Proceedings of International Symposium on City Planning 2013

Social Fragmentation and Disaster: a Case Study of ,

Ting-Jay Lee Ph.D. Student, Department of Bio-Industry Communication and Development, National Taiwan University(email: [email protected]) Li-Pei Peng Assistant Professor, Department of Bio-Industry Communication and Development, National Taiwan University(email: [email protected])

Abstract Social vulnerability approach has been recognized as one of the most important perspectives to discuss contemporary disaster, because the approach particularly accentuates human agency when discussing the issues of environmental changes or occurrences of disasters. However, social vulnerability is such a multi-faceted and complex construct that scholars from different fields are hardly to make a measurement consensus and to dialogue with each others. Some scholars consider that the approach attempts to manifest the role of human agency, but if lack of the historical observations, interpreting the causes of disasters through event-based viewpoint that hardly to reflect the institutional mechanism behind of disaster events. Therefore, this exploratory research conducted a social fragmentation concept which represents the social solidarity of a social system. Besides, for connecting to the institutional mechanism, this research depicted the trend of social fragmentation based on the historical data of 1983-2011 in the rural area of , Taiwan. Further, we tried to overlay trends of social fragmentation and simulated flood scene at municipality level by GIS. This research attempted not only to capture the characteristics of social fragmentation process but also to provide more local and long term meaning of contexts to disaster research.

Keywords: Disaster, Social Fragmentation, Social Vulnerability, Municipality

- 1 - 1. The changing meaning of disaster: From “Natural” to “Catastrophe” Recently, social vulnerability approach has been recognized as one of the most crucial perspectives to discuss the causes of contemporary disasters because the approach attempts to highlight the significance of human agency when discussing the causes and occurrence patterns of contemporary disasters. In other words, the crucial concept of social vulnerability approach to interpret contemporary disasters has become from “natural disaster” to “catastrophe”. Some researchers have exhibited that under the same impact condition of natural disaster, the more vulnerability of social system, the more serious disaster damage occurred (Cutter, S. L., 1996; Cutter, S. L. et al., 2003; Turner, B. L. et al., 2003; de Mendes, O. & Manuel. J., 2009; Menomi, S., et al., 2012). Thus, because structural characteristics of social system moderate various impacts brought from disasters, the discourse of disasters is treated as a social construct instead of a simple nature event. Some scholars pointed out that the traditional epistemology of disaster was as an “event-based” perspective which overemphasized particular disaster events such as typhoons or earthquakes. However, it is easy to ignore that disasters are consequences caused by human society. For instance, overuse of sloping site owing to urbanization is possible to lead to collapses of buildings and landslides. The result of emphasizing either disaster event itself only or the immediate effect is leaving the human agency out of consideration (Tierney, K. J., 2007). So the institutional roots which cause disasters will be hardly improved. For these reasons, lately, the social vulnerability researchers consider that through the “process of vulnerability” to understand the causes of disasters is necessary (Turner, B. L. et al., 2003). Such understanding of disaster will be helpful to establish more local-contextual strategy to responding disasters, environmental changes and more sustainable life style (Turner, B. L., et al., 2003). Hence, only by considering the trajectory or process concepts to understand disaster, we can clarify the limitation and the possibility of human action while facing changes of social-environmental system.

2. Social vulnerability, Social Fragmentation, and Disaster “Vulnerability is individual or groups base on their capacity to prepare, response, resist and recover from the impact of natural disaster” (Blaikie, et al., 1994). Different knowledge fields have various definitions of social vulnerability because of the multi-dimensions and high abstract level (Menomi, et al., 2012). Furthermore, the complexity of disaster situation enables the content and operations of social vulnerability to be a developing concept, certain factors which has been recognized to be crucial to decide the degree of a social system, for instance, personal property, age, density of buildings, single department economics, race, ethnicity, etc. However, rare researches attempt to conceptualize these factors or deeply examine the relationship between the main factors and its changes. Majority of the applied researches mainly conduct SoVI without weighting to measure the social vulnerability degree of social system (Cutter, 1996; Cutter, et al., 2003; de Mendes, 2009). However, taking the regional characteristics of disasters into account, most research can hardly to decide the weighting of measurement items. Even though the measurement can provide the abstract picture of the vulnerable level of a social system, but such way is still difficult to display the details and other potential characteristics. Such measurement and lack of historical data may neglect the other potential heterogeneity in terms of the role of human agency among social systems and reflecting institutional mechanism.

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Social fragmentation can be seen as the reverse concept of the social integration (Evans, et al., 2004). It represents the weak social solidarity and lack of social support. Under such meanings, individuals who belong to the highly social fragmented society are hardly coped with the disaster problems they have. Hence, we may assume that to a certain extent, a high social integration system has more capacity to response to disaster or recover from damages than its counterpart. The other crucial point is still that social fragmentation which is stand for the degree of social integration to a social system, the current situation must be the consequence of long-term societal development. Therefore, this research aims to conduct the social fragmentation concept to capture the social integration level of a social system for supplement to the social vulnerability index (SoVI). Further to present if the concept associated with the longitudinal data can depict the trend of social fragmentation and potential response while facing nature disaster.

3. Method and Data Analysis This research presents 2 analyses including first to describe the trend of social fragmentation at municipality level in Chiayi County by using longitudinal statistical data. Second is to conduct overlay analysis on the scene of both social fragmentation trend and simulated flood. Based on the changing trend of every social fragmentation of those municipalities, this research analyzes overlay pictures which simulated the flood scene of Chiayi County under the condition of rainfall above one day/500 mm. Through such analytical strategy, this research can grasp potential response capacity to major disaster at municipality level.

3.1 Variables and Data Resources Traditionally, social fragmentation concept assumes that high-migration, divorce rate and solitary percentage, etc., to describe the low social integration of social system. However, this research considers the experiences of rural area in Taiwan. One of the root causes of social fragmentation in rural area is high out-migration that is caused by the population push and pull effect during the process of urbanization. Thus, differing from the general assumption of social fragmentation, this research considers that high out-migration phenomenon can manifest the social fragmentation in rural area of Taiwan. Under these considerations, the social increase rate was assumed to be negative to social fragmentation. However, marriage condition is recognized a crucial factor to promote the social integration for social system.

- 3 - Table 1 Variable and Relation to Social Fragmentation Relation to Social Concept Variable Source1 Fragmentation Social Fragmentation Social Increase Negative Department of Accounting and Rate2 Statistics, （1983-2011）3 Crude Divorce Positive Department of Accounting and Rate4 Statistics, Chiayi County

Crude Marriage Negative Government Rate5 （2000-2011） Natural Disaster Risk Simulated Flood -- -- Water Resources Agency, Scene Ministry of Economic Affairs (2007-2010) Note: Dapu has extreme large social migration rate in many years, in order to avoid confounding the index building. Thus, we excluded Dapu’s data. 2 Social increase rate = (in-migration rate) – (out-migration rate). 3 The original data of social increase rate in 1988 and 1995 year are absent. 4 Crude divorce rate = ( registered pairs of divorce／population of mid-year)*1000 5 Crude marriage rate= (registered pairs of marriage／population of mid-year)*1000

Therefore, Table 1 shows our assumption that divorce rate and marriage rate have positive and negative association with social fragmentation respectively. In sum, this research designated social increase rate, crude divorce rate and crude marriage rate as measures of the social fragmentation. The longitudinal data of all these 3 variables were collected from Department of Accounting and Statistics of Chiayi County Government from 1983 to 2011. For assessing the potential response of social system to natural disaster, we used the simulated flood scene based on the real flood data, 2007-2011, in order to understand the different exposure risk of disaster, the trend of potential responses and the differences among municipalities.

3.2 Analysis Method The analytical procedure can be divided into two main steps. The first step is to analyze the trend of social fragmentation during 1983-2011. The second is to overlay the basis of the spatial distribution of simulated flood scene and the trend of social fragmentation in Chiayi County by GIS. In order to get meaningful comparisons among 3 items and integrate them to a social fragmentation index, we conducted the standardize procedure on items which means that the lower social increase rate, the more social fragmentation; the lower crude marriage rate, the more social fragmentation; and the lower crude divorce rate, the lower social fragmentation. Therefore, before sum up all standardized scores of items, we reverse the direction of crude divorce rate’s standardized scores. After that, we summed up the standardized scores of items and calculate the item averages of each year as annually social fragmentation index score. The longitudinal data is from 1983-2011. In order to clearer display the characteristic of social fragmentation, we divided the 18 years into six time periods by 1983-1985, 1986-1990, 19991-1995, 1996-2000, 2001-2005 and 2006-2011. We summed up the standardized scores and then calculate the average of each time period. Further, we overlay the basis of the spatial distribution of simulated flood scene and the trend of social fragmentation six time periods.

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4. Results 4.1 Trend of social fragmentation between 1983 and 2011 4.1.1 Range of social increase rate According to the range of standardized social increase rate scores between 1983 and 2011 year, the in-migration township is . The out-migration townships are Dongshi and Xikou. The townships changed from out-migration to in-migration are Dalin, Lucao, Xinhang, Yizhu and Liujiao. , and show decreased in-migration. , Meishan, Zhougpu and are changed from in-migration to out-migration (Table 2 and 3).

4.1.2 The range of crude divorce rate between 2000 and 2011 Table 4 and 5 show standardized scores of crude divorce rate which is original and without direction reverse. The different range of standardized score of divorce rate between 2000 and 2011 year shows that the increased divorce rate townships are Xikou, Dongshi, Yizhu, Xinhang, Zhougpu, Zhuqi and Alishan from low to high. In detail, Xinhang, Zhougpu, Zhuqi and Alishan has been transformed from negative to positive value. The townships with decreased divorce rate are Taibao, Dalin, Budai, Shuishang, Puzi, Liujiao and Meishan. Lucao, Minxiong and Fanlu are transformed from positive to negative value.

Table 2 Range of social increase rate between 1983 and 2011 Region Seashore Plain Township Dongshi Budai Liujiao Yizhu Lucao Shuishang Xinhang Minxiong Xikou Range of 0.63 0.41 1.34 1.04 0.97 -1.89 0.98 -2.15 0.73 Z-score Region Plain Hill-Mountain -- Township Taibao Dalin Puzi Zhougpu Zhuqi Meishan Fanlu Alishan -- Range of -0.31 0.77 -0.74 -1.81 -0.21 -0.77 0.49 0.7 -- Z-score

Table 3 Characteristic of social increase rate between 1983 and 2011 Range 1983 2011 Characteristic Township Positive + + Increased in-migration Fanlu − + Out-migration to in-migration Dalin, Lucao, Xinhang, Yizhu, Liujiao − − Decreased out-migration Dongshi, Xikou Negative + + Decreased in-migration Zhuqi, Taibao, Minxiong + − In-migration to out-migration Puzi, Meishan, Zhougpu, Shuishang − − Increased out0migration None Note: Ranges of standardized scores are ranged in order from low to high.

Table 4 Range of crude divorce rate between 2000 and 2011 Region Seashore Plain Township Dongshi Budai Liujiao Yizhu Lucao Shuishang Xinhang Minxiong Xikou Range of 0.88 -0.18 -0.78 1.02 -1.07 -0.65 1.02 -2.08 0.41 Z-score Region Plain Hill-Mountain -- Township Taibao Dalin Puzi Zhougpu Zhuqi Meishan Fanlu Alishan -- Range of -0.01 -0.10 -0.75 1.47 2.05 -0.80 -2.50 7.01 -- Z-score

- 5 - Table 5 Characteristic of crude divorce rate between 2000 and 2011 Range 2000 2011 Characteristic Township Positive + + Increased divorce rate Xikou, Dongshi, Yizhu

− + Negative to positive Xinhang, Zhougpu, Zhuqi, Alishan − − Increased divorce rate None Negative + + Decreased divorce rate Shuishang, Dalin + − Positive to Negative Lucao, Minxiong, Fanlu − − Decreased divorce rate Taibao, Budai, Puzi, Liujiao, Meishan

4.1.3 The range of crude marriage rate between 2000 and 2011 Based on the distribution of range of standardized score of marriage rate between 2000 and 2011, Table 6 shows that the increased level of range are Fanlu, Meishan, Minxiong, Taibao, Shuishang, Budai, Zhuqi, Zhougpu, Puzi and Alishan. The decreased level of standardized marriage rate includes Lucao, Dalin, Xinhang, Dongshi, Xikou, Liujiao and Yizhu. The standardized scores transformed from negative to positive are Minxiong, Taibao, Zhuqi, Puzi and Alishan. Xinhang, Xikou, Liujiao and Yizhu are transformed from positive to negative (Table 6 and 7).

Table 6 Range of crude marriage rate between 2000 and 2011 Region Seashore Plain Township Dongshi Budai Liujiao Yizhu Lucao Shuishang Xinhang Minxiong Xikou Range of -1.21 0.59 -2.18 -2.36 -0.41 0.55 -1.12 0.4 -1.26 Z-score Region Plain Hill-Mountain -- Township Taibao Dalin Puzi Zhougpu Zhuqi Meishan Fanlu Alishan -- Range of 0.49 -0.42 2.27 1.77 0.85 0.38 0.11 3.51 -- Z-score

Table 7 Characteristic of crude marriage rate between 2000 and 2011 Range 2000 2011 Characteristic Township Positive + + Increased marriage rate Shuishang, Zhougpu − + Negative to positive Minxiong, Taibao, Zhuqi, Puzi, Alishan − − Increased marriage rate Fanlu, Meishan, Budai Negative + + Decreased marriage rate Dongshi + − Positive to Negative Xinhang, Xikou, Liujiao, Yizhu − − Decreased marriage rate Lucao, Dalin

4.1.4 The range of social fragmentation between 1983 and 2011 Table 8 and 9 presents that increased level of standardized social fragmentation scores are Alishan, Meishan, Zhuqi, Zhougpu, Shuishang and Minxiong. The decreased level of standardized social fragmentation scores are Taibao, Xinhang, Dalin, Puzi, Yizhu, Budai, Xikou, Dongshi, Fanlu, Lucao and Liujiao. In detail, the township with standardized scores changed from negative to positive is Lucao only. The townships changed from positive to negative are Meishan and Zhuqi.

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Table 8 Range of social fragmentation between1983 and 2011 Region Seashore Plain Township Dongshi Budai Liujiao Yizhu Lucao Shuishang Xinhang Minxiong Xikou Range of 0.75 0.58 0.98 0.52 0.9 -1.43 0.11 -1.73 0.7 Z-score Region Plain Hill-Mountain -- Township Taibao Dalin Puzi Zhougpu Zhuqi Meishan Fanlu Alishan -- Range of 0.09 0.26 0.38 -1.29 -0.48 -0.17 0.81 -0.04 -- Z-score

Table 9 Characteristic of social fragmentation between 2000 and 2011 Range 1983 2011 Characteristic Township Positive + + Decreased fragmentation Taibao, Puzi, Fanlu − + Negative to positive Lucao − − Decreased fragmentation Xinhang, Dalin, Yizhu, Budai, Xikou, Dongshi, Liujiao Negative + + Increased fragmentation Zhougpu, Shuishang, Minxiong + − Positive to Negative Meishan, Zhuqi − − Increased fragmentation Alishan

Figure1 Overlay analysis on the trend of social fragmentation in six time periods

4.2 Overlapping social fragmentation trend and simulated flood scene Based on the trend of social fragmentation from 1983 to 2011, we overlaid the social fragmentation and simulated flood scene as Figure 1. We observed 4 types of social fragmentation trend. Type one showed that social fragmentation scores are continually lower

- 7 - than average of all townships; we name such type as “continual high social fragmentation”, it includes Dongshi, Budai, Yizhu, Lucao, Puzi, Liuijao and Xinheng. Type two showed that the social fragmentation scores are changed from positive to negative that means social fragmentation degree increased, this type is named as “transformed social fragmentation”, which includes Shuishang and Zhougpu. Type three showed the fluctuated trend of social fragmentation, it includes Dalin, Meishan, Zhuqi, Fanlu and Alishan, we call this type “Fluctuated social fragmentation”. Finally, Taibao is categorized as one type due to its higher social fragmentation scores than average of all townships. Hence, we call this type as “continual low social fragmentation”.

5. Concluding Remarks According to the results, we identified the four types of social fragmentation that includes the “continual high social fragmentation”, “transformed social fragmentation”, “fluctuated social fragmentation” and “continual low social fragmentation”. Besides, we also found that the “continual high social fragmentation” type is located in the seashore region, the “transformed social fragmentation” type clusters the plain region, the “fluctuated social fragmentation” type gathers at the hill-mountain region, The “continual low social fragmentation” type includes Taibao City only because it is the county capital and located at the core region of the county. It is obvious that the researcher may overlook such potential types of social fragmentation if lack of longitudinal trend analysis. In other words, the trend analysis is necessary to clarify different characteristics of social fragmentation in the future. Therefore, we can say that the changing trend analysis based on the longitudinal data can come off the limitation of event-based perspective to discussing disaster and also can provide historical and local contexts for further insights of human agency and institutional mechanism of natural disasters. Different from the traditional social vulnerability of using the SoVI measurement, we emphasized that social fragmentation is related to social integration about the aspect of social systems. Therefore, it may be a supplemental role to fill in the shortages of measurement of SoVI, after all understanding more about the changes of human society would help us to mitigate and adapt to the disasters in the future.

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Vulnerability and Resilience in Order to Design Risk-Mitigation Strategies. Natural Hazards, 64:2057–2082. (8) Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J.J., Corell, R.W., Christensen, L., Eckley, N., Kasperson, J.X., Luers, A,. Martello, M.L., Polsky, C., Pulsipher, A., Schiller, A. (2003), A Framework for Vulnerability Analysis in Sustainability Science. Proceedings of the National Academy of Sciences, 100(14), 8074-8079. (9) Tierney, K. J. (2007), From the Margins to the Mainstream? Disaster research at the crossroads. Annual Review of Sociology, 33, 503-525.

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