Emergent Social Vulnerability: Linking Hazards of Place to Individual Vulnerabilities

Authors: Joseph Tuccillo*, University of Colorado, Boulder, Seth Spielman, University of Colorado-Boulder
Topics: Hazards and Vulnerability, Hazards, Risks, and Disasters, Population Geography
Keywords: vulnerability, hazards, population, census, microdata
Session Type: Paper
Day: 4/13/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Napoleon B3, Sheraton 3rd Floor
Presentation File: No File Uploaded

Within the spatial sciences, social vulnerability--or the potential for individuals, groups, or households to be harmed by a hazard event or disturbance--is often viewed as a place based construct. It is assumed that the vulnerability of places (neighborhoods, cities) can be measured through aggregate characteristics linked to socioeconomic hardship. Yet measures of social vulnerability constructed from aggregate data mask understanding of how individuals are themselves vulnerable. While there is ample evidence that different places have different levels of social vulnerability, without attention to individual context, it is not at all clear how to efficiently translate aggregate-level vulnerability metrics into policy or operational response. We argue that social vulnerability emerges from the social interactive properties of place. If one could understand vulnerability from an individual level, one could craft policies that address the specific vulnerabilities of the people in a place whilst still accounting for the collective (area-level) concerns. Moreover, viewing vulnerability as an emergent construct allows us to target vulnerable individuals within affluent (less vulnerable) places. In this paper we develop a new way of thinking about vulnerability based on measuring vulnerability at the individual level (using survey responses from the US Census), statistically geo-locating individuals to census tracts, then ranking tracts based on their composition of vulnerable individuals. Two test cases for Denver, Colorado and New York City are evaluated. We believe this method is a significant theoretical and methodological advance that enables new ways of incorporating data-intensive science into policy making and public sector operations.

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