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This chapter provides the foundation for the book. The objective of this chapter is to outline the theme of the book and to provide the context for the chapters that follow. Disaster recovery is a challenge for governments and for affected communities, families, and individuals. It is a challenge, because recovery from catastrophic disasters can be much more complicated and elusive than what can be addressed by national and international aid organizations given the time and other resources. The short literature review provides the research context, and the overview of the book describes each of the chapters briefly.

Disasters shape the development of communities and societies not only physically but also socially. This chapter provides some quantitative evidence to this effect by examining changes in social capital in communities affected by the 2008 Wenchuan Earthquake in China.

A two-wave, longitudinal household questionnaire survey data set was used for analysis. The baseline data were obtained in January, 2009, around 8 months after the 2008 Wenchuan Earthquake, adopting a stratified sampling method within a county severely disrupted by the earthquake. A ­follow-up survey with the same households was conducted in the summer of 2012. Finally, 415 household questionnaire surveys from nine communities within the county were collected for analysis.

Overall, it can be concluded that social capital was strengthened in the post-disaster recovery process in the survey area. Social capital was measured according to three dimensions: (1) affiliation with organizations, (2) the degree of available social support, and (3) the degree of social cohesion within communities. It was found that the average degree of social capital increased during the recovery process, with a decrease of social capital inequalities between different families. More specifically, although informal personal networks were found to be the most prominent sources of social support, the support provided by formal organizations played a relatively more important role immediately after the catastrophe, given that most of the personal networks were also affected. Community cohesion was also found to have increased, with a decrease of standard deviation in the recovery process. This chapter suggests that disasters could generate positive effects rather than negative ones alone. Stronger and more tightly knit communities could be built in the disaster recovery process, if appropriate policies and methods are implemented.

This comparative study qualitatively explores how linguistic minority immigrants and refugees experienced the 2010–2011 Canterbury and Tohoku disasters, including their coping mechanisms and their perceived vulnerabilities and resilience. The data used for this qualitative analysis was primarily drawn from 28 in-depth interviews with linguistic minority immigrants and refugees and their supporting organization staff conducted in 2015–2016. Additional material was drawn from two publicly available data sets. Immigrants and refugees are typically thought of as being more vulnerable in disasters. However, findings drawn from this research demonstrate the nonlinearity, complexity, and contextuality of social vulnerabilities in disasters, suggesting that they are not necessarily powerless help-seekers in some cases. Using Bourdieu’s capital theory, this study demonstrates how immigrants and refugees were active social agents in these disasters. Consequently, we need to reconceptualize the social vulnerability approach. Some study participants had experiences of going through wars and everyday disasters, which made them more resilient. This is conceptualized here as earned strength, which can be a significant resource in disasters for the socially vulnerable. This chapter hopes to answer some critical questions regarding the social vulnerability approach: how do we incorporate the structure–agency concept, how do we theoretically deal with the contextuality/nonlinearity of social vulnerability in disasters, and how do we conceptualize a research study that can seek more practical and generalizable findings, instead of event-driven and disaster-specific findings?