Derailing Toronto’s Industrial Legacy: Building Toronto into an Ideal Liveable City through Rail Deck Park
Bibliographic record
Abstract
In this last decade, the City of Toronto has introduced a number of new plans and projects aimed at creating a more ebullient, liveable urban fabric through reintroducing, revitalizing, and restoring nature within the city. Rail Deck Park, the development this Paper critiques, is but one of these projects that has been proposed with the intent of enhancing urban life by bringing nature back into the urban core. Sold on the promise that it will create a “more liveable Toronto for everyone”, this staggering twenty-one acres of proposed Park, at first glance, represents an important citybuilding moment. Yet, this Paper questions and exposes the potential dark side that lies beneath this seemingly moral city-building opportunity and the broader trajectory of building the ideal “liveable city” through mega-natures. At present, there is a growing body of work dedicated to illuminating the problematic sociopolitical and economic motives masked behind mega-nature developments, such as Rail Deck Park. This work suggests that while these nature projects appear to be “inherently good”, they are often mobilized to transform the urban landscape into one that ostensibly caters to the valorized drivers of the economy, known as the creative class. The commonness of these motives raises important questions about the authenticity and benevolence associated with Rail Deck Park and the “liveable city” vision it seeks to extend. Departing from these suspicions, in this Paper, I investigate the authenticity of Rail Deck Park by explicating the politics and planning behind its development. Theoretically, I draw upon political ecology, the global city research paradigm, and neo-Gramscian theories, to demonstrate how this project and the City’s “liveable city” vision are subsumed in the landscape of creative and competitive city-building. Particularly, when confronted with the logics of the market, neoliberal urbanism, and the City’s longstanding vision to build a more competitive Toronto, the authenticity of this development quickly unravels. Despite its promise of creating “liveability for everyone”, ii ultimately, I suggest that the Park is being built to create a more liveable city but only for the valorized drivers of the economy and those willing to buy into the product that is the city of Toronto.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".