Rethinking Multicultural Planning: An Empirical Study of Ethnic Retailing
Bibliographic record
Abstract
The recent waves of immigration have dramatically impacted urban landscapes and economies of Canada’s largest metropolitan regions. One notable phenomenon is the rise of ethnic retail strips and centers as physical markers of increasing multiculturalism. The dynamics of ethnic retailing pose various opportunities and challenges for municipalities; yet, our knowledge of its complexities is limited and current literature on multicultural planning offers little useful guidance in planning practice. This study examines three retail strips in the inner city of Toronto, namely East Chinatown, the Gerrard India Bazaar, and Corso Italia, and one suburban Asian theme mall, the Pacific Mall in the City of Markham in an attempt to identify the role of urban planning in responding to the rise of ethnic retail neighbourhoods. The findings of the four cases indicate that urban planners have been unable to intervene actively in ethnic retail and direct its development and growth. The planning legislative structure and the lack of policy support hinder planners’ capacity to be proactive. Planners cannot work alone to build multicultural cities. This paper concludes on the importance of municipal intervention and interdepartmental collaboration as useful implications for multicultural planning practice.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
| grok | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
| opus | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".