Is there room for collective agency in a gentrifying city?: Planning for autonomous community space in Toronto
Bibliographic record
Abstract
The proliferation of gentrification in Toronto has been enabled by the city’s adoption of neoliberal urban development processes consistent with Toronto’s growing desire to compete with other global cities for the attention of global investors. The impacts of gentrification are far-reaching, with physical, economic, cultural, and social consequences associated with the increase in property values, rents, changes in commercial orientation, demographics, and neighbourhood class structure. As state sanctioned gentrification continues to take place across the city of Toronto, and terms such as “community benefits” are integrated into major neighbourhood revitalization projects by developers, this paper considers the implications that this change in urban development processes has for community-based organizations and their access to space, and the consequent implications for the autonomy of community based work. The high cost of real estate combined with the emphasis on service oriented third sector actors in the neoliberal city has resulted in increased pressures faced by community-based organizations to fit within the neoliberal valuation of the third sector, and higher property values or to face displacement and dissolution. This Major Paper examines the relationship between gentrification and access to space for community-based organizations in Toronto. The discussion presented here discusses the current neoliberal urban development context that is specific to the experiences of community-based organizations in Toronto’s gentrifying neighbourhoods, followed by a review of the main concerns and challenges raised by community-based organizations operating in these areas. By using a variety of methods including interviews, a survey and a focus group, the findings of this research project indicate that neoliberal urban development practices impact the ability of community-based organizations to access and maintain space for their communities while maintaining autonomy in regards to their activities and location. Without the ability to generate revenue to keep up with the real estate pressures of Toronto’s gentrifying neighbourhoods or to fit within the service-oriented systems of valuation of the third sector produced by neoliberal policies, the question arises as to how community-based organizations can continue to contribute to the development of Toronto’s community-focused social infrastructure. Findings indicate that the main challenges facing these organizations fall within four key categories: top-down planning processes, inequitable acquisition processes, dependence on underutilized space and of course, financial barriers. By reviewing these findings in relation to the context in which these organizations are operating, five recommendations are made in regards to current and proposed methods of creating autonomous spaces for community-based organizations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".