“They're Colonizing My Neighborhood”: (Perceptions of) Social Mix in Canada
Bibliographic record
Abstract
In recent years, urban neighborhoods in many Western nations have undergone neighborhood restructuring initiatives, especially in public housing developments. Regent Park, Canada's oldest and largest public housing development, is a neighborhood currently undergoing ‘neighborhood revitalization’ based on the social mix model. One tenet of this model is the idea that original public housing residents are benefiting from interactions with middle class residents. Based on qualitative interviews and ethnographic observations with original housing residents as well as new middle–class homeowners, we examine whether cross–class interactions actually occur “on the ground” in Regent Park. By examining an iteration of the model that differs with respect to the direction of resident movement—that is, the revitalization of Regent Park involves more advantaged residents buying into the once low–income neighborhood, as opposed to providing lower–income residents with housing vouchers to move out of the community (and into more affluent neighborhoods across the city)—our study provides a unique contribution to the existing research on social mix. In particular, our research examines whether the direction of this resident movement has any distinct or demonstrable impact on: (1) the daily perceptions, attitudes, and actions of original and new residents, and (2) the nature of cross–class interactions. Second, unlike the vast majority of studies done in Europe and the United States, which are conducted “postrevitalization,” we examine the effects of neighborhood revitalization as the process unfolds.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".