Public Involvement in Flood Management in the Red River Basin: An Assessment of a Recent Initiative
Bibliographic record
Abstract
The success of flood planning and management relies at least partially on effective and fair public involvement. In this paper we examine a recent initiative in Canada’s Red River basin, centreing on two alternatives for structural adjustments: a $660 million expansion of the Red River Floodway and a $543 million system of dykes and diversion channels near the Town of Ste. Agathe, 24 km upstream of Winnipeg. The first part of the paper provides background on flooding in the Red River basin. The next describes the public involvement process used in the planning and management initiative, and the third evaluates the process. The evaluation is both grounded in criteria defined by research participants and based on an assessment framework derived from the public involvement literature. The methodology was qualitative, interactive and adaptive, and included a group interview, participant observation, semi-structured interviews and a review of documents. The results suggest that key publics had limited influence in decision processes leading to the preparation of the main report detailing the two alternatives. Further, most research participants would have preferred earlier public involvement, i.e., before basic decisions about the two options had been made. There were mixed reviews of public meetings run by the Manitoba Clean Environment Commission, and several research participants called for greater use of interactive, deliberative mechanisms, such as workshops, round tables and mediation. Finally, a strong theme in the issues raised by participants was that the scope of the options report, namely Flood Protection Studies for Winnipeg, was too narrow. A recasting of the public involvement process would likely have broadened the scope to encompass a basin-wide perspective.
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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 | 0.043 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".