The Private Eye of Public Life: Surveillance, Security, and Urban Governance in the City of Toronto
Bibliographic record
Abstract
Market forces increasingly drive the development of urban space in globalized cities. Following deindustrialization, some municipalities have become dependent upon tax revenues derived from office towers. City managers and officer tower developers work under the pressure of competition to ensure their spaces are attractive to this highly mobile work force; safety and security are key selling points. In Toronto, large sections of urban space have been privatized and are policed by private security. Much of the privately owned space is designed to be publicly accessible, creating new dynamics between private security and public police. Changes to federal and provincial legislation, combined with a rapid expansion in the deployment of private security guards, signal an emerging urban governance model that supports private-public partnerships in policing. Under the supervision of David Murakami Wood, I conducted interviews with high-ranking politicians, security professionals, and social services executives in Toronto. These interviews revealed concerns about the erosion of public space, the treatment of marginalized populations, and inadequate private security regulations. Some argue the legal rights of private property owners permit security and surveillance practices that violate democratic values. Clearly, there is tension between the market forces that inform private policing, and the civic accountability of public police forces that remains unresolved. My research suggests new legislation is required to ensure this emerging urban governance model, which features private policing, preserves the democratic rights and freedoms of all citizens.
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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 | 0.002 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".