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Record W1965366468 · doi:10.1071/wf10096

Complexity of homeowner wildfire risk mitigation: an integration of hazard theories

2011· article· en· W1965366468 on OpenAlexafffundabout
Bonita L. McFarlane, Tara K. McGee, Hilary Faulkner

Bibliographic record

VenueInternational Journal of Wildland Fire · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of AlbertaNatural Resources CanadaCanadian Forest Service
FundersSocial Sciences and Humanities Research Council of CanadaInstitute for Catastrophic Loss Reduction
KeywordsBusinessHazardDisaster mitigationEnvironmental planningRisk managementEnvironmental resource managementWildland–urban interfaceSocial connectednessEnvironmental sciencePsychologyFinance

Abstract

fetched live from OpenAlex

Each year wildfire affects communities in Canada, resulting in evacuations and, in some cases, loss of homes. Several Canadian wildfire management agencies have initiated mitigation programs aimed at reducing wildfire risk. Successful wildfire mitigation involves both community-level and homeowner action. This paper examines factors that influence wildfire mitigation by homeowners. We draw upon the general hazards and wildfire management literature to develop and test a theoretical model for homeowner wildfire mitigation that includes perceived risk, an evaluation of threat significance and the influence of perceived costs and benefits of mitigation. We used a mail survey to collect data from 1265 residents in six interface communities in the province of Alberta. Results showed a high level of completion for most mitigation activities. A structural equation model provided support for the hypothesis that the evaluation of threat involves weighing the negative effects of mitigation on homeowners’ feelings of connectedness to nature and the cost of mitigation with the positive influences of fear, a sense of responsibility and perceived effectiveness of mitigation. Considering the total effects, threat assessment had the greatest effect on mitigation by homeowners, followed by perceived effectiveness of mitigation in reducing damage and not having financial resources for mitigation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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 teacher head, 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

Citations133
Published2011
Admission routes3
Has abstractyes

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