“Momma always said that woman was the epitome of resource”: Contesting Canada’s Colonial-Capitalist Food Systems in Jonny Appleseed
Bibliographic record
Abstract
Despite living in a colonial-capitalist society structured to exploit their lands and bodies, the Oji-Cree women in the novel Jonny Appleseed, (2018) written by Joshua Whitehead (Two-Spirit Oji-Cree/nêhiyaw member of Peguis First Nation), resist settler-Canadian hegemony by feeding themselves and their communities through subversive acts of food sovereignty. According to Audra Simpson (Kahnawà:ke Mohawk), the Canadian settler-colonial regime legitimizes its occupying presence on Turtle Island by deteriorating, disappearing, and killing Indigenous women. Inflicting hunger – preventing Indigenous people from nourishing their bodies – is just one of the multifarious forms of violence administered by the settler state in efforts to eradicate Indigenous presence from the land. As a result, as the Oji-Cree women in the novel navigate a matrix of intersecting capitalist, colonial, heteropatriarchal, and white supremacist policies and (infra)structures to feed themselves and their relatives, they engage in resistance; they refuse to disappear. This chapter examines the setting of Winnipeg through an analytic lens of settler colonial urbanism and racial capitalism. The characters Peggy and Jordan demonstrate ingenuity, resourcefulness, and resilience as they employ creative foraging methods to obtain food from their hostile, hyper-capitalist environment. Jordan combines her extensive knowledge of Winnipeg’s grocery and restaurant infrastructure with her intimidating yet friendly demeanor to procure discounted or free meals, which she regularly shares with her friends. Peggy similarly defies capitalist norms by obtaining and distributing vital resources to isolated or otherwise immobilized Indigenous residents in both Winnipeg and Peguis First Nation. In performing these acts of community care, Peggy also challenges the settler-imposed boundary between urban and reserve spaces on Treaty One territory.
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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 | 0.001 |
| Science and technology studies | 0.039 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".