A Study of the Role of Small Ethnic Retail Grocery Stores in Urban Renewal in a Social Housing Project, Toronto, Canada
Bibliographic record
Abstract
Urban renewal often drives away the original residents, replacing them with higher income residents who can afford the new spaces, leading to gentrification. Urban renewal that takes place over many years can create uncertainties for retailers and residents, exacerbating the gentrification process. This qualitative study explored how the urban renewal process in a multi-cultural social housing neighborhood in Toronto (Regent Park) affected the small ethnic retail grocery stores (SERGS) that supplied ethnic foods and items to the ethnic populations living there. Interviews were conducted with ten SERGS store owners/managers and 16 ethnic residents who lived in Regent Park before renewal and were displaced, or who were displaced and returned. The SERGS stated that they provided culturally familiar items and offered a social credit scheme that recognized existing social relationships and allowed low-income residents to afford food and other amenities in a dignified manner and pay later, without penalty or interest. At the same time, the SERGS were unsupported during the renewal, were excluded from the civic planning processes, could not compete for space in the new buildings, and experienced declining sales and loss of business. The residents stated that the SERGS were trusted, provided a valued cultural social spaces for ethnic identity formation, and ethnic food security but they faced many uncertainties about the role of SERGS in a renewed neighborhood. Based on this study, it is recommended that ethnic retailers be recognized for the role they play in formulating ethnic identities and food security in mixed-use mixed-income communities and that they be included in planning processes during urban renewal. Such recognition may enable more former residents to return and lessen the gentrification.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".