Shifting Shores and Perspectives: Making Room for the Sea and the Storm in False Creek Flats
Bibliographic record
Abstract
Coastal cities are grappling with how to shift their approach in designing the built environment to respond to global warming and sea level rise. With the potential increase of sea level rise by 1 metre by the year 2100, and climate change projecting more intense and frequent storms to British Columbia’s coasts, Vancouver will need to consider more resilient approaches to address flood risk along its shores. One area that will be exposed to flood risks includes the False Creek Flats, a historic tidal flat converted to rail and industrial hub in the core of the city, and on the cusp of transforming into the city’s next employment hub. At present, it is indiscernible that the False Creek Flats at one time was a historic tidal flat with a rich ecology supporting a variety of plants and wildlife, providing food and sustenance to the Indigenous people whose traditional territory included this land. The emergence of the rail and industry erased this history, the connection to the water, and the dynamic coastal processes that shaped the landscape. With the False Creek Flats undergoing a significant transformation over the next number of years, there is a window of opportunity to reconnect False Creek Flats to the coastal landscape, while also making room for flood waters and shifting perspectives on how we live with and build with water. This practicum seeks to develop a resilient design approach for False Creek Flats through three lenses: robustness, ensuring people are safe; adaptive, making room for the water; and transformative, shifting perspectives through design interventions. Leveraging the opportunity to make False Creek Flats resilient to climate change and flooding will benefit Vancouver by creating opportunities to shift public perspectives on how the city should adapt to sea level rise and climate change, while also bolstering public policy that will make the city and its residents more adaptive and resilient to change.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.015 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".