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Exploring relationship between social inequality and adaptations to climate change: evidence from urban household surveys in the Yangtze River delta, China

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Abstract

This research enhances our understanding of the complex relationship between climate change, social inequality, and adaption, in urban areas. It is novel, being the first research in this area to be based on a conceptual econometric framework within which multiple stages are explicitly developed, and for which empirical evidence is gathered. We use this approach to examine the role of material, social status, and power inequality in influencing spontaneous adaptation choices in urban settings of China’s Yangtze River delta. This framework differentiates two vital stages in adaptation decision making at the household level which allows us to examine, first, how social inequality shapes the severity of climate impact and, second, how social inequality interacts with this experience to influence responses to these impacts. We pilot this approach in selected metropolitan areas of Shanghai and Nanjing. Our results show that all dimensions of social inequality are significantly associated with experiences of climate change and adaptation choice. Application of our conceptual framework provides policymakers and planners with a new and useful tool that can be used to formulate better policy measures that either enable the disadvantaged to adapt in situ or provide these groups with real opportunities and capacities to migrate.

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Notes

  1. In situ adaptation can take the following forms: adopting new crop(s) to suit the altered growing conditions, improving water management, adopting new agricultural techniques, returning farmland to forestry in rural areas, and insuring assets against climate change-related damages, changing personal lifestyle and habits, improving building structure, and purchasing climate change protection devices in urban areas.

  2. The YRD encompasses two provinces (Jiangsu, Zhejiang) and one municipality (Shanghai). The region supports 8.1 % of China’s population (1.34 billion) and contains the nation’s largest urban cluster—one that comprises 16 major cities. According to China’s New National Urbanisation Plan (2014–2020), which places urban policy at the heart of Chinese decision-making, the YRD, together with another two largest urban clusters that involve Beijing–Tianjin–Hebei and Pearl River Delta in east coast of the country, will continue to gain momentum in the process of urbanization and will play pivotal roles in the new era of urbanization (State Council 2014).

  3. A residents’ committee is a grassroots organization of self-governance by residents in cities on the basis of residence. It is essential in direct grass-roots democracy, crucial pillars of grass-roots agencies of state power, and links between the government and residents. It plays major roles in: handling family planning, social service, public affairs, and public welfare services of the residents in the local residential area; reporting local residents’ opinions and demands to the local government; and publicizing the principles, policies, and statutes of the Communist Party and the government.

  4. We used publicly available sources to construct a household roster. Such information was obtained from the administrative sheets maintained by local residents’ committees, which recorded the names, basic demographic characteristics (e.g., age, sex), occupation, and residential address of people who have registered their household status with the local residents’ committees as either permanent urban residents or temporary residents (the transient migrant or “floating” population). Using these frames, we systematically drew random samples of households in each of the 50 selected local residents’ communities. The sample was proportionately distributed to each local community to be surveyed in terms of population size.

  5. The household head was asked to respond to the questionnaire. Where the household head was unavailable, his or her spouse, or an informant who was most knowledgeable about the household situations, answered the survey questions.

  6. There are varied push and pull factors for migration, including crop failure, displacement, and resettlement due to urbanization or other infrastructure projects. To clarify for our research, we specifically asked respondents if climate change was the primary reason, or not, for their migration.

  7. The power inequality variable collected information for the 5-year period from 2007 to 2011. It was also used as a proxy measurement for 2007 in the first-stage model. We argue that power inequality is almost unlikely to change over the 5-year period and likely to be highly correlated across years.

  8. The factor of climate change is simply assessed by assessing respondents’ answers to the question: “Did climatic events or climate-induced disasters in the Delta (or origin areas of migrants) occur frequently in the past 5 years (2007–2011), compared to the preceding decades?” Answers to this question were coded as 5 levels at Likert scale ranging from 1 (“never happened”) to 5 (“happened very frequently”). This variable of “frequency of climate-related events since 2007” is only used in the second-stage regression, but not in the first-stage model, as the 5-year period covered means it would not be appropriate to use it to predict the climate change impact in 2007 in the first-stage regression.

  9. The MProbit model is used to estimate several correlated binary outcomes jointly (Greene 2008: 827).

  10. The MLogit model is one of the most frequently used regression models in situations of unordered multiple choice dependent variables (Greene 2008: 843–845).

  11. We only present the results of the MLogit modeling with respect to to the impacts of climate change on the economic situation and living environment of surveyed households, as this model has a slightly better fit in terms of BIC than the modeling of impacts on health conditions and living environment.

References

  • Adamo, S. (2010). Environmental migration and cities in the context of global environmental change. Current Opinion in Environmental Sustainability, 2(3), 161–165.

    Article  Google Scholar 

  • Adger, W., Arnell, N., & Tompkins, E. (2005). Successful adaptation to climate change across scales. Global Environmental Change, 15, 77–86.

    Article  Google Scholar 

  • Adger, W., Barnett, J., Brown, K., Marshall, N., & O’Brien, K. (2013). Cultural dimensions of climate change impacts and adaptation. Nature Climate Change, 3, 112–117.

    Article  Google Scholar 

  • Adger, W., Barnett, J., Chapin III, F., & Ellemor, H. (2011). This must be the place: underrepresentation of identity and meaning in climate change decision-making. Global Environmental Politics, 11(2), 1–25.

    Article  Google Scholar 

  • Adger, W., & Kelly, P. (1999). Social vulnerability to climate change and the architecture of entitlements. Mitigation and Adaptation Strategies for Global Change, 4, 253–266.

    Article  Google Scholar 

  • Afangideh, A., Akpan, P., Udofia, E., & Ukeh, D. (2012). Socio-demographic determinants of response strategies by resource-poor farmers to climate change in south-eastern Nigeria. Journal of Geography and Geology, 4(1), 33–41.

    Article  Google Scholar 

  • Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50, 179–211.

    Article  Google Scholar 

  • Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behaviour. In D. Albarracín, B. Johnson, & M. Zanna (Eds.), Handbook of attitudes and attitude change: Basic principles. Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Barbieri, A., Domingues, E., Queiroz, B., Ruiz, R., Rigotti, J., Carvalho, J., et al. (2010). Climate change and population migration in Brazil’s Northeast: Scenarios for 2025–2050. Population and Environment, 31, 344–370.

    Article  Google Scholar 

  • Begum, R., Siwar, C., Abidin, R., & Pereira, J. (2011). Vulnerability of climate change and hardcore poverty in Malaysia. Environmental Science and Technology, 4, 112–117.

    Article  Google Scholar 

  • Bi, P., Williams, S., Loughnan, M., Lloyd, G., Hansen, A., & Kjellstrom, T. (2011). The effects of extreme heat on human mortality and morbidity in Australia: Implications for public health. Asia Pacific Journal of Public Health, 23, 27S–36S.

    Article  Google Scholar 

  • Black, R., Adger, N., Arnell, W., Dercon, S., Geddes, A., & Thomas, D. (2011a). The effect of environmental change on human migration. Global Environmental Change, 21, S3–S11.

    Article  Google Scholar 

  • Black, R., Bennett, S., Thomas, S., & Beddington, J. (2011b). Climate change: Migration as adaptation. Nature, 478, 447–449.

    Article  Google Scholar 

  • Bourdieu, P. (1984). Distinction: A Social Critique of the Judgement of Taste. London: Routledge.

    Google Scholar 

  • Burton, I., Huq, S., Lim, B., Pilifosova, O., & Schipper, E. (2002). From impacts assessment to adaptation priorities: The shaping of adaptation policies. Climate Policy, 2, 145–159.

    Article  Google Scholar 

  • Cappellari, L., & Jenkins, S. (2003). Multivariate probit regression using simulated maximum likelihood. The Stata Journal, 3(3), 278–294.

    Google Scholar 

  • Castles, S. (2011). Understanding global migration: A social transformation perspective. Journal of Ethnic and Migration Studies, 36(10), 1565–1586.

    Article  Google Scholar 

  • Chen, J., Guo, F., & Wu, Y. (2011). One decade of urban housing reform in china: Urban housing price dynamics and the role of migration and urbanization, 1995–2005. Habitat International, 35, 1–8.

    Article  Google Scholar 

  • China Daily. (2013). The Yangtze River delta has become the core region of human migration in China. Retrieved August 28, 2013, from http://www.chinadaily.com.cn/hqgj/jryw/2013-04-10/content_8717325.html.

  • Cui, Y. (Ed.). (2008). Shanghai Almanac. Shanghai: Shanghai Almanac Press.

    Google Scholar 

  • Cutter, S. (2011). The Katrina exodus: internal displacements and unequal outcomes. Government Office for Science. Retrieved May 1st, 2014, from http://go.nature.com/somswg.

  • DaVanzo, J. (1981). Repeat migration, information costs, and location-specific capital. Population and Environment, 4(1), 45–73.

    Article  Google Scholar 

  • Deressa, T., Hassan, R., Ringler, C., Alemu, T., & Yesuf, M. (2009). Determinants of farmers’ choice of adaptation methods to climate change in the Nile Basin of Ethiopia. Global Environmental Change, 19(2), 248–255.

    Article  Google Scholar 

  • Dulal, H., Shah, K., & Ahmad, N. (2009). Social equity considerations in the implementation of Caribbean climate change adaptation policies. Sustainability, 1(3), 363–383.

    Article  Google Scholar 

  • Elliott, J., & Pais, J. (2006). Race, class, and Hurricane Katrina: Social differences in human responses to disaster. Social Science Research, 35(2), 295–321.

    Article  Google Scholar 

  • Feng, S., Krueger, A. B., & Oppenheimer, M. (2010). Linkages among climate change, crop yields and Mexico-US cross-border migration. Proceedings of the National Academy of Science, 107(32), 14257–14262.

    Article  Google Scholar 

  • Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: the reasoned action approach. New York: Psychology Press.

    Google Scholar 

  • Fussell, E., & Massey, D. (2004). The limits to cumulative causation: International migration from Mexican urban areas. Demography, 41(1), 151–171.

    Article  Google Scholar 

  • Gold, T., Guthrie, D., & Wank, D. (2002). Social connections in China: Institutions, culture, and the changing nature of guanxi. New York: Cambridge University Press.

    Book  Google Scholar 

  • Goldthorpe, J. (2010). Analysing social inequality: A critique of two recent contributions from economics and epidemiology. European Sociological Review, 26, 731–744.

    Article  Google Scholar 

  • Greene, W. (2008). Econometric analysis. New York: Pearson Education Inc.

    Google Scholar 

  • Grothmann, T., & Patt, A. (2005). Adaptive capacity and human cognition: The process of individual adaptation to climate change. Global Environmental Change, 15, 199–213.

    Article  Google Scholar 

  • Gu, C., Hu, L., Zhang, X., Wang, X., & Guo, J. (2011). Climate change and urbanization in the Yangtze River delta. Habitat International, 35, 544–552.

    Article  Google Scholar 

  • Henry, S., Boyle, P., & Lambin, E. (2003). Modelling inter-provincial migration in Burkina Faso, West Africa: The role of socio-demographic and environmental factors. Applied Geography, 23, 115–136.

    Article  Google Scholar 

  • Hisali, E., Birungi, P., & Buyinza, F. (2011). Adaptation to climate change in Uganda: Evidence from micro level data. Global Environmental Change, 21, 1245–1261.

    Article  Google Scholar 

  • Hradil, S. (2001). Soziale Ungleichheit in Deutschland (8th ed.). Opladen: Leske+Budrich.

    Google Scholar 

  • Hugo, G., Bardsley, D., Tan, Y., Sharma, V., Williams, M., & Bedford, R. (2009). Climate change and migration in the Asia-Pacific region. ABD, Manila: Final Report to the Asian Development Bank.

    Google Scholar 

  • Hunter, L., Nawrotzki, R., Leyk, S., Maclaurin, G., Twine, W., Collinson, M., et al. (2013). Rural outmigration, natural capital, and livelihoods in South Africa. Population, Space and Place. doi:10.1002/psp.1776.

    Google Scholar 

  • Information Office of the State Council of China (IOSC). (2011). China’s policies and actions for addressing climate change, November 2011, Beijing. Retrieved March 15, 2013, from http://gjs.mep.gov.cn/lydt/201111/t20111123_220431.htm.

  • IPCC. (2007). Impacts, Adaptation and Vulnerability. Cambridge: Cambridge University Press.

    Google Scholar 

  • IPCC. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Working Group II Contribution to the IPCC 5th Assessment Report. Retrieved May 5, 2014, from http://ipcc-wg2.gov/AR5/images/uploads/WGIIAR5-TS_FGDall.pdf.

  • Isham, J. (2002). The effect of social capital on fertiliser adoption: evidence from Rural Tanzania. Journal of African Economies, 11, 39–60.

    Article  Google Scholar 

  • Katungi, E. (2007). Social capital and technology adoption on small farms: the case of banana production technology in Uganda. Ph.D. Thesis. Department of Agricultural Economics, Extension, and Rural Development, University of Pretoria, South Africa.

  • Kelly, P., & Adger, N. (2000). Theory and practice in assessing vulnerability to climate change and facilitating adaptation. Climatic Change, 47(4), 325–352.

    Article  Google Scholar 

  • Kovats, S., Wilkinson, P., & Menne, B. (2010). Social inequalities in environmental risks associated with global climate change. In World Health Organization (Eds.), Environment and health risks: A review of influence and effects of social inequalities (pp. 149–158). WHO Regional Office for Europe: Copenhagen. Ministry for Foreign Affairs, Stockholm, Sweden.

  • Lewicka, M. (2011). Place attachment: How far have we come in the last 40 years? Journal of Environmental Psychology, 31(3), 207–230.

    Article  Google Scholar 

  • Li, Z., & Wu, F. (2006). Socio-spatial differentiation and residential inequalities in Shanghai: A case study of three neighborhoods. Housing Studies, 21(5), 695–717.

    Article  Google Scholar 

  • Liu, D., & Ye, Y. (2005). Relative sea-level rise and ground subsidence in the Yangtze River Delta. Journal of Geological Hazards and Environment Preservation, 16(4), 400–404.

    Google Scholar 

  • Luber, G., & McGeehin, M. (2008). Climate change and extreme heat events. American Journal of Preventive Medicine, 35, 429–435.

    Article  Google Scholar 

  • Lwasa, S., Tenywa, M., Majaliwa, M., Wanjalolo, G., Sengendo, H., & Prain, G. (2009). Enhancing adaptation of poor urban dwellers to the effects of climate variability and change. IOP Conference Series: Earth and Environment Science, 6, 332002.

    Article  Google Scholar 

  • Massey, D., Arango, J., Hugo, G., Kouaouci, A., Pellerino, A., & Taylor, J. (1993). Theories of international migration: An integration and appraisal. Population and Development Review, 19, 431–466.

    Article  Google Scholar 

  • Massey, D., Axinn, W., & Ghimire, D. (2010). Environmental change and out-migration: Evidence from Nepal. Population and Environment, 32(2–3), 109–136.

    Article  Google Scholar 

  • McLeman, R., & Smit, B. (2006). Migration as an adaptation to climate change. Climatic Change, 76, 1–2.

    Article  Google Scholar 

  • McMichael, A. (2012). An ill wind? climate change, migration, and health. Environmental Health Perspectives, 120(5), 646–654.

    Article  Google Scholar 

  • Mehrotra, S., Natenzon, C., Omojola, A., Folorunsho, R., Gilbride, J., & Rosenzweig, C. (2009). Framework for City Climate Risk Assessment. Retrieved May 1, 2014, from http://www.uccrn.org/documents/Framework_for_City_Risk_Assessment-June17.pdf.

  • Miao, Q., Shuanghe, S., Dingyuan, F., & Yuguo, D. (1995). Preliminary analysis on the climate change’s influence on the economic development in the Yangtze River Delta. In Institute of Work Department of China Association of Science and Technology (Ed.), The Yangtze River’s development in the 21st century (pp. 59–64). Beijing: Surveying and Mapping Press.

    Google Scholar 

  • National Development and Reform Commission (NDRC). (2007). China’s National Program for Adapting to Climate Change. Retrieved May 21, 2014, from http://www.ndrc.gov.cn/xwzx/xwfb/200706/t20070604_139486.html.

  • National Population & Family Planning Commission of China (NPFPC). (2012). 2012 Report on China’s Migrant Population Development. Beijing: China Population Publishing House.

    Google Scholar 

  • Osberghaus, D., Finkel, E., & Pohl, M. (2010). Individual adaptation to climate change: The role of information and perceived risk. Discussion Paper No. 10–061, Centre for European Economic Research.

  • Paavola, J., & Adger, W. (2006). Fair adaptation to climate change. Ecological Economics, 56, 594–609.

    Article  Google Scholar 

  • Peng, R., Bobb, J., Tebaldi, C., McDaniel, L., Bell, M., & Dominici, F. (2011). Towards a quantitative estimate of future heat wave mortality under global climate change. Environmental Health Perspectives, 119, 701–706.

    Article  Google Scholar 

  • Perch-Nielsen, S., Bättig, M., & Imboden, D. (2008). Exploring the link between climate change and migration. Climatic Change, 91, 375–393.

    Article  Google Scholar 

  • Population Census Office of the State Council (PCOSC). (2011). Major figures on population census of China: Population Growth. Beijing: China Statistics Press.

    Google Scholar 

  • Ramin, B., & Svoboda, T. (2009). Health of the homeless and climate change. Journal of Urban Health, 86(4), 654–664.

    Article  Google Scholar 

  • Reuveny, R. (2007). Climate change-induced migration and violent conflict. Political Geography, 26, 656–673.

    Article  Google Scholar 

  • Rosenzweig, C. (2010). Cities lead the way in climate–change action. Nature, 467, 909–911.

    Article  Google Scholar 

  • Roulleau-Berger, L. & Lu, S. (2005). Migrant workers in Shanghai. China Perspectives, 58, 2–9. Retrieved Sep 30th, 2014, from http://chinaperspectives.revues.org/456.

  • Rye, J. (2006). Leaving the countryside: An analysis of rural-to-urban migration and long-term capital accumulation. Acta Sociologica, 49(1), 47–65.

    Article  Google Scholar 

  • Rye, J. (2011). Youth migration, rurality and class: A Bourdieusian approach. European Urban and Regional Studies, 18(2), 170–183.

    Article  Google Scholar 

  • Savage, M., Warde, A., & Devine, F. (2005). Capitals, assets, and resources: Some critical issues. British Journal of Sociology, 56(1), 31–47.

    Article  Google Scholar 

  • Shanghai Government (2011a). Water Conservancy Construction in Pudong, Shanghai. Retrieved May 21st, 2014, from http://www.shanghai.gov.cn/shanghai/node2314/node2315/node15343/u21ai543073.html.

  • Shanghai Government (2011b). The twelfth five year plan for meteorology development in Shanghai. Retrieved May 21st, 2014, from http://www.shanghai.gov.cn/shanghai/node2314/node2319/node22396/node22403/u21ai565276.html.

  • Shuman, E. (2010). Global climate change and infectious diseases. The New England Journal of Medicine, 362, 1061–1063.

    Article  Google Scholar 

  • Sinden, J., & King, D. (1990). Adoption of soil conservation measures in Manilla Shire, New South Wales. Review of Marketing and Agricultural Economics, 58(2–3), 179–192.

    Google Scholar 

  • Skeldon, R. (1997). Migration and development: A global interpretation. Londo: Longman.

    Google Scholar 

  • Som, R. (1973). Recall lapse in demographic enquiries. New York: Asia Publishing House.

    Google Scholar 

  • Song, S. (2009). Migration, income inequality and the urban poor in China. The Chinese Economy, 4, 3–6.

    Article  Google Scholar 

  • State Council. (2014). China’s new national urbanization plan (2014–2020). Beijing: People’s Publishing House.

    Google Scholar 

  • Stott, P., Stone, D., & Allen, M. (2004). Human contribution to the European heatwave of 2003. Science, 432(7071), 610–614.

    Google Scholar 

  • Thomas, D., & Twyman, C. (2005). Equity and justice in climate change adaptation amongst natural resource dependant societies. Global Environmental Change, 15(2), 115–124.

    Article  Google Scholar 

  • Thomas, D., Twyman, C., Osbahr, H., & Hewitson, B. (2007). Adapting to climate change and variability in southern Africa: Farmer responses to intra-seasonal precipitation trends in South Africa. Climatic Change, 83, 301–322.

    Article  Google Scholar 

  • Tol, R. (2009). The economic effects of climate change. Journal of Economic Perspectives, 23, 29–51.

    Article  Google Scholar 

  • Tompkins, E., & Adger, W. (2004). Does adaptive management of natural resources enhance resilience to climate change? Ecology & Society, 9(2), 1–10.

    Google Scholar 

  • Uejio, C., Wilhelmi, O., Golden, J., Mills, D., Gulino, S., & Samenow, J. (2011). Intra-urban societal vulnerability to extreme heat: The role of heat exposure and the built environment, socioeconomics, and neighborhood stability. Health Place, 17(2), 498–507.

    Article  Google Scholar 

  • Vedwan, N., & Rhoades, R. (2001). Climate change in the Western Himalayas of India: A study of local perception and response. Climate Research, 19, 109–117.

    Article  Google Scholar 

  • Wang, J., Gao, W., Xu, S., & Yu, L. (2012). Evaluation of the combined risk of sea level rise, land subsidence, and storm surges on the coastal areas of Shanghai, China. Climatic Change, 115(3–4), 537–558.

    Article  Google Scholar 

  • Warner, K., Ehrhart, C., de Sherbinin, A., Adamo, S., & Chai-Onn, T. (2009). In Search of Shelter: Mapping the Effects of Climate Change on Human Migration and Displacement. Washington DC: the World Bank and CARE Inc.

  • Weinstein, N. (1989). Effects of personal experience on self protective behaviour. Psychological Bulletin, 105, 31–50.

    Article  Google Scholar 

  • Wheeler, S., Zuo, A., & Bjornlund, H. (2014). Australian irrigators’ recognition of the need for more environmental water flows and intentions to donate water allocations. Journal of Environmental Planning and Management, 57(1), 104–122.

    Article  Google Scholar 

  • Whitmarsh, L. (2008). Are flood victims more concerned about climate change than other people? The role of direct experience in risk perception and behavioural response. Journal of Risk Research, 11(3), 351–374.

    Article  Google Scholar 

  • Wong, K., & Zhao, X. (2001). Living with flood: victims’ perceptions in Beijiang, Guangdong, China. Area, 33(3), 190–201.

    Article  Google Scholar 

  • Xu, M., & Ma, D. (2009). Yangtze River Basin climate change vulnerability and adaptation report. Beijing: China Water & Power Press.

    Google Scholar 

  • Yardley, J., Sigal, R., & Kenny, G. (2011). Heat health planning: The importance of social and community factors. Global Environmental Change, 21(2), 670–679.

    Article  Google Scholar 

  • Young, I. (2000). Inclusion and democracy. Oxford: Oxford University Press.

    Google Scholar 

  • Zhang, W. (Ed.). (2008). Jiangsu statistical yearbook. Beijing: China Statistics Press.

    Google Scholar 

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Acknowledgments

This study was supported by the Australian Research Council Discovery project (DP110105522). We would like to express our great gratitude to four anonymous reviewers, Dr. Lori M. Hunter (Editor-in-Chief of Population and Environment), Dr. Heather Paull, and Dr Alec Zuo at University of South Australia for their constructive suggestions and thought-provoking comments on the early manuscript.

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  1. Discipline of Geography, Environment and Population, The University of Adelaide, Adelaide, SA, 5005, Australia

    Yan Tan, Xuchun Liu & Graeme Hugo

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Correspondence to Yan Tan.

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Tan, Y., Liu, X. & Hugo, G. Exploring relationship between social inequality and adaptations to climate change: evidence from urban household surveys in the Yangtze River delta, China. Popul Environ 36, 400–428 (2015). https://doi.org/10.1007/s11111-014-0223-2

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