change in peri-urban areas are moderated by a shared vision of the future.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".