An Immigrant Neighbourhood as a Site of Planetary Urbanization: The Case of St. James Town, Toronto
Bibliographic record
Abstract
Immigration is a contested topic in a global reality defined by the spatiality of nation-states. However, in the case of South-North mobility, the public debate usually overlooks the role of colonial legacies and capitalist dependencies in shaping the patterns and trajectories of migration. On the scale of the Global North’s cities, narratives tend to revolve around the immigrant enclaves as problematic or dangerous. This dissertation informs the debate with a qualitative overview of the neighbourhood of St. James Town in Toronto, an area characterized by a strong immigrant presence. Analyzing the spatiality of immigrants on the scale of the nation-state, the city and the neighbourhood itself, it employs the conceptual framework of planetary urbanization to explain the role of newcomers as agents creating and maintaining global flows of capital and ideas, actively taking part in the production of space in Canada and far beyond it. At the same time, this work examines the spatiality of an immigrant enclave as an expression of a settler colonial nation-state, highlighting the vital role of spaces such as St. James Town in global and domestic patterns of precarity and exploitation. Portraying the neighbourhood in a dynamic moment of change, both in terms of infrastructural interventions as well as population structure, this dissertation highlights the resilience and community-formation skills of newcomers as well as the great cost of spatial and social adaptation. It also points out the shortcomings of the planetary urbanization concept, underscoring the necessity to include post-colonial criticisms and a nuanced, multi-faceted role of human mobility in explaining the works of global capitalism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.011 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".