Transportation-led Redevelopment And Affordability Along The Eglinton Avenue Lrt Line, Toronto.
Bibliographic record
Abstract
New rapid transit lines have been demonstrated to increase access and enhance equity and social inclusivity in cities. However fixed transit infrastructure improvements have also been shown to lift property values, decrease affordability, and lead to displacement and community homogenization in areas adjacent to its construction. The following case study examines this often overlooked relationship between enhanced mobility and reduced affordability in the context of Ontario's largest single infrastructure project, the Eglinton Crosstown Light Rail Transit (LRT). \nThe case study first looks at the history of rapid transit infrastructure in Toronto and the role of provincial transit agency Metrolinx and their stated goals in the development of new transit. The case study area, a 2.1km stretch of Eglinton Avenue West is subsequently examined, detailing the neighbourhood's history, demographic makeup and existing affordability conditions. The implications of new transit development in the study area to date and in the future are considered. Parties likely to gain the most from the Crosstown LRT such as the development and real estate firms are discussed in context to those most at risk of losing out, tenanted business and residents. Reggae Lane, a local project in the case study area conceived in recognition of the changes to come, is discussed by way of interviews with the local councillor who proposed the project as well as the founder of Canadian Reggae World and active participant in the project. Finally the paper offers up a series of policy recommendations that could prove beneficial in preventing transit land displacement and towards create positive outcomes for neighbourhood affordability.
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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 | 0.000 | 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 | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".