Multicultural democracy in the city: Explaining municipal responsiveness to immigrants and ethno-cultural minorities
Bibliographic record
Abstract
This study explores why and how local leaders in Canada's immigrant magnet city-regions adapt municipal governance structures in response to increasing levels of ethno-cultural diversity. It compares the responsiveness of eight highly diverse urban and suburban municipalities to immigrants and ethno-cultural minorities including: Toronto, Mississauga, Brampton and Markham in the Greater Toronto Area and Vancouver, Richmond, Surrey and Coquitlam in the Greater Vancouver Regional District. Given the novelty of this empirical terrain, the study begins by documenting and evaluating municipal responses and creates a typology of municipal responsiveness to immigrants and ethno-cultural minorities. Then, the dissertation explains why Canadian municipalities vary in their responsiveness to immigrants and ethno-cultural minorities by engaging with the dominant theoretical paradigm of the urban politics literature - urban regime theory. Through detailed case studies, the thesis documents the development of lasting coalitions---urban regimes---in several municipalities. In this way, it demonstrates how some municipalities have managed to develop policy capacity in the settlement and multiculturalism policy fields---despite their tight fiscal constraints---by pooling private sector and public sector resources. The inquiry also looks at factors that shape the way in which urban regimes develop. It develops two categories of ethnic configurations---"biracial" and "multiracial"--And explores how and why these configurations affect urban regime development. The study concludes that, all other things being equal, multiracial municipalities are less responsive to their immigrant populations than biracial municipalities. The analysis also explores the role of the intergovernmental context in municipal responsiveness to immigrants and ethno-cultural minorities. It finds that the province matters a great deal to municipal governance in Canada but in more complex ways than the constitutional relationship between provinces and municipalities would suggest. What is clear at the conclusion of this dissertation is that municipal governments are much more than simple "creatures of provinces". They are important democratic governments that are at the vanguard of social change.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".