Aga Khan Museum and Ismaili Centre as alternative planning model for mosque development
Bibliographic record
Abstract
Multiculturalism is widely celebrated in Toronto as a cornerstone of our society. When multiculturalism moves outside festivals and food, groups make spatial claims of citizenship and identity, the experience is somewhat different. There is no doubt that some racialized minorities have fared well in the Greater Toronto Area. Their growth is no longer confined to low-income enclaves within the City of Toronto but into city suburbs. This growth comes with the increased demand for spatial citizenship through culturally suited social, recreational, commercial and religious space. It is here where the experience of multiculturalism changes. The inherently political and contentious process of land use planning and its response to individual groups needs for certain type of developments is the broad focus of this paper. The paper looks at how the practice of planning in the Greater Toronto Area has responded to social diversity in cities by studying the specific process of mosque development for Muslim Canadians. Mosque development has faced challenges in the planning arena through staunch opposition that often hides behind legitimate planning technicalities to express the personal distaste for a group of people. My goal was to understand the role of planning departments in recognizing and responding to the rise of these conflicts in land use development. he paper examines the development process of five specific traditional mosques in the Toronto area to identify disputes and challenges. These are compared with a different \ntype of Islamic development--the Aga Khan Museum, Park and Ismaili Centre--to better understand how features such as multifunctionality, scale and status appear more acceptable to planning and the general public producing fewer obstacles in its development as compared to traditional mosque development. I look at how wealth, starchitecture, the framing of the development as cultural rather than a religious, and the support of local organizations contribute to the success and acceptance of a project, as compared to traditional mosque developments. The paper is organized into three sections: 1) a review of the Aga Khan development in order to understand the purpose and the development process; 2) an examination of the development of more conventional mosques in the Greater Toronto Area with an \nemphasis on the challenges in such developments; and 3) an analysis elucidating some material concepts and themes that emerge from the case studies in order to facilitate in improving the planning process for mosques.
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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 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".