<scp>SPORT</scp> ‐ <scp>RELATED GENTRIFICATION</scp> : Behind the Spectacle of Settler Colonial Urbanism
Bibliographic record
Abstract
Abstract Urban studies scholars and sociologists of sport have critically examined the production and consumption of world‐class sports spectacles that are constitutive elements of urban growth agendas and broader accumulation processes by dispossession. This multi‐year community‐based research project goes behind the spectacle, exploring the uneven impacts of Rogers Place, a $613.7 million (CAD), publicly financed hockey arena and its associated entertainment district on city‐centre communities in Edmonton, Alberta—an area with a sizeable Indigenous urban street community. In doing so, we bring together critical sport and urban geography scholarship and work by Indigenous Studies scholars who have examined how Indigenous peoples in Western Canadian Prairie cities navigate the white possessive logics of settler colonial urbanism and the state‐sponsored gentrification of their communities and land. Our analysis challenges common‐sense ideas about the community‐wide benefits of sport‐related gentrification and pervasive beliefs that settler colonialism is an event of the past that occurred entirely outside of cities. We also highlight the aspirations of city‐centre residents to continue living in their shared urban homespaces and to collectively envision other futures that are neither based on the violent practices of sport‐driven gentrification nor its associated forms of genocidal inclusion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| 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".