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Record W3022084090 · doi:10.1007/s13753-020-00272-z

Barriers to Insurance as a Flood Risk Management Tool: Evidence from a Survey of Property Owners

2020· article· en· W3022084090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Disaster Risk Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsVancouver Coastal HealthUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFlood insuranceProperty insuranceFlood mythBusiness interruption insuranceBusinessActuarial sciencePurchasingCasualty insuranceGovernment (linguistics)Insurance policyInsurabilityRisk managementNatural hazardKey person insuranceFinanceGeneral insuranceIncome protection insuranceMarketingGeography

Abstract

fetched live from OpenAlex

Abstract By using risk-adjusted price signals to transfer responsibility for property-level flood protection and recovery from governments to property owners, flood insurance represents a key tenet of the flood risk management (FRM) paradigm. The Government of Canada has worked with insurers to introduce flood insurance for the first time as a part of a broader shift towards FRM to limit the growing costs of flooding. The viability of flood insurance in Canada, however, has been questioned by research that disputes the utility of purchasing coverage by property owners. This study tested this assumption by drawing on public opinion survey data to assess factors that influence decisions about the utility of insurance. The findings reveal that Canadians have limited knowledge of flood insurance coverage, exhibit a low willingness-to-pay for both insurance and property-level flood protection measures, and expect governments to shoulder much of the financial burden of flood recovery through disaster assistance.

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.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.044
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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