Bibliographic record
Abstract
We are frequently enjoined to eat in one way or another in order to reduce harm, defeat global warming, or at least save our own health. In this paper, I argue that individualism about food saves neither ourselves nor the world. I show connections between what Lisa Heldke identifies as substance ontologies and heroic food individualism. I argue that a conception of relational ontologies of food is both more accurate and more politically useful than the substance ontologies offered to us by certain approaches to both veganism and carnivory. Since relationality does not in itself offer normative guidance for eating, I ask how eaters might better practice relationality. With particular attention to Potawatomi scientist Robin Wall Kimmerer’s invitation to settlers to “become indigenous to place,” I suggest that forms of relationality based in anarchist practices of “mutual aid” better offer white settlers, and eaters more generally, a political approach to relational ontologies while resisting a tendency towards epistemic and spiritual extractivism. I argue that mutual aid approaches have much to offer to the politics of food and eating at every scale.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.063 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.020 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".