Bibliographic record
Abstract
In the time of globalization, many cities, including the city of Victoria in BC, have engaged in a development model fueled by investment, tourism, and economic immigration. This model requires public authorities to implement policies that contribute to making cities worthy of capital, tourists, and immigrants. Digital connectivity, real estate development, local amenities, and revitalized neighbourhoods are essential ingredients for economic development. In contrast, poverty and urban decay are not good for the way of life that politicians, entrepreneurs, tourists, and urbanites desire. Therefore, all visual manifestations of urban decay, including homelessness, should be restricted by law. In response to this development model, homeless people are forced to perform actions that are banned like building tent cities in parks. In doing so, homeless people challenge exclusionary legal and spatial orderings that support anti-homeless cities. This paper develops a performativity-based approach to legal geography to contribute to the debate about homelessness in Canada. Rather than focusing on the social right to housing, my argument in this paper zeroes in on the right to use urban space without being excluded. To this goal, I explore interactions between local authorities, homeless people, and other social actors in Victoria to explain that reiterated human interaction is the means to perform and rectify legal and spatial orderings that segregate homeless people. Thus, the performativity-based approach to legal geography developed throughout this paper illustrates not only how anti-homeless cities are socially performed, but also how they are collectively contested.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.041 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".