The "Paris Problem" in Toronto: The State, Space, and the Political Fear of "The Immigrant"
Bibliographic record
Abstract
The Paris Problem in Toronto addresses contemporary debates on place-based urban policies in the immigrant neighbourhoods of Western metropolitan centers. Taking the ideologically constructed figure of the immigrant seriously, I emphasize the need to examine the relational formation of urban and imperial policies and politics of intervention. Focusing on Toronto (Canada), a city celebrated for its diversity management and tolerance, the central thesis of this dissertation is that the material force of the ruling classes political fear of non-White working-class populations and neighbourhoods is central to the formation of place-based urban strategies. This political fear feeds upon a territorialized and racialized security ideology that conceives of non-White working-class spaces as potential spaces of insecurity, political disorder and violence. It is based on this security ideology and its link to race riots that the Paris problem has become a common reference point in policy circles in Toronto since 2005. I show how this territorialized and racialized security ideology is camouflaged within a liberal humanitarian ideology that renders non-White working-class spaces as spaces simultaneously in need of securitization and tutelage. Such a rendition parallels the perceptions of ungoverned spaces in the war on terror. I examine major place-based social development policies (Priority Neighbourhoods, Toronto Strong Neighbourhood Strategy 2020), place-based housing redevelopment policy (Tower Renewal), and national and urban policing strategies, providing the first comprehensive socio-historical analysis of place-based urban policy targeting non-White poverty in Toronto that began in the 1990s. I have traced the ideological formation and transformation of major policy techniques like mapping and policy concepts such as: poverty, security, policing, development, empowerment, social determinants of health, equity and prevention across various scales and temporalities. Instead of eradicating or reducing poverty, the goal of such policies is to constitute a liberal post-colonial poor, one who is eminently less threatening to the political stability of imperialist capitalism. My research shows that the state can mobilize place-based policy as a modality of neo-colonial pacification. Not reducible to a product of neoliberalization, such a policy recomposes colonial relations of domination by moderating violence and pacifying perceived threats to the existing order.
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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 | 0.002 |
| Science and technology studies | 0.027 | 0.030 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".