Agricultural Power: Politicized Ontologies of Food, Life, and Law in Settler Colonial Spaces
Bibliographic record
Abstract
In this dissertation, I develop a theoretical account of agricultural power in the settler colonial contexts of Canada and the United States. By analyzing archival, historical, and legal documents, I argue that the imposition of animal agriculture not only functioned as a method of settler territorialization, but also relied on and reproduced western humanist ontologies of food, humans, animals, and land in these spaces. These ontologies are not objective accounts of reality but are contingent expressions of power that continue to shape alimentary norms and food law. Agricultural power is not constrained to the location of the farm, but is strategically deployed in various registers to re-secure animal-based ontologies of food. Based on an analysis of proposed food legislation and legal cases seeking to enjoin the use of the terms milk, meat, and eggs on plant-based food labels, I show that agricultural power works via law to reproduce ârealâ food as only animal-based. I then argue that agricultural power and its concurrent ontologies of food and animals continues to shape new meat technologies despite the absenting of the animal from its production methods. In-vitro meat represents a modified form of agricultural power where its target shifts from the location of the animal body to the animal cell. Agricultural power is then a mobile and shifting constellation of relations variously deployed through legal and cultural institutions to reproduce animal-based ontologies of food. Regardless of its point of application, the property status of nonhuman animals is foundational to its exercise. Despite my critiques of the food ontologies produced and sustained by agricultural power, I argue that it remains a useful political project to ontologize food as a means of cultivating ethical relations between humans, animals, and the more than human world. To this end, I introduce a contextual ontological veganism premised on a distinction between edibility and food, and where human and animal interests are weighed equally. In this sense, someone or something that is edible should only be ontologized as food based on an evaluation of the relations that produced this item and that are constituted through its consumption. Given how law and agricultural power co-articulate to ontologize animals as property, I propose that this food politics be structured by a non-anthropocentric legal subjectivity of beingness for nonhuman animals where they exist neither as property nor as persons, but are recognized as vulnerable, embodied, and relational (Deckha forthcoming). In so doing, the contextual ontological veganism outlined in this dissertation has legal, ontological, and ethical implications for how we understand ourselves and for how we relate to others through eating.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.067 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".