Searching for an Authentic Chinatown: Studentification, Intangible Heritage, and Contentious Space
Bibliographic record
Abstract
Toronto’s Chinatown West is currently undergoing socio-spatial restructuring through intertwined processes of redevelopment, gentrification, and commercial change. In this Major Paper, I examine how the presence of urban universities are triggering much of this transformation. Building on recent global debates about universities and the role of students in neighborhood change, I unpack the effect of higher concentration of students on residential typologies and commercial change; and second, the politics of studentification in Chinatown West. \nOur findings indicate that vertical studentification occurs on both the residential and commercial boundaries of Chinatown. Similarly, an analysis of changes in the commercial orientation and employment patterns of Chinatown shows a move away from employment in retail and offices, into food services and part-time job opportunities catering to youth. Finally, we discuss how the growing intake of international students–particularly from China– in proximity to Chinatown creates new tensions and diverse reactions to neighbourhood change within the existing Chinese community. While some entrepreneurial community members, particularly those representing the business community are pro-growth, other long-term residents are concerned about the displacement caused by studentification and organize to contest new developments. The community responses from the long-term Chinese residents and other members of Chinese diaspora raise important questions on the future of Chinatown, who is Chinatown for, and how might a historically marginalized neighborhood be preserved in a rapidly growing city. The findings also highlight the interconnected nature between higher education institutions (HEIs) and their locality, and the volatility of student-focused neighborhoods to urban politics.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".