The strategic uses of race to legitimize ‘social mix’ urban redevelopment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article contends examines how racialization – the strategic employment of racial discourses to both define- and legitimize-specific social and spatial changes – serves as an adaptive and strategic means for city leaders and developers to control, define, plan and implement efforts to reshape impoverished neighborhoods. The deployment of racial tropes and narratives, such as diversity and ‘social mix’, organize and make legible redevelopment and its consequences of displacement for communities of poor minority residents. Urban development initiatives are imagined, worked out, legitimated and reconciled in an urban politics that relies on the deployment of racialized discourses of colorblindness, inclusivity and diversity. Drawing on a case study of redevelopment of Regent Park in Toronto, Canada, the paper examines how minorities are placed in the position of combatting socioeconomic and spatial inequalities, including displacement, on racial terms set by white elites.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it