They Have Always Been Military: On So-Called Militarized Policing in Canada
Bibliographic record
Abstract
Over the last few years there has been growing attention to and discussion of the so-called militarization of policing. Unfortunately, much of this discussion poses the militarization of policing as a recent phenomenon. This paper examines policing in Canada within the context of an ongoing military practice. It shows that policing was founded on a military basis and continues to be carried out on a military basis as exemplified in the more recent developments that have raised alarm about militarization. It raises the need for a retheorization of policing within the context of capitalist social struggles and highlights some instructive recent theoretical developments toward that end. Properly understanding the police in Canada can help to contextualize and challenge current responses that are limited to reforms for police (de-militarization, de-escalation, improved training, non-lethal weaponry, etc.) or which even allow for the expansion of policing (community policing, drones, etc.). [Article copies available for a fee from The Transformative Studies Institute. E-mail address: journal@transformativestudies.org Website: http://www.transformativestudies.org ©2024 by The Transformative Studies Institute. All rights reserved.] KEYWORDS: Canada, Colonialism, Militarization, Policing, Protest, Royal Canadian Mounted Police, Settler States, War.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.030 | 0.016 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".