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Record W2963319759 · doi:10.1108/ijdrbe-10-2018-0044

Choice of emergency shelter: valuing key attributes of emergency shelters

2019· article· en· W2963319759 on OpenAlexaffabout
Ali Asgary, Nooreddin Azimi

Bibliographic record

VenueInternational Journal of Disaster Resilience in the Built Environment · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsYork University
Fundersnot available
KeywordsSample (material)PopulationOriginalityBusinessEmergency managementGeographyMarketingTransport engineeringOperations managementPsychologyEngineeringMedicineEnvironmental healthSocial psychologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to examine people’s preferences for some of the key attributes of emergency shelters, including type, privacy level, location, spatial arrangement and pet-friendliness. Design/methodology/approach Choice experiment (CE) method was used in this study. A standard CE questionnaire was designed and completed by a sample of 293 residents of the Greater Toronto Area, Ontario (Canada), during the winter of 2015. Findings When using publicly provided shelters, people prefer to stay in hotels, places of worship and then community shelters, in that order. These findings correspond to the values that they place for various attributes through the CE survey. Findings show that responders place the highest values for emergency shelters that provide more privacy, located close to their home, and are pet friendly. Type of shelter and the “arrangement” attributes were not found to be as important and valuable. Research limitations/implications This study uses a convenient sampling method as such may not fully represent the study population. Practical implications Emergency shelter provision by local, regional and national governments cost significant amount of money and thus it is important that the society get the maximum benefit from it. This will be possible when users’ preferences are considered in planning, design, and operation of emergency shelters. The findings enable emergency managers to perform cost-benefit analysis an increase the efficiency of emergency shelters. Originality/value While previous studies have examined emergency-shelter types, characteristics and user-satisfaction levels, this is a novel study because it uses a choice experiment method to extract monetary values for key emergency-shelter attributes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.998

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.079
GPT teacher head0.276
Teacher spread0.197 · 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 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

Citations21
Published2019
Admission routes2
Has abstractyes

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