The Global City versus the City of Neighborhoods: Spatial Practice, Cognitive Maps, and the Aesthetics of Urban Conflict
Bibliographic record
Abstract
Political–economy, which conceptualizes space as a resource over which different groups struggle, has long been the dominant perspective in the study of urban conflict. However space is also a cultural object from which actors derive particular meanings. In order to understand how meaningful interpretations of space give rise to urban conflict, this paper examines the architectural expansions of two Toronto museums. Both projects were fiercely opposed by local creative and professional class residents—a group who might be expected to welcome elite architecture and cultural investment. To explain the origins of this conflict, I demonstrate how the museum leadership and surrounding community understood the spatial context of the expansion projects in strikingly different ways. While the former group saw Toronto as a “global city” and looked to international landmarks for precedents, the latter saw Toronto as a “city of neighborhoods” and were more concerned with how the projects contributed to more mundane aspects of the neighborhoods such as parks and playgrounds. I attribute these different “aesthetic” interpretations to the distinct spatial practices and associated cognitive maps of each group.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.060 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".