Function, Process, and Change: Designing Flood Infrastructure to Protect Calgary's Vulnerable Communities
Bibliographic record
Abstract
This chapter discusses the evolving role of infrastructure in the face of climate change&s;s impact on cities and landscapes. Infrastructure goes beyond traditional services, encompassing ecological networks that support urban well-being. Public spaces and landscapes play a crucial role by providing ecosystem services, including clean water, fresh air, and access to nature. Open space networks are increasingly recognized as vital assets in addressing climate challenges such as greenhouse gas reduction, flood protection, and urban heat management. Parks are evolving into multi-functional landscapes, integrating natural diversity with pathways and infrastructure for stormwater management. This chapter looks into the case of Calgary, Alberta, which faces climate-related risks like flooding and drought. The city&s;s open space network, with its extensive riverfront pathways, is essential for both recreation and flood protection. The need for flood barriers became evident after a major 2013 flood, prompting innovative design solutions that integrated flood protection with urban amenities. Communication and engagement were pivotal in gaining public acceptance for these changes. Visual toolkits, terrain analysis, and virtual reality tools helped convey the necessity and design of flood barriers. The chapter highlights the difference in public acceptance between projects on public versus private land and underscores the importance of transparent communication in managing change. The projects highlighted in this chapter demonstrate how cities adapt to changing climates while preserving beloved urban landscapes, emphasizing the critical role of effective communication in achieving resilient and multi-functional urban environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".