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Record W7009870973

Flood risk perception in the Red River Basin, Manitoba : implications for hazard and disaster management

2005· dissertation· en· W7009870973 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2005
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsnot available
Fundersnot available
KeywordsFlood mythDelphi methodRisk perceptionHazardRisk managementPerceptionSample (material)Emergency managementRisk assessment
DOInot available

Abstract

fetched live from OpenAlex

A key element in hazard and disaster management is awareness of how stakeholders perceive risk. The primary goal of this study is to examine flood risk perception and its role in decision-making in relation to hazard and disaster management in the Red River Basin, Manitoba, Canada. The specific study objectives are to: 1) assess the nature of perceived risk at both the local and organizational levels; 2) determine if there is any variation between perceived risk among flood area residents and institutional experts; 3) identify various factors that influence perceptions of risk and decision-making processes at the local level; and 4) examine the variations in flood area residents' perceptions of risk and flood-related issues based on their geographical location. In order to achieve the objectives of the study, the research methods selected were qualitative in nature. A modified Delphi Process was utilized to solicit subjective, informed judgments from residents and decision makers in the basin. The Delphi Process involved two methods: 1) face-to-face interviews, and 2) a two-round mail-out Delphi survey. A sample (non-representative) of 42 respondents was divided into two separate groups, Flood Area Residents and Institutional Representatives. Flood Area Residents were divided into Winnipeg (urban) and South (rural) respondents and Institutional Representatives were divided into Senior, Local, and Non-Government respondents. The study findings established that while an element of variation in perceived risk between flood area residents and institutional experts does exist, it is not as significant as postulated in the literature. Residents' perceptions were based on subjective factors, but many exhibited a general awareness of objective risk. Perceptions of institutional experts responsible for managing risk involved some degree of value judgments and an element of subjectivity as well. The gap that did appear to exist between the two groups was associated with a lack of understanding and communication. The study findings also indicated that a number of factors have influenced residents' perceptions of risk. The most notable factors were the geographical location of Winnipeg and South respondents and the influence of large-scale structural mitigation measures. Other influencing factors identified were: past flood experience, uncertainty, and visual presentation of the flood. The research exemplified that the inclusion of perceptions of risk is pivotal to decision-making processes. For example, a lack of communication to residents regarding policy changes to evacuation procedures since 1997 could have considerable implications for future flood response (i.e. public opposition). Within the City of Winnipeg the reduction in physical risk and sense of security afforded by the Floodway has attenuated the perceptions of risk of some respondents and potentially made them more vulnerable to extreme flood events. The Floodway Expansion project may exacerbate this situation by increasing the level of physical protection. In addition, past flood experience heightened the awareness of some respondents and will serve as the context for future perceptions; uncertainty amplified risk-related anxiety for some respondents and could potentially increase stress in future floods; and visual presentation of the flood heightened perceptions of risk for some respondents and in some cases also influenced behaviour. With an enhanced understanding of risk perception, institutional experts and decision makers will be better able to establish and implement proactive mitigation and preparedness strategies that are sustainable and improve resiliency. One of the keys to this inclusion is a two-way communication process that involves learning on both sides.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.215
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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