Community BIAs as Practices of Assemblage: Contingent Politics in the Neoliberal City
Bibliographic record
Abstract
Business Improvement Areas (BIAs) are a domain of urban governance that has been aptly characterized as a form of neoliberal urbanization aimed at improving the business climate of downtowns. This paper engages with a growing body of literature on contingent neoliberal urbanisms to consider BIAs as an assemblage of coevolving projects and actors. It focuses specifically on two ‘community’ BIAs in Toronto's downtown West, where recent actions of differently positioned stakeholders effectively reveal how multiple agendas can inform BIA practices. Our objective is twofold: (a) to draw attention to the practices of smaller, community-based BIAs that predominate in North America; and (b) to explore the analytical and political openings that arise when institutions commonly identified as neoliberal are investigated as an assemblage of related but distinctive and sometimes disjunctive projects.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.054 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".