Flood risk mapping in southwestern Nova Scotia: Perceptions and concerns
Bibliographic record
Abstract
Abstract Flood risk mapping allows for informed decision making regarding personal and community planning. Resistance to flood risk mapping can be driven by potential decline of property values. This paper explores resistance to flood risk mapping through the lens of climax thinking. Climax thinking is a novel theory guiding explorations of resistance to proposed land use changes. The aim of this study was to understand flood experiences, the presence of resistance to flood risk mapping, and whether climax thinking could help explain this resistance. To address this, surveys were administered to residents in the Nova Scotian towns of Liverpool and Bridgewater. We found that one third of respondents have experienced flooding, yet the majority have not seen a flood risk map, nor were they concerned about the potential impacts of flooding. Only one sixth of respondents exhibited resistance to flood risk mapping because of potential loss to property value. Dimensions of climax thinking were predictive of this resistance, specifically ignorance of an individual's own ability to adapt and inability to recognize the impact of their adaptation decisions on others, which together quadrupled the predictive power of the ordinal regression model. These insights can be applied to support the acceptance of flood risk mapping .
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".