Can Social Vulnerabilities Be Affected by the Location of the Disaster - Essay Example

1. Can social vulnerabilities be affected by the location of the disaster? If so, how? Yes, social vulnerabilities can be affected by the location of the disaster. Social vulnerability is “the degree to which societies or socio-economic groups are affected by stresses and hazards, whether brought about by external forces or intrinsic factors – internal and external – that negatively impacts the social cohesion of a country” (UNDP, 2000). More concisely put, vulnerability to environmental hazards signifies the potential for loss, and losses vary geographically and over time (Cutter, et al., 2003). Social vulnerability is largely thought of as pertaining to the individual characteristics of people, such as age, race, health, income, type of dwelling unit and employment. What is of interest in most studies on social vulnerability, therefore, are the inequalities of people; yet there has been little done to compare the social vulnerability of one place to another (Carter, et al., 2003). The location of a disaster may be material in determining the economic loss that may be sustained from natural hazards. For instance, as the Japan earthquake showed recently, social vulnerability to earthquakes may be higher in cities due to the existence of earthquakes, and even higher in cities close to the shore where a tsunami may hit. It was for this reason that Cutter, et al. (2003) devised a hazards-of-place model of vulnerability, depicted in the following figure. The diagram shows an interactive link between the geographic context bubble and the social fabric bubble. Thus, while geographic context is primarily determinative of biophysical vulnerability, and social fabric primarily determinative of social vulnerability, the interaction between geographic context and social fabric also impact upon the two vulnerabilities. It is this link which the proposition of place context in social vulnerability refers to, as far as the place influences the social conditions in the location, the standard of wealth, the prevalence of response facilities, and the presence of response expertise. Cutter, et al., 2003, p. 244 Social vulnerability is partially the product of place inequalities, consisting of those characteristics such as level of urbanization, growth rates, economic vitality, and other contributory factors, whether positive or negative, which may influence the possible losses people may sustain in times of natural disasters. Cutter, et al. (2003) explored the possibility that a set of indicators may consistently describe the locational context of social vulnerabilities. The empirical study tested among 250 variables which were narrowed down to 42 independent variables. Of these, eleven composite factors were determined to be relevant in distinguishing the social vulnerabilities among different counties. Among these factors, personal wealth of counties (including median house values, median rents, and percentage of households earning more than $75,000 per annum) accounts for the most significant weight, explaining 12.4 per cent of the variance. This is because the communal wealth enables a community to absorb losses more quickly and recover faster, although it also means that more material goods are at risk at the particular location. 2. How can social vulnerability be incorporated into a risk assessment, vulnerability assessment, or risk management model? “Hazards, vulnerability and risk are all uniquely intertwined in the development of death and destruction from disasters” (Blaikie, et al., 2004, p.3). There is little doubt that social vulnerability has a logical and material influence on the risk assessment of a place or for a particular situation. It has not been effectively done to date as a matter of regular practice, however, because of the nature of social vulnerability. While most risk assessment models or vulnerability assessment techniques are quantitative, social vulnerability is highly insusceptible to quantitative estimation. Simply put, it is different to capture social vulnerability in terms of numbers. There have been various persistent attempts by academic researchers to effectively quantify social vulnerability, many of them apparently successful in capturing the essence of social vulnerability. One of these methods is that developed in the study by Dwyer, Zoppou, Nielsen, Day and Roberts (2004), which prescribed a technique for measuring certain attributes that contribute to vulnerability to natural hazards has been developed. The technique consists of four steps that shall be elaborated on as follows: (1) Indicator selection In any study that attempts to measure something, quantifiable indicators that will be made the basis of measurement. In the study by Dwyer et al., thirteen indicators have been selected, which are: age, income, gender, employment, residence type, household type, tenure type, health insurance, house insurance, car ownership, disability, English language skills, and debt/ savings. Two hazard indicators have also been identified, namely residence damage, and injuries. The latter two were included in order to link the model to a hazard context. (2) Accomplishment of a risk perception questionnaire The researchers felt the need to identify how the identified indicators would contribute to the vulnerability of individuals. This required data capture from the environment, for which a questionnaire was developed. It would have been ideal to be on hand to capture actual data when a disaster unfolds; in lieu of this, however, the questionnaire is the next best alternative. The questionnaire was developed from the perception of individuals who would form part of the population, and refined with the help of experts. (3) Construction of a decision tree analysis The use of decision tree analysis is a classification methodology that is employed to analyse and categorize large volumes of data, as an initial step to be processed into useful information. For the Dwyer study, the decision tree was applied to the data gathered by questionnaire, so as to find relationships that may exist between the indicator attributes. The study in particular was successful in identifying 11 decision rules that are determinative of a high level of vulnerability in the face of natural hazards. For each rule, a combination of two or more indicator attributes was necessary to predict vulnerability. Finally, (4) Synthetic estimation. Under ideal conditions, the researcher would have access to the highly detailed data pertaining to an individual; however, except for a few authoritarian jurisdictions, the individual has a right to privacy which the ethical researcher must respect. As a result thereof, Dwyer, et al. developed a method of synthetic estimation in lieu of cross-correlated data to the real population. The estimation process is largely statistical, for apparent reasons, which while not perfectly accurate could nevertheless provide a tool for analysing possible scenarios of natural hazard impacts on social vulnerability. To be sure, this is not the only method of measuring social vulnerability, but it demonstrates a feasible procedure that could aid in factoring in social vulnerability in most risk assessment and vulnerability assessment quantitative methods. References: Cutter, S L; Boruff, B J & Shirley, W L (2003) “Social Vulnerability to Environmental Hazards” Social Science Quarterly, June, 84(2):242-261 Blaikie P; Cannon, T; Davis, I; & Wisner, B 2004 At Risk: Natural Hazards, People’s Vulnerability, and Disasters, 2nd ed. New York, NY: Routledge Dwyer, A., Zoppou, C., Nielsen O., Day, S., & Roberts, S. “Quantifying Social Vulnerability:: A methodology for identifying those at risk to natural hazards.” Accessed 5 November 2011 from http://www.ga.gov.au/image_cache/GA4267.pdf United Nations Development Program (UNDP) (2000) Human Development Report 2000. New York: Oxford University Press Read More