Adaptive reuse in a declining city: altering the Station Mall on the Sault Ste. Marie Waterfront
Bibliographic record
Abstract
This Thesis takes a closer look at my hometown of Sault Ste. Marie, ON. I have found that overall this industrial city has been in a decline or dying over the past decade or longer. The differences when compared to the decline of other industrial cities is that the industry backbone of Sault Ste. Marie is currently thriving. This decline is stressed by an aging community, lack of available work, and continuous emigration of younger generations. This has led to a stagnant economy, degradation of infrastructure, and rise of criminal culture throughout the city. Nowhere else is this more evident than in the downtown core of Sault Ste. Marie Within this thesis, I look towards the efficient use of our existing built environment; focusing on adaptive reuse on multiple scales, from existing architectural structures to sites and reintroducing it to the social urban environment of the community. Taking this opportunity to research how to work with these spaces architecturally, programmatically and urbanistically, I am making the effort to effectively revitalize these declining rough areas or neighbourhoods. This topic stems from a belief in the importance of taking a sustainable approach to an existing building’s embodied energy, while also mitigating urban sprawl. Meanwhile, recognizing that the re-use of existing buildings or spaces allows for the chance of preserving (rediscovering) history, emotion, and atmosphere while introducing new programs to these spaces. The question that is explored within this thesis is whether the revitalization of a historical centerpiece within a city that is in a state of decline can have enough of an impact to stabilize the surrounding community. Throughout the growth of medium sized cities there develops a phenomenon known as ‘doughnut cities’. This happens when a city continues to expand outwards and less focus is placed on the center or downtown leading to the death or decline of said area. In addition to this, there is also precedent for the death or decline of single industry cities. These cities tend to fall into decline when the main industry takes a downturn; resulting in effects to job availability and the local economy. Both of these phenomena look as though to play a part in the situation Sault Ste. Marie finds itself in currently. The proposed project looks at redesigning and reprogramming the Station Mall and Downtown Waterfront site in Sault Ste. Marie. Over the years, projects reprogramming existing historical buildings have had positive impact on their surrounding sites and the community. Although, the city’s downtown and predominantly this site has suffered a gradual abandonment and decline, through this research project I believe a positive change can be made for the city and its community. This thesis explores these topics and questions through extensive research in addition to a methodology focusing on the use of mapping and layering to progress through the project. From historical mapping to current site analysis; working at multiple scales from city, to neighbourhoods, to the building. Taking a layered approach to fully understand the historical and situational basis within the project and transition into the final design proposition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".