Regional Planning and Urban Revitalization in Mid-Sized Cities: A Case Study on Downtown Guelph
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With over a decade having passed since the inception of the provincially led growth plan in Ontario, there is an opportunity to explore how cities have adapted to meet the challenges of this regional-scale plan. The Growth Plan for the Greater Golden Horseshoe seeks to mitigate the negative eff ects of decades of sprawling development by focusing on building dense, urban, transit-connected communities. While the growth plan has a primary focus on municipalities in the Greater Toronto Area, it is also inclusive of smaller urban centres that sit outside of the province’s Greenbelt. Th ese mid-sized cities have a history of downtown decline and dispersed urban form. With the inclusion of mid-sized cities in the growth plan, however, there is an opportunity to explore the strategies smaller municipalities are using to attract public and private investment and achieve residential and employment provincial targets in their core areas by 2041. Th rough a case study approach, focused on downtown Guelph, Ontario, this paper argues that the growth plan can serve as a catalyst to alter the planning paradigm in mid-sized cities, and that through locally led community planning efforts, and a range of site-specific incentives, mid-sized cities can begin to revitalize their downtowns and reverse core area decline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it