A Flood Tale of Two Cities: St. Catharines and London, ON
Bibliographic record
Abstract
The world's growing state of climate change has caused natural disasters to increase significantly. Flood disasters have risen in Ontario and require municipalities to implement flood-resilient measures to create a safer environment for their residents. This research follows a mixed methods approach to compare flood resiliency and determine if the Government of Ontario’s Five Flood Resilience Priorities are being implemented in St. Catharines and London. Four findings are highlighted: firstly, neither municipality satisfies the five flood resiliency priorities the provincial government set out. Secondly, St. Catharines is more vulnerable to flood disasters. Thirdly, London’s basement flooding program is executed exceptionally well compared to St. Catharine’s. The latter needs many improvements to create a more flood-resilient community. Lastly, homeowners in each municipality have varying perspectives on where responsibility for flooding lies. These findings show that, while both cities need to work towards improving their flood resiliency, St. Catharines needs additional improvements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".