Planning for Commuters: An Evaluation of Transit Oriented Developments in the Greater Golden Horseshoe
Bibliographic record
Abstract
Urban sprawl has been at the forefront of the planning discussion for a long time, and rightfully so. It is an inefficient way of building out communities that only contribute to the autodependency that Canadians have. Transit-oriented developments (TOD) have been proposed as a way to combat urban sprawl by building communities that are compatible with high-order transit. The province of Ontario has made this way of building one of the key pillars in municipal growth through its Major Transit Station Areas (MTSA). Municipalities must conform to these provincial plans, so every municipality that is situated on a current or future GO rail line needs to build these communities. While there are policies that the province has provided, there are stark variations between municipalities when it comes to building these MTSAs. Furthermore, the province is using a one-type-fits-all approach to MTSAs, resulting in communities that do not complement the overall municipality or transit modes. In this paper, I explore these differences between municipalities for commuter TODs. A comparative case study of four different municipalities that are all building TODs around GO stations and all have high proportions of commuters. Mount Pleasant GO, Kitchener GO, Milton GO, and Whitby GO are used for this analysis. Within these case studies, a policy analysis, development review, and regression analysis using the Transportation Tomorrow Survey were completed to inform an evaluation of the sites. Each site is evaluated on three criteria: if it is a utopian TOD, a commuter TOD, and if it succeeds in the provincial policies. The findings are then used to inform policy recommendations for the future Caledon Station GO within Caledon and the province.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".