“It’s Just Gravel”: The Logic of Elimination in Edmonton’s Downtown Revitalization
Bibliographic record
Abstract
Edmonton’s burgeoning “Ice District" has been a frosty source of contention in the city. But criticism of the Ice District — which has ranged from its name to its funding — has hardly addressed the project’s positioning in a larger event of settler colonialism. By analyzing recent news coverage and an interview with a stakeholder in Edmonton’s urban development, I argue that the city’s downtown revitalization disregards urban aboriginal sovereignty. I find that Edmonton’s downtown core is a uniquely aboriginal space, with nearly 50 per cent of Edmonton’s urban homeless population being aboriginal-identified, while aboriginal peoples only constitute less than 6 per cent of the greater Edmonton population. In conjunction with language seeking to “cleanse” the area of perceived danger and imprint capitalist productivity in an “empty” area, I conclude that Edmonton's downtown revitalization project operates as a settler colonialist function to eliminate urban indigenous populations. I position this argument within a greater conversation of indigenous sovereignties in Canada: how can the urban indigenous population in Edmonton be self-sustaining — let alone sovereign — when the very land they reside is under constant siege by a competing municipality?
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".