Bibliographic record
Abstract
Agroecological transitions aim to redesign the structure of contemporary global food systems to improve food security, ecosystem health, community development, worker livelihoods, and social and ecological justice. A fundamental principle of agroecology is the responsible governance of land. Yet land—as a concept, resource, and territory—is heavily contested through processes of colonization, enclosure, commodification, and financialization. The governance of land and natural resources is also intimately tied to questions of power and privilege—Who governs land? Who benefits, and who is excluded? These questions presuppose an ontological understanding of land that can also be contested: What is land, what purpose(s) does it serve, and for whom? In this article, we review key concepts at the intersection of land governance and agroecology. We take a case study approach to highlight how tensions around ontologies of land mediate agroecological futures in 2 settler-colonial contexts: Brazil and Canada. We then explore how land governance for agroecology might be experienced and understood across different land governance institutions—including relational and community commons, private property regimes, and new forms of hybrid land relations that challenge land privatization. We discuss how these land regimes influence people, landscapes, and agroecological outcomes and conclude with a consideration of the access, equity, and justice implications of different land governance approaches for sustainable food systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.022 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".