Lifting Up Downtown Understanding revitalization practices and processes in Mission and Chilliwack, British Columbia
Bibliographic record
Abstract
Downtowns are the metaphorical and geographical heart of a city. They play an important role in the city as a whole, serving as the locus of public gatherings and as a centre of economic activity. A vibrant and successful downtown is vital to the longevity and success of a city. However, over the last century, low-density urban development patterns have resulted in suburban sprawl, the spread of shopping malls, and increased reliance on the private automobile, leaving many downtowns in a state of decline and decay. This phenomenon has been particularity problematic for small and mid-sized downtowns. In response, hundreds of cities have attempted to reverse the fortunes of their cores by employing revitalization plans and policies. This research project examines how downtown revitalization occurs from the perspectives of stakeholders who are actively engaged in revitalization processes, using Mission and Chilliwack, British Columbia as case studies. The goal of this research is to identify the successes and shortcomings of Mission and Chilliwack’s revitalization endeavours and understand the reasons for them. Development in both cities continues to be more feasible and profitable outside the core and, to date, neither downtown strategy has been able to reverse this trend. Political strife surrounding the revitalization process in Mission and a perceived lack of safety associated with homelessness in Chilliwack have hampered revitalization efforts. Both municipalities understand the importance of public investment in revitalization and have recently begun investing millions of dollars into beautification and redevelopment projects in their downtowns. The findings from this research are used to compare the experiences of Mission and Chilliwack to one another and to formulate lessons and recommendations for the execution of similar projects in other cities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".