Values and floodplain management: Case studies from the Red River Basin, Canada
Bibliographic record
Abstract
Abstract Where floods are prevalent, decisions on how to mitigate vulnerability are made within a social-cultural context that includes values (and related customs, norms, beliefs, technology) of local people, which have evolved through interactions with the physical environment. Consequently, the success of floodplain management and flood mitigation activities is determined, at least in part, by the nature of values that impact the decision-making process. This paper explores this contention by considering the community values context surrounding flood risk management in two small Canadian communities in the Red River Basin. Using a qualitative methodology that includes semi-structured interviews with residents, community values are identified and accounted for in the context of flood vulnerability. Values discussions are organized around seven broad categories: community identity and community attributes; community economic development; technical and nonstructural approaches; civic engagement; flood legacy; personal rights and liberties; and shared values. Challenges posed by key identified values and their policy implications are considered. Some values are found to act as constraints if sustainable floodplain management practices are to be realized.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".