Icons and Identity: A Study of Two Museums and the Battle to Define Toronto
Bibliographic record
Abstract
Iconic architecture has become a popular “hard-branding” strategy among urban policymakers hoping to elevate the global status of their city and attract outside investment, tourists, and skilled migrants. However, iconic architecture is more than just an economic tool; it is an attempt to create a symbolic representation of place which, in the process, physically reshapes the urban landscape itself. As such, iconic architecture offers an important opportunity to study the relationship between abstract notions of place and concrete urban development practices. Focusing on this relationship, this dissertation investigates two museum expansion projects in Toronto: the Royal Ontario Museum and the Art Gallery of Ontario. Both museums hired internationally-renowned architects to design striking, iconic facades and both projects became mired in political controversy that pitted the museums against members of the surrounding community. Focusing specifically on the role of culture and meaning, the dissertation offers three main findings. First, it reveals that public cultural institutions (the primary clients of iconic architecture) use this development strategy to generate political legitimacy and, by extension, attract outside financial support. By asserting themselves physically within the cityscape, they similarly attempt secure a central place within local public life. Second, the dissertation demonstrates how competing notions of place can emerge between different groups of urban inhabitants and subsequently become the basis for urban political struggle. Employing cognitive mapping analysis, the dissertation demonstrates how the museums’ cosmopolitan vision for Toronto contradicted more locally-focused notions of place held within the community. Finally, in examining how this political conflict played out during development, the dissertation reveals the importance of “performative power” in forging community consensus and overcoming initial differences. More specifically, the success of the projects depended on how well the museum leadership conformed to existing cultural expectations held within the community. These findings, taken as a whole, provide important empirical and theoretical insights into how urban inhabitants understand place, and how these understandings inform their actions within the context of major urban development projects.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.049 | 0.024 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".