The Food Police: The White Possessive Securitization of Winnipeg Food Spaces
Bibliographic record
Abstract
Grocery shopping is one of the most necessary everyday practices when it comes to being food secure. Food security is frequently spatially imagined along two axes – access and health. I highlight the specific conditions of existence for food insecure citizens in Winnipeg to demonstrate the incommensurability of how food insecurity is imagined and intervened upon, or not, through municipal policy. Drawing on Critical Indigenous Studies scholar Aileen Moreton-Robinson’s theorizations of white possession, I establish a framework of white possessive securitization to interrogate the dynamics between policy, policing, and securitization of space that results in Indigenous people being subjected to multiple modes of policing when grocery shopping. With white possessive securitization, I trace how individual settler citizens operate as self-governing subjects to police Indigenous people in the city while carrying out the aims of white patriarchal sovereignty – to secure private property. I provide three vignettes of the intersections of municipal policy and the policing of food by focussing on municipal budgets, securitization of public-private space, and grocery stores. These vignettes delineate how policing in grocery stores interfere with Indigenous food security and are inseparable from inflated municipal policing budgets, austerity measures that reduce community services, increased surveillance, threats of violence, and the undiscriminating implementation of the rule of law by individual settler citizens who through rationalities of governmentality are the police.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".