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dc.contributor.advisorJarrod Goentzel.en_US
dc.contributor.authorBann, Gabriel(Gabriel T.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Institute for Data, Systems, and Society.en_US
dc.contributor.otherTechnology and Policy Program.en_US
dc.date.accessioned2021-01-06T17:38:36Z
dc.date.available2021-01-06T17:38:36Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/129077
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, September, 2020en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 57-58).en_US
dc.description.abstractNatural disasters such as hurricanes, floods, and wildfires have been increasing both in frequency and in the cost of damages. Different communities experience disasters differently, from the immediate losses to the long-term recovery process. Age, disability, race, housing status, and socioeconomic status are factors that can contribute to disparities in a person or community's vulnerability to disasters. Federal disaster aid policy has historically contributed to disaster vulnerability as well, at times enhancing disparities in survivors' ability to respond or recover. The Federal Emergency Management Agency (FEMA) has recently significantly expanded its efforts to individualize the survivor experience, and especially consider the survivor's social vulnerability. We received a large dataset with outcomes for Individual Assistance (IA) programs for registrants in eight different natural disasters from 2008-2017. My research has been to analyze these outcomes in order to explore potential disparities in the survivor experience based on demographic characteristics at the individual and community levels. This document covers my exploration of this data set in the context of social vulnerability. I employ high-level descriptive statistics as well as multi-level modeling techniques to depict the relationship between demographic variables associated with social vulnerability and outcomes in IA programs. Through these modeling techniques, I find that many individual and community-level demographic variables are strongly correlated with FEMA assistance outcomes including assistance amount and the number of contacts between the registrant and FEMA. Finally, I outline significant disparities in assistance levels for different demographic groups.en_US
dc.description.statementofresponsibilityby Gabriel Bann.en_US
dc.format.extent58 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleAn analysis of outcomes for FEMA individual assistance recipients in the context of social vulnerabilityen_US
dc.title.alternativeAnalysis of outcomes for Federal Emergency Management Agency individual assistance recipients in the context of social vulnerabilityen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.departmentTechnology and Policy Programen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc1227201492en_US
dc.description.collectionS.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Programen_US
dspace.imported2021-01-06T17:38:33Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentTPPen_US
mit.thesis.departmentESDen_US
mit.thesis.departmentIDSSen_US


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