Planning for the First Mile & Last Mile in the Greater Toronto and Hamilton Area
Bibliographic record
Abstract
This paper brings together topics surrounding transportation planning issues and opportunities in the Greater Toronto and Hamilton Area. Using the concept of transit urban design around major transit station areas, I examine how to retrofit the existing urban form across multiple typologies to solve first-mile/last-mile transportation mobility challenges in suburban communities across the region. By undertaking a holistic and interdisciplinary approach towards retrofitting suburban communities, simple changes can make all the difference across a multitude of basic typologies. \nThe paper begins with review of the scholarly literature surrounding the themes connected to this topic. Beginning with a historical dive back two centuries, I examine the factors that led to the desire to create the first suburban environments away from cities. From here we explore the history of the automobile and suburban sprawl in Europe and America. Focusing on Toronto in the mid 20th century, I look at when planning changed course and abandoned the American model of city building in favour a new Toronto style, one which would save most of the downtown core. Following this, I unpack barriers to the built environment, the first-mile/lastmile dilemma in transportation planning, and what it means to retrofit suburbia and what that entails. Finally, we examine current land use issues around regional transit stations in the GTHA and identify the conditions requiring retrofits. \nI then turn to policy and break down the expectations from the Province of Ontario's Growth Plan for the Greater Golden Horseshoe, identifying Urban Growth Centres and major transit station areas within various typologies, as per the plan. Continuing the dive into policy, I uncover what the Provincial Policy Statement, Planning Act, and Greenbelt Plan all have to provide with regards to transportation planning and transportation infrastructure development. I then examine local policy in the City of Toronto's Official Plan and the Toronto Complete Street Design Guidelines. Following this I look at how cities and people take policy into action, examining the role and form of public consultation and its impacts. Then looking at the two Regional Transportation Plans, I examine what has been done, what is in progress and what is proposed in the region to help close transit gaps and create a well-connected network for the GTHA. \nUsing the Growth Plan's urban growth centres as key nodes, the retrofit of suburban environments across the region is broken down into three typologies: (1) greenfields, (2) autocentric superblocks, and (3) developed communities. The typologies are distinct as they interact with the urban environment in different ways, and require unique retrofit strategies in order to implement better transit urban design strategies. First, we look at "creating the blocks," then "changing the blocks" and finally "laying the blocks" of the urban environment. \nVarious themes related to transportation planning, urban design and mobility are connected to numerous challenges and benefits identified within the retrofit process for each typology. I examine issues around land ownership, costs, equity in decision making, safety, politics and public opinion. I also present opportunities in the form of transit-oriented development, redeveloping blocks, and alternative modes available through transportation demand management, in order to mitigate first-mile/last-mile issues and increase local to regional mobility across the region and between its nodes. I conclude that a holistic, interdisciplinary approach, considering numerous angles at once is required regardless of the context in question.
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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 | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".