Municipal corporate security and risk mitigation companies in Canadian cities: a new military urbanism?
Bibliographic record
Abstract
Despite Western cities’ long history as settings for democratic politics and freedom of public movement in open streets, markets, and squares, in the twenty-first century, cities are increasingly viewed as major sites and sources of risk. The risks include terrorism and street crime. But cities are also deemed to be sources of risk insofar as they are thought to create conditions that harm citizens, for which city governments can be held liable. As both site and source of risk, many organizations have sought to securitize and police cities. Their efforts take multiple forms, from building secured residential high-rise developments, to deploying sophisticated camera surveillance systems in commercial districts, to stepping-up municipal police and private security patrols in residential neighborhoods, to posting signs listing hazards to persons and property in city-owned parking lots and recreation facilities, and more. Indeed, there is neither a shortage of agencies rethinking the city as a site or source of risk nor of securitizing and policing strategies that see and remake the city this way. As we noted in this book’s Introduction, this is one reason1 why we say cities throughout the world are becoming policing cities. This pluralization of policing in cities is fascinating given that municipal public police services in the West now openly acknowledge what has been known since their modern Peelian beginnings in nineteenth-century London; public police cannot be everywhere at once and must share the substantial load of security provision (see Shearing and Marks 2011). Indeed, Sir Robert Peel implied the public should help shoulder this load in espousing his famous idealized view of London’s police as the public, and the public as the police. But this chapter focuses on a decidedly more clandestine collection of agents than the public police and with whom this seemingly escalating burden is to be shared. Their distinctive securitizing and policing strategies that are mundanely practiced with little fanfare seem antithetical to traditional ideals of democracy and freedom of movement in cities. They may even befit a creeping militarization of the urban.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.033 | 0.021 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".