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      Revealing hazard-exposure heterophily as a latent characteristic of community resilience in social-spatial networks

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      Scientific Reports
      Nature Publishing Group UK
      Natural hazards, Environmental social sciences

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          Abstract

          We present a latent characteristic in socio-spatial networks, hazard-exposure heterophily, to capture the extent to which populations with dissimilar hazard exposure could assist each other through social ties. Heterophily is the tendency of unlike individuals to form social ties. Conversely, populations in hazard-prone spatial areas with significant hazard-exposure similarity, homophily, would lack sufficient resourcefulness to aid each other to lessen the impact of hazards. In the context of the Houston metropolitan area, we use Meta’s Social Connectedness data to construct a socio-spatial network in juxtaposition with flood exposure data from National Flood Hazard Layer to analyze flood hazard exposure of spatial areas. The results reveal the extent and spatial variation of hazard-exposure heterophily in the study area. Notably, the results show that lower-income areas have lower hazard-exposure heterophily possibly caused by income segregation and the tendency of affordable housing development to be located in flood zones. Less resourceful social ties in hazard-prone areas due to their high-hazard-exposure homophily may inhibit low-income areas from better coping with hazard impacts and could contribute to their slower recovery. Overall, the results underscore the significance of characterizing hazard-exposure heterophily in socio-spatial networks to reveal community vulnerability and resilience to hazards.

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          Most cited references36

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          Social Vulnerability to Environmental Hazards*

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            Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness.

            Communities have the potential to function effectively and adapt successfully in the aftermath of disasters. Drawing upon literatures in several disciplines, we present a theory of resilience that encompasses contemporary understandings of stress, adaptation, wellness, and resource dynamics. Community resilience is a process linking a network of adaptive capacities (resources with dynamic attributes) to adaptation after a disturbance or adversity. Community adaptation is manifest in population wellness, defined as high and non-disparate levels of mental and behavioral health, functioning, and quality of life. Community resilience emerges from four primary sets of adaptive capacities--Economic Development, Social Capital, Information and Communication, and Community Competence--that together provide a strategy for disaster readiness. To build collective resilience, communities must reduce risk and resource inequities, engage local people in mitigation, create organizational linkages, boost and protect social supports, and plan for not having a plan, which requires flexibility, decision-making skills, and trusted sources of information that function in the face of unknowns.
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              A place-based model for understanding community resilience to natural disasters

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                Author and article information

                Contributors
                joeyliu0324@tamu.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                24 March 2023
                24 March 2023
                2023
                : 13
                : 4817
                Affiliations
                GRID grid.264756.4, ISNI 0000 0004 4687 2082, Zachry Department of Civil and Environmental Engineering, , Texas A&M University, ; 199 Spence St., College Station, TX 77843-3136 USA
                Article
                31702
                10.1038/s41598-023-31702-9
                10039027
                36964245
                adcbfeb5-f429-4c46-879e-e3ccf18ba48c
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 May 2022
                : 16 March 2023
                Funding
                Funded by: National Science Foundation CAREER Award
                Award ID: 1846069
                Award ID: 1846069
                Award Recipient :
                Categories
                Article
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                © The Author(s) 2023

                Uncategorized
                natural hazards,environmental social sciences
                Uncategorized
                natural hazards, environmental social sciences

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