Investigating the Eglinton LRT Crosstown: Understanding the Impact of Transit Oriented Development on Racialized Communities in Flemingdon Park
Bibliographic record
Abstract
Over the recent years, we have seen Transit Oriented Developments (TODs) expansion in the development and construction phase across Toronto. TODs are near existing and newly constructed transit lines like the Eglinton Crosstown LRT East. Although the construction of TODs is highly encouraged amongst policymakers, developers, and planners to curb urban sprawl and a means of building more dense, sustainable, and accessible communities that would see residents utilizing public transportation in their daily lives, there has not been an indepth analysis on the wide-ranging effects of such transit-related projects on neighbouring communities such as Flemingdon Park. Several relatively old apartment buildings with social housing projects (Toronto Community Housing) are close to the newly built Science Center Station (Eglinton Crosstown LRT). Issues arise when landlords and property managers see the significant investment in transit projects as an opportunity to increase rent and turn what has traditionally been a relatively affordable area into a means of collecting massive profits. \nIn this research paper, I outline Flemingdon Park's development to understand the community's history and what it looks like currently with the construction of TODs and the LRT. Then I look at Transit Oriented Developments and Affordable Housing, specifically delving into the case of 31-35 St. Dennis Drive, apartment building to understand the issues that tenants are facing, such as renoviction, above-guideline rent increases and what has since pushed them to fight back and organize a rent strike. The paper concludes by examining the role of community-based participatory planning and how citizen control and power can open pathways to meaningful engagement within urban planning processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".