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Record W3190900862 · doi:10.24815/ijdm.v4i2.21183

Are We Prepared for the Next Disaster? Evidence from Ice Storm

2021· article· en· W3190900862 on OpenAlexaffabout
Ali Asgary, Ali Vaezi, Nooreddin Azimi

Bibliographic record

VenueInternational Journal of Disaster Management/International journal of disaster management/Smong News · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsBrock UniversityYork University
Fundersnot available
KeywordsPreparednessStormEmergency managementMeteorologyPsychologyBusinessPolitical scienceGeography

Abstract

fetched live from OpenAlex

This study examines the impacts that an emergency had on people’s preparedness levels, using the December 2013 Ice Storm in the Greater Toronto Area (GTA) as a case. A questionnaire consisting of three sections was developed to measure the associated impacts, people’s reactions/opinions, as well as their preparedness levels before and after the ice storm. The goal of the research is not only to discuss the factors that influenced people’s ability to prepare, respond to and recover from the ice storm but also to generate useful insights for future disasters that are similar in nature. Our analysis includes various aspects such as the effectiveness of advance warnings and their ability to disseminate information to mass audiences. The findings show that, most of the respondents believe that they learned a lot about ice storms and their impacts because of their prior experience; a significant majority believe that it is the city’s/municipality’s responsibility to prepare for emergencies like ice storms; home ownership was significantly associated with the previous ice storm preparedness; and, power outage experience was significantly associated with the next ice storm preparedness.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.005
Open science0.0070.002
Research integrity0.0000.001
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 head0.069
GPT teacher head0.354
Teacher spread0.284 · 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.

Study designNot applicable
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

Citations3
Published2021
Admission routes2
Has abstractyes

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