“We're not just about building subdivisions. We can also do good things for the world”: Private Developers and Active Transportation Implementation in the Region of Waterloo
Bibliographic record
Abstract
Since the mid-19th century, Canada’s population has become more urbanized as Canadians choose to live in one of its major urban centres, such as the Region of Waterloo. As this trend continues into the 21st century, increased demands have been placed on urban transportation infrastructure and services. Development patterns in Canadian cities have been predominately car-oriented creating negative health impacts for citizens and hindering climate action goals. Active transportation, such as walking and bicycling, has been promoted as a way to improve public health and reduce greenhouse gas emissions. Support for active transportation planning exists in current provincial, regional, and local planning policies. Private developers are an important part of transforming these policies into the built environment. However, previous research has shown that translating policies to practice has encountered barriers including processes that have not evolved to meet demands. Additionally, the role of private developers in implementing active transportation policies and collaboration methods between the public and private sectors remains a gap in current research. The purpose of this study was to explore the role private developers play in achieving the goals of the Region of Waterloo’s active transportation plans. An explanatory qualitative study design was chosen to explore the current planning framework and gather information through the use of document analysis and 17 key informant interviews from both the public and private sectors. The results show that there are four main barriers for private developers in achieving active transportation goals: excessive vehicle parking requirements, the lack of measures of success, the integration of active transportation initiatives into policy, and the limited methods of collaboration between the public and private sectors. This study presents recommendations to reduce or remove these barriers that can be applied by the Region of Waterloo and/or private developers to facilitate improved implementation of active transportation plans. Although focused on the Region of Waterloo, this research can be applied by planners in other Ontario municipalities to improve active transportation networks and contributes to the body of knowledge on the relationship between the public and private sectors in planning.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".