Negotiating heritage: cultural identity, community practice, and preservation politics in Toronto’s Chinatown
Bibliographic record
Abstract
This thesis investigates the impact of historic preservation policies and grassroots community efforts on the cultural identity of Toronto's Chinatown. As urban redevelopment shapes the neighborhood, questions arise about whether preservation protects culture or merely stabilizes architecture. The study explores how preservation is negotiated in a diasporic context through archival research, field observations, and a series of semi-structured interviews with residents, business owners, artists, and organizers. Key findings indicate a disjunction between government-led preservation frameworks and community perceptions of cultural value. Archival records, including the 1962 meeting between Chinese leaders and city officials, reveal the longstanding tension between development and cultural continuity. More recent cases, such as the opposition to mural projects by Friends of Chinatown Toronto, further highlight community resistance to top-down strategies perceived as "artwashing" or symbolic tokenism. The research emphasizes that cultural identity in Chinatown is not solely rooted in the physical environment but also in people's lived experiences, memories, and practices. The thesis reframes preservation as an ongoing negotiation rather than a static act by centering oral histories and grassroots activism. It ultimately argues for a more inclusive, community-responsive approach to heritage that prioritizes cultural sustainability over aesthetic or economic motives.
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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 | 0.017 | 0.012 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".