Building Resilience

Social Capital in Post-Disaster Recovery

Daniel P. Aldrich

• Publisher: University of Chicago Press
• Year: 2012
• ISBN:
  9780226012896
• Topic: Politics & International Relations
• Subtopic: Politics
• Index: Politics & International Relations

Each year, natural disasters threaten the strength and stability of communities worldwide. Yet responses to the challenges of recovery vary greatly and in ways that aren't explained by the magnitude of the catastrophe or the amount of aid provided by national governments or the international community. The difference between resilience and disrepair, as Daniel P. Aldrich shows, lies in the depth of communities' social capital. Building Resilience highlights the critical role of social capital in the ability of a community to withstand disaster and rebuild both the infrastructure and the ties that are at the foundation of any community. Aldrich examines the post-disaster responses of four distinct communities—Tokyo following the 1923 earthquake, Kobe after the 1995 earthquake, Tamil Nadu after the 2004 Indian Ocean Tsunami, and New Orleans post-Katrina—and finds that those with robust social networks were better able to coordinate recovery. In addition to quickly disseminating information and financial and physical assistance, communities with an abundance of social capital were able to minimize the migration of people and valuable resources out of the area. With governments increasingly overstretched and natural disasters likely to increase in frequency and intensity, a thorough understanding of what contributes to efficient reconstruction is more important than ever. Building Resilience underscores a critical component of an effective response.

1

Social Capital: Its Role in Post-Disaster Recovery

Within two years of Hurricane Katrina, the neighborhood of Mary Queen of Vietnam within Village de L’Est in the northeast corner of New Orleans had rebuilt many of its heavily damaged homes and restored most of its shops. Census tract data from the year 2000 show that income in the area was lower than the state and national averages, and there is no evidence that government agencies provided special assistance to local residents after the flooding (author interviews, 2010). Yet two years after the levees broke, while much of the rest of the city stood empty, surveys reported a 90 percent repopulation rate and a 90 percent business recovery rate in this section of the Big Easy (LaRose 2006; Faciane 2007). More than five years after floodwaters as high as eleven feet surged through the area, though, much of New Orleans’s Lower Ninth Ward—approximately twelve miles to the southeast—looks as damaged as the day the levees broke. Poverty rates in the Village de L’Est area are close to those of the Ninth Ward (Chamlee-Wright 2010), yet across the Ninth Ward, less than 35 percent of the original population has returned, and many houses sit empty, with visible water lines on their walls (New York Times, 27 August 2010).

Thousands of miles away and a year earlier in Tamil Nadu, India, the 2004 Indian Ocean tsunami devastated hundreds of villages and killed thousands of residents along the sandy southeast coast. Within a year of the catastrophe, some villages put fishermen back to work, built new housing for the community, and brought in aid from both domestic and foreign organizations. Other hamlets—similarly devastated by the tsunami—seemed to be off the map of aid relief (Hindu, 17 March 2007). After disasters, some communities bounce back quickly, while others struggle to meet basic needs for food, water, shelter, and employment (Fletcher 2010). Certain neighborhoods draw their survivors back and attract new residents, while other areas in the same city become ghost towns, emptied of people.

This book seeks to explain the variation in post-disaster recovery by focusing on the role of social capital—the networks and resources available to people through their connections to others. I argue that higher levels of social capital—more than such factors as greater economic resources, assistance from the government or outside agencies, and low levels of damage—facilitate recovery and help survivors coordinate for more effective reconstruction.¹ Even highly damaged communities with low income and little outside aid benefit from denser social networks and tighter bonds with relatives, neighbors, and extralocal acquaintances. Alternatively, neighborhoods with lower levels of social resources can find themselves unable to organize collectively to deter looting and garbage dumping, to communicate necessary requests to the authorities, and to work together to rebuild their community. Deeper reservoirs of social capital serve as informal insurance² and mutual assistance for survivors, help them overcome collective action constraints, and increase the likelihood that they will stay and work to rebuild (as opposed to moving elsewhere) (Simile 1995).

However, social capital can be a double-edged sword, helping in-groups recover more effectively but at the same time slowing or halting rebuilding for those with fewer social resources who sit outside the mainstream. Neighborhoods and groups with fewer social resources face negative outcomes, both inadvertent and deliberate. The absence of social capital can stall a community’s recovery, short-circuiting attempts to overcome collective action problems (Chamlee-Wright 2010). Further, strong bonding social capital can reinforce existing systems of discrimination and justify programs that provide benefits only locally, not regionwide or citywide, harming those on the margins of society. I explore the “Janus-faced” nature of social capital (Szreter 2002) through studies of four disasters that took place between 1923 and 2005.

Defining Disasters and Their Impact

Sociologists define disasters broadly as failures of social systems (cf. Girard and Peacock 2000, 203; Erikson 1976, 154) or as occasions “when extraordinary efforts are taken to protect and defend some social resource whose existence is perceived as threatened” (Dynes 1989, 9). Here I use the word disasters to refer to collective events that—at least temporarily, and often for years afterward—suspend normal daily life routines owing to widespread damage (Fischer 1998, 3). Speaking broadly, disasters are events that overwhelm capacity in multiple ways (cf. Sawada 2010).³ Turner (1976, 755–756) saw a disaster as “an event, concentrated in time and space, which threatens a society or a relatively self-sufficient subdivision of a society with major unwanted consequences.” For this book a disaster is an event that suspends normal activities and threatens or causes severe, communitywide damage. This open-ended definition of disasters excludes traffic jams, plane delays, and fender benders but includes earthquakes, tsunamis, nuclear meltdowns, tornadoes, fires, and floods. Such events take lives, destroy homes and businesses, disrupt the standard flow of goods and services, put standard operating procedures on hold, and damage critical infrastructure. The four main events I discuss in this book fall into the category of megacatastrophes in that each killed more than one thousand people and destroyed thousands of residential and commercial structures. Some of the cases involved the devastation of half of the affected city (the 1923 Tokyo earthquake; cf. Aldrich 2008c) or the flooding of four-fifths of the area (Hurricane Katrina).

Attempts to further subcategorize disasters as “natural” or “man-made” are increasingly problematic given that much of the destruction from a disaster like Hurricane Katrina⁴ occurred precisely because of human attempts to subvert or artificially control nature (Steinberg 2000). Some have called this resulting vulnerability endogenous in that the outcome is at least in part the result of human actions (Auerswald et al. 2006, 5). Societies regularly build houses and provide insurance for residents in floodplains and flood-prone coastal areas; planners construct cities below sea level, while developers destroy the components of natural ecosystems such as mangroves, marshes, and wetlands that would protect such areas from flooding (Kolbert 2006). By centralizing and concentrating energy, population, and economic power into smaller areas, we have made the consequences for emergencies and disasters all the more intense (Perrow 2007).

Scholars of disaster continue to debate whether catastrophes have long-term structural impacts on localities and nations—that is, whether crises serve as a mechanism for Schumpeter’s vision of “creative destruction.” Some see crises as bringing economic opportunity, while others see either no long-term effects or negative outcomes for disaster-struck areas. For example, Douglas Dacy and Howard Kunreuther suggested that “a community may benefit economically from a disaster through a rapid inflow of capital for rebuilding purposes” (1969, 181).⁵ J. M. Albala-Bertrand (1993) studied the aftereffects of twenty-eight disasters in twenty-six Central and South American countries and found that despite varying levels of damage and pre-disaster economic development, even the worst disasters rarely had long-term, measurable economic impact. In their study of the population of Japanese cities bombed during the Second World War, Donald Davis and David Weinstein (2002, 1283) argued that “even very strong temporary shocks have virtually no permanent impact on the size of cities.”

Taiji Hagiwara and Toshiki Jinushi (2005) studied the Kobe earthquake and argued that by 2001—some six years after the event—any effects of the quake on the economy were negligible. Gary Becker (2005) argued that “lasting economic effects are similarly small for most other natural disasters that have occurred during the past couple of centuries.” Stephanie Chang (2000), on the contrary, posited that severe disasters, including the Kobe earthquake, did have a long-term structural impact on the economy; Eduardo Cavallo, Andrew Powell, and Oscar Becerra (2010b) estimated that a decade after a major disaster, national output per capita may remain one-third below normal. Furthermore, quantitative studies have shown that disasters may dampen the technological transfer between developed and developing countries, with major catastrophes reducing the spillover of knowledge (Cuaresma, Hlouskova, and Obersteiner 2008, 225).

Regardless of their measurable effect on the economies of cities and regions, disasters remain among the most critical events affecting residents and their neighborhoods around the world. Sociologists have underscored that the individual-level course of post-disaster recovery cannot be captured through simple economic measures; instead, recovery for many survivors involves an associational, mental transition from victim to citizen (Tatsuki et al. 2005, 3). For communities at large, recovery involves both population recovery and the (re)creation of bonds among neighbors; surveys have confirmed that after disasters, most survivors see social connections and community as critical for their recovery (Tatsuki and Hayashi 2002, 3; Tatsuki et al. 2004). Understanding what factors speed or impede disaster recovery is critical both for survivors and for decision makers who must allocate scarce resources after a crisis.

According to the Emergency Events Database, over the past three decades “natural” disasters killed close to three million people and inflicted billions of dollars in property damage. The 2004 Indian Ocean tsunami devastated the southeast Indian coast of Tamil Nadu; floodwater inundated New Orleans after Hurricane Katrina in 2005; and the 2010 Haiti earthquake may have killed 300,000 people. The 9.0 magnitude earthquake off Japan’s northeast shore on 11 March 2011 set off a massive tsunami that killed close to 20,000 people in Aomori, Fukushima, Miyagi, and Akita Prefectures and triggered a terrifying nuclear crisis in that country.⁶ While large-scale crises such as the 1991 Bangladesh cyclone, the 2008 Cyclone Nargis in Myanmar, Marmara earthquakes, and Italy’s 2009 earthquake captured media attention, numerous smaller-scale floods, typhoons, earthquakes, and mudslides killed hundreds of thousands of victims around the world and affected far more. Researchers have confirmed an upward trend in the number of disasters, individuals affected by them, and their economic costs over the past two decades (Hoyois et al. 2007). Scientists predict that the global cost of disaster, in both lives and property damage, will only increase with the progression of climate change.

Scholars recognize that the negative effects of disasters are concentrated in the most socially vulnerable populations, which include the poor, minorities, women, and the elderly (Steinberg 2000, 194; Morrow 2005; Cutter and Emrich 2006; Gill 2007; Cutter and Finch 2008).⁷ We know much about common flaws in disaster responses, such as the ways communications networks are likely to break down (Kweit and Kweit 2006), how intergovernmental relationships impede effective coordination (Rubin and Barbee 1985; Schneider 1990), and the fundamentally rhetorical “fantasy documents” prepared by disaster planners that play little role in actual disaster responses (Clarke 1999). However, researchers know little about what has gone right (cf. Valelly 2004). Specifically, scholars and disaster planners often overlook the fact that within disaster-affected regions, certain neighborhoods and towns recover from catastrophe more quickly than others (Edgington 2010, xv). Some areas display remarkable resilience after a crisis, while others seem unable to recover (Gulf Times, 25 June 2006). A clearer understanding of post-disaster resilience along with the factors that promote recovery will provide policy makers and victims alike with “usable knowledge”—knowledge that is both accurate and politically tractable (Haas 2004, 572).

Resilience and Recovery

Throughout this volume, I focus on the recovery of disaster-struck communities and the presence (or absence) of a capacity I call resilience. There are thousands of ways to define recovery after catastrophe, including economic (Albala-Bertrand 1993), demographic, infrastructure, and transportation-focused metrics (Liu, Fellowes, and Mabanta 2006; Karatani et al. 2000).⁸ The simplest definition of recovery—and perhaps the one least likely to occur—is one in which the community or city restores itself to its pre-disaster condition (Albala-Bertrand 1993, 173). But recovery is not a static point or a single moment in time: it is an extended process. Based on past studies, I define community recovery as the process of repopulation by survivors—who may have fled or been evacuated—and new residents along with the gradual resumption of normal daily routines for those occupants.⁹ In the case studies, I use various proxies to capture this concept, including yearly measures of population change, household and village access to and receipt of aid packages, and the construction and occupation of temporary housing.¹⁰ Some of these measures, such as temporary housing and access to assistance, encapsulate earlier stages of recovery, while others, such as population return, immigration, and growth, capture events that take place over years and even decades. Whereas popular press accounts hope to see results within weeks or months, an actual return to normality may take far longer, and population levels may never reach pre-disaster points. New Orleans, for example, will likely remain a smaller city than it was before Katrina.

For the studies of the 1923 Tokyo and 1995 Kobe earthquakes, I focus on population change because, as others have argued, “the numerical resilience of the population may be a reasonable proxy for recovery. For cities that have lost huge percentages of their populations, the restoration of the city as a place of habitation is itself a signal achievement” (Vale and Campanella 2005, 12). Population growth demonstrates whether survivors and newcomers are repopulating what may otherwise be a ghost town. The importance of monitoring how many residents and newcomers return to a city after a disaster can be seen in the efforts of United States government officials to capture this quantity of interest after Hurricane Katrina (Russell 2006). Authorities used creative measuring techniques, such as monitoring the US Postal Service’s change of address form filings, to measure population return to New Orleans after the storm (Lang 2006; Warner 2006). Weil (2010) has tied repopulation levels to various indicators of social capital and civic engagement in post-Katrina New Orleans. Similarly, in their study of the resilience of Japanese cities from 1925 to 1965—a period during which many of those areas in the study were bombed by Allied Forces—Davis and Weinstein (2002) used population measures to track overall trends in development. Observers pointed out that after the tragic 1972 Managua earthquake in Nicaragua, many citizens chose to flee to neighboring nations rather than attempt to return home and rebuild in a culture poisoned by civil war and corruption (Garvin 2010). David Edgington followed the population recovery for more than a decade after the 1995 Kobe earthquake to understand patterns of recovery in the city (2010, 206). Etsuko Yasui (2007, 319) argued that population recovery has proved to be an essential part of disaster recovery.

Beyond the process of recovery, scholars and decision makers alike have recently focused on resilience (Smith 2011). President Barack Obama praised New Orleans in the fall of 2010 as a “symbol of resilience,” primarily because of the return of people and businesses to the area in the five years following the citywide floods (Bowman 2010). International disaster planners at the 2005 World Conference on Disaster Reduction adopted the Hyogo Framework for Action, focused on “building the resilience of nations and communities to disasters” (United Nations International Strategy for Disaster Reduction 2005).¹¹ George Galster, Jackie Cutsinger, and Up Lim investigated the ways urban neighborhoods demonstrate what they call stability: outcomes are stable “if, upon being upset by some transient external force, the indicator tends to return to its original state” (2007, 169). The word resilience derives from the Latin word resilire, meaning “to jump back” or “to recoil,” and it generally describes “the capacity of a material or system to return to equilibrium after a displacement” (Norris et al. 2008, 127; cf. Adger et al. 2005). Across social science and biological science research, resilience indicates the “capacity for successful adaptation in the face of disturbance, stress, or adversity” (Norris et al. 2008, 129).

Broadly speaking, there are at least five dimensions to resilience after disaster, including “1) personal and familial socio-psychological well being; 2) organizational and institutional restoration; 3) economic and commercial resumption of services and productivity; 4) restoring infrastructural systems integrity; and 5) operational regularity of public safety and government” (McCreight 2010, 4–5). In this book I define resilience at the communal, not individual, level, focusing on the ability of a neighborhood, ward, or area to engage in positive, networked adaptation after a crisis. Resilience is a neighborhood’s capacity to weather crises such as disasters and engage in effective and efficient recovery through coordinated efforts and cooperative activities. Neighborhoods demonstrating less resilience fail to mobilize collectively and often must wait for recovery guidance and assistance from private or public sectors (Chamlee-Wright 2010). It is possible to use public policy programs and local initiatives to build resilience—that is, to increase a neighborhood’s capacity to recover effectively—as I discuss throughout this volume and at length in the conclusions and concrete policy recommendations in chapter 7.

Standard Theories of Recovery

Researchers have proposed hypotheses that link the ability of a region, town, or neighborhood to recover to a variety of factors, but few have carried out replicable empirical analyses to test them. Standard analyses envision quality of governance, aid, damage from the disaster, socioeconomic and demographic conditions, and population density as among the most important factors used to determine recovery rates. More recently, some studies have added social resources to the list of potential factors.

As a result, many observers assume that the quality of governance—whether local or regional—best determines how resilient disaster-struck areas will be. After disasters, affected people and commentators rush to judge the effectiveness of the government response. Following Hurricane Katrina, for example, pundits argued that the Bush administration had underestimated the damage from the broken levees and was unprepared for the scale of tragedy that followed (Murray 2006). Critics argued that Federal Emergency Management Agency (FEMA) director Michael Brown seemed unawa...