Flood risk management and shared responsibility: Exploring Canadian public attitudes and expectations
Bibliographic record
Abstract
One of the central tenets of the flood risk management (FRM) paradigm is that responsibility for flood mitigation and recovery must be shared with stakeholders other than governments, including property‐owners themselves. However, existing research suggests that this imperative is unlikely to be effective unless property‐owners demonstrate a sense of personal responsibility and are willing to undertake protective behaviours. In Canada, several recent policy changes have effectively transferred more responsibility to homeowners, but it is unclear whether Canadians are ready to accept this obligation. This article presents results from a national survey of Canadians living in high‐risk flood areas, which probed their attitudes concerning the division of responsibility for flood mitigation and recovery among governments, insurers and homeowners, as well as their willingness to adopt protective behaviours. The survey, which received 2,300 responses from all 10 provinces, indicates that Canadians are willing to accept some responsibility, but for most this perceived responsibility is insufficient to influence their decisions on mitigation and recovery. Governments in Canada could learn from jurisdictions that have addressed this disconnect through policies designed to improve awareness of FRM among property‐owners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".