Uncertainty Analysis Applied to the Representation of Multidimensional Social Phenomena

References

• Acharya, S., M. S. Setia, A. Palkar, D. Reddy, P. Keskar, P. Deoraj, M. Parthasarthy, P. Narayan, S. Rajan, and A. Saxena. 2021. Development of a composite indicator to prioritize districts for implementation of human immunodeficiency virus programmes in Maharashtra, India. The International Journal of Health Planning and Management 36 (1):71–82. doi: 10.1002/hpm.3066.
   PubMed Web of Science ®Google Scholar
• Amorim, M. C. d. C. T. 2018. Spatial variability and intensity frequency of surface heat island in a Brazilian city with continental tropical climate through remote sensing. Remote Sensing Applications: Society and Environment 9:10–6. doi: 10.1016/j.rsase.2017.11.001.
   Google Scholar
• Annoni, P., and D. Weziak-Bialowolska. 2016. A measure to target antipoverty policies in the European Union regions. Applied Research in Quality of Life 11 (1):181–207. doi: 10.1007/s11482-014-9361-z.
   PubMed Web of Science ®Google Scholar
• Arretche, M. 2018. Paths of inequality in Brazil: A half-century of changes. Springer, Cham.
   Google Scholar
• Arrondo, R., A. Cárcaba, and E. González. 2021. Drivers of subjective well-being in Spain: Are there gender differences? Applied Research in Quality of Life 16 (5):2131–54. doi: 10.1007/s11482-020-09862-x.
   Web of Science ®Google Scholar
• Artelaris, P. 2017. Geographies of crisis in Greece: A social well-being approach. Geoforum 84:59–69. doi: 10.1016/j.geoforum.2017.06.003.
   Web of Science ®Google Scholar
• Atkinson, A. B. 1970. On the measurement of inequality. Journal of Economic Theory 2 (3):244–63. doi: 10.1016/0022-0531(70)90039-6.
   Web of Science ®Google Scholar
• Atkinson, A. B. 2016. Inequality: What can be done. Practice 40 (2):289–92.
   Google Scholar
• Ayala, L., A. Jurado, and J. Pérez‐Mayo. 2011. Income poverty and multidimensional deprivation: Lessons from cross‐regional analysis. Review of Income and Wealth 57 (1):40–60. doi: 10.1111/j.1475-4991.2010.00393.x.
   Web of Science ®Google Scholar
• Beal, T., and D. Ervin. 2018. The geography of malnutrition. The Professional Geographer 70 (1):47–59. doi: 10.1080/00330124.2017.1310623.
   Web of Science ®Google Scholar
• Becker, G. S., and B. R. Chiswick. 1966. Education and the distribution of earnings. The American Economic Review 56 (1/2):358–69.
   Web of Science ®Google Scholar
• Becker, W., M. Saisana, P. Paruolo, and I. Vandecasteele. 2017. Weights and importance in composite indicators: Closing the gap. Ecological Indicators 80:12–22. doi: 10.1016/j.ecolind.2017.03.056.
   PubMed Web of Science ®Google Scholar
• Bernabé, E., A. L. Suominen-Taipale, M. M. Vehkalahti, A. Nordblad, and A. Sheiham. 2009. The T‐health index: A composite indicator of dental health. European Journal of Oral Sciences 117 (4):385–9. doi: 10.1111/j.1600-0722.2009.00649.x.
   PubMed Web of Science ®Google Scholar
• Boing, A. F., A. C. Boing, K. J. P. Wagner, and S. V. Subramanian. 2020. Narrowing geographic inequality in life expectancy in Brazil: A multilevel analysis between 1991 and 2010. Public Health 180:102–8. doi: 10.1016/j.puhe.2019.11.015.
   PubMed Web of Science ®Google Scholar
• Borsdorf, A., and R. Hidalgo. 2008. New dimensions of social exclusion in Latin America: From gated communities to gated cities, the case of Santiago de Chile. Land Use Policy 25 (2):153–60. doi: 10.1016/j.landusepol.2007.04.001.
   Web of Science ®Google Scholar
• Brazilian Institute of Geography and Statistics [IBGE]. 2010. Population census 2010. Accessed August 20, 2020. https://censo2010.ibge.gov.br/resultados.html.
   Google Scholar
• Brazilian Institute of Geography and Statistics [IBGE]. 2020. Population estimates. Accessed August 20, 2020. https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-populacao.html.
   Google Scholar
• Brooks, A. 2019. Clothing poverty: The hidden world of fast fashion and second-hand clothes. Zed Books Ltd, London.
   Google Scholar
• Bruto da Costa, A. 1998. Exclusões Sociais Cadernos Democráticos. Lisboa: Gradiva.
   Google Scholar
• Bucheli, F. 2021. Before entering adulthood: Developing an index of capabilities for young adults in Bogota. Applied Research in Quality of Life 16 (3):965–1002. doi: 10.1007/s11482-019-09781-6.
   Web of Science ®Google Scholar
• Caniato, A. M. P., and M. S. Capelasso. 2016. O desamparo dos adolescentes pobres na cidade de Maringá. Revista de Ciências Humanas 50 (2):375–96. doi: 10.5007/2178-4582.2016v50n2p375.
   Google Scholar
• Cardoso, R. d. S., and M. C. d. C. T. Amorim. 2015. Análise do clima urbano a partir da segregação socioespacial e socioambiental em Presidente Prudente-SP, Brasil. GEOSABERES: Revista de Estudos Geoeducacionais 6 (3):122–36.
   Google Scholar
• Carlsen, L. 2020. How happy are we actually? A posetic analysis of the world happiness index 2016–2019 Denmark as an exemplary case. International Journal of Community Well-Being 3 (3):311–22. doi: 10.1007/s42413-019-00044-8.
   Google Scholar
• Carmo, R. M. d. 2009. Um olhar sobre a pobreza: Vulnerabilidade e exclusão social no Portugal contemporâneo. Sociologia, Problemas e Práticas 59:163–7.
   Google Scholar
• Chakravorty, S. 2014. Fragments of inequality: Social, spatial and evolutionary analyses of income distribution. New York: Routledge.
   Google Scholar
• Chung, S., H. Jeon, A. Song, and J. H. Kim. 2019. Developmental trajectories and predictors of social exclusion among older Koreans: Exploring the multidimensional nature of social exclusion. Social Indicators Research 144 (1):97–112. doi: 10.1007/s11205-018-2045-6.
   Web of Science ®Google Scholar
• Cinelli, M., M. Spada, W. Kim, Y. Zhang, and P. Burgherr. 2021. MCDA index tool: An interactive software to develop indices and rankings. Environment Systems and Decisions 41 (1):82–109. doi: 10.1007/s10669-020-09784-x.
   PubMedGoogle Scholar
• Colton, J. S., and S. Holmes. 2018. A social justice theory of active equality for technical communication. Journal of Technical Writing and Communication 48 (1):4–30. doi: 10.1177/0047281616647803.
   Google Scholar
• Connolly, C., R. Keil, and S. H. Ali. 2021. Extended urbanisation and the spatialities of infectious disease: Demographic change, infrastructure and governance. Urban Studies 58 (2):245–63. doi: 10.1177/0042098020910873.
   Web of Science ®Google Scholar
• Deaton, A. 2013. The great escape. Princeton University Press, Princeton, Nova Jersey, EUA.
   Google Scholar
• Demo, P. 2003. Pobreza da pobreza. Rio de Janeiro: Editora Vozes.
   Google Scholar
• Dialga, I., and L. T. H. Giang. 2017. Highlighting methodological limitations in the steps of composite indicators construction. Social Indicators Research 131 (2):441–65. doi: 10.1007/s11205-016-1263-z.
   Web of Science ®Google Scholar
• Ekel, P., W. Pedrycz, and J. Pereira, Jr. 2020. Multicriteria decision-making under conditions of uncertainty: A fuzzy set perspective. Chinchester: John Wiley & Sons.
   Google Scholar
• El Gibari, S., T. Gómez, and F. Ruiz. 2019. Building composite indicators using multicriteria methods: A review. Journal of Business Economics 89 (1):1–24. doi: 10.1007/s11573-018-0902-z.
   Google Scholar
• Farias, F. O., D. C. Bargos, and L. F. Matias. 2016. Aplicação de geotecnologias no estudo da relação entre a valorização da terra urbana e a presença de áreas verdes na cidade de Paulínia (SP). Revista Brasileira de Cartografia 68 (2):275–87.
   Google Scholar
• Feng, Z., D. R. Phillips, and K. Jones. 2018. A geographical multivariable multilevel analysis of social exclusion among older people in China: Evidence from the China Longitudinal Aging Social Survey ageing study. The Geographical Journal 184 (4):413–28. doi: 10.1111/geoj.12274.
   Web of Science ®Google Scholar
• Ferrara, A. R., and R. Nisticò. 2013. Well-being indicators and convergence across Italian regions. Applied Research in Quality of Life 8 (1):15–44. doi: 10.1007/s11482-012-9180-z.
   Web of Science ®Google Scholar
• Freedman, L. 1969. Public housing: The politics of poverty. New York: Holt, Rinehart and Winston.
   Google Scholar
• Gao, P., S. Liu, W. Qi, and H. Qi. 2020. The nexus between poverty and the environment: A case study of Lijiang, China. Sustainability 12 (3):1066. doi: 10.3390/su12031066.
   Web of Science ®Google Scholar
• García-Vélez, D. F., M. A. Contreras-Jaramillo, T. P. Torres-Gutiérrez, and R. F. Correa-Quezada. 2020. Social exclusion in Ecuador with housing indicators: A regional analysis. In Entrepreneurship and the community, 159–76. Cham: Springer.
   Google Scholar
• Giambona, F., and E. Vassallo. 2013. Composite indicator of financial development in a benefit‐of‐doubt approach. Economic Notes 42 (2):171–202. doi: 10.1111/j.1468-0300.2013.12005.x.
   Google Scholar
• Glaeser, E. L., S. D. Kominers, M. Luca, and N. Naik. 2018. Big data and big cities: The promises and limitations of improved measures of urban life. Economic Inquiry 56 (1):114–37. doi: 10.1111/ecin.12364.
   Web of Science ®Google Scholar
• Goedhart, T., V. Halberstadt, A. Kapteyn, and B. Van Praag. 1977. The poverty line: Concept and measurement. The Journal of Human Resources 12 (4):503–20. doi: 10.2307/145372.
   Web of Science ®Google Scholar
• Greco, S., A. Ishizaka, M. Tasiou, and G. Torrisi. 2019. On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness. Social Indicators Research 141 (1):61–94. doi: 10.1007/s11205-017-1832-9.
   Web of Science ®Google Scholar
• Guerra, A., P. Marcio, and R. A. Silva. 2015. Atlas da exclusão social no Brasil: Dinâmica da exclusão social na primeira década do século XXI. São Paulo: Cortez Editora.
   Google Scholar
• Gutberlet, J., and A. Hunter. 2008. Social and environmental exclusion at the edge of São Paulo, Brazil. URBAN DESIGN International 13 (1):3–20. doi: 10.1057/udi.2008.2.
   Web of Science ®Google Scholar
• Haan, M., G. A. Kaplan, and T. Camacho. 1987. Poverty and health prospective evidence from the Alameda County study. American Journal of Epidemiology 125 (6):989–98. doi: 10.1093/oxfordjournals.aje.a114637.
   PubMed Web of Science ®Google Scholar
• Hagenaars, A. J. M., and B. M. S. Van Praag. 1985. A synthesis of poverty line definitions. Review of Income and Wealth 31 (2):139–54. doi: 10.1111/j.1475-4991.1985.tb00504.x.
   Google Scholar
• Healy, A. E. 2019. Measuring food poverty in Ireland: The importance of including exclusion. Irish Journal of Sociology 27 (2):105–27. doi: 10.1177/0791603519828313.
   Google Scholar
• Hungaro, A. A., A. Gavioli, R. Christóphoro, S. R. Marangoni, R. F. Altrão, A. L. Rodrigues, and M. L. F. de Oliveira. 2020. Homeless population: Characterization and contextualization by census research. Revista Brasileira de Enfermagem 73 (5):1–8. doi: 10.1590/0034-7167-2019-0236.
   Web of Science ®Google Scholar
• INPE. 2010. Catálogo de Imagens. Accessed August 20, 2020. http://www.dgi.inpe.br/CDSR/
   Google Scholar
• Iriarte, L., and L. Musikanski. 2019. Bridging the gap between the sustainable development goals and happiness metrics. International Journal of Community Well-Being 1 (2):115–35. doi: 10.1007/s42413-018-0012-2.
   Google Scholar
• Irwin, M. D. 2007. Territories of inequality. In The sociology of spatial inequality, ed. L. M. Lobao, G. Hooks, and A. R. Tickamyer, 85–109. SUNY Press, Albany, Nova York, EUA.
   Google Scholar
• Jannuzzi, P. M. d. 2012. Indicadores sociais no Brasil: Conceitos, fontes de dados e aplicações. São Paulo: Alínea.
   Google Scholar
• Kakwani, N. C. 1980. Income inequality and poverty. New York: World Bank.
   Google Scholar
• Kandylis, G. 2015. Levels of segregation, lines of closure: The spatiality of immigrants’ social exclusion in Athens. Local Economy: The Journal of the Local Economy Policy Unit 30 (7):818–37. doi: 10.1177/0269094215601819.
   Google Scholar
• Karagiannis, R., and G. Karagiannis. 2020. Constructing composite indicators with Shannon entropy: The case of Human Development Index. Socio-Economic Planning Sciences 70:100701. doi: 10.1016/j.seps.2019.03.007.
   Web of Science ®Google Scholar
• Keogh, S., S. O’Neill, and K. Walsh. 2021. Composite measures for assessing multidimensional social exclusion in later life: Conceptual and methodological challenges. Social Indicators Research 155 (2):389–410. doi: 10.1007/s11205-021-02617-7.
   Web of Science ®Google Scholar
• Kuc-Czarnecka, M., P. Samuele Lo, and A. Saltelli. 2020. Quantitative storytelling in the making of a composite indicator. Social Indicators Research 149:775–802. doi: 10.1007/s11205-020-02276-0.
   Web of Science ®Google Scholar
• Lago, L. C., and A. L. Cardoso. 2017. Segregation and real estate production. In Urban transformations in Rio de Janeiro, 127–41. Cham: Springer. doi: 10.1007/978-3-319-51899-2_8.
   Google Scholar
• Laparra, M., N. Z. Mutilva, and I. G. Lautre. 2021. The multidimensional conception of social exclusion and the aggregation dilemma: A solution proposal based on multiple correspondence analysis. Social Indicators Research, 158:637–666. doi: 10.1007/s11205-021-02707-6.
   PubMed Web of Science ®Google Scholar
• Lenoir, R. 1974. Les exclus: Un Français sur dix. Paris: Editions du Seuil.
   Google Scholar
• Levitas, R. 2006. The concept and measurement of social exclusion. In Poverty and social exclusion in Britain, ed. C. Pantazis, D. Gordon, and R. L. Policy Press, Bristol.
   Google Scholar
• Libório, M. P., P. Y. Ekel, O. d. S. Martinuci, L. R. Figueiredo, R. M. Hadad, R. de, M. Lyrio, and P. Bernardes. 2021. Fuzzy set based intra-urban inequality indicator. Quality & Quantity. doi: 10.1007/s11135-021-01142-6.
   Google Scholar
• Libório, M., O. Martinuci, P. Bernardes, and P. Ekel. 2018. Medidas e escalas de desigualdade de renda em perspectiva. GOT - Journal of Geography and Spatial Planning 15 (15):287–314. doi: 10.17127/got/2018.15.012.
   Google Scholar
• Libório, M. P., O. d. S. Martinuci, S. Laudares, R. d. M. Lyrio, A. M. C. Machado, P. Bernardes, and P. Ekel. 2020. Measuring intra-urban inequality with structural equation modeling: A theory-grounded indicator. Sustainability 12 (20):8610. doi: 10.3390/su12208610.
   Web of Science ®Google Scholar
• Libório, M. P., O. d. S. Martinuci, A. M. C. Machado, R. M. Hadad, P. Bernardes, and V. A. L. Camacho. 2021. Adequacy and consistency of an intraurban inequality indicator constructed through principal component analysis. The Professional Geographer 73 (2):282–96. doi: 10.1080/00330124.2021.1871766.
   Web of Science ®Google Scholar
• Libório, M. P., O. d. S. Martinuci, A. M. C. Machado, T. M. Machado-Coelho, S. Laudares, and P. Bernardes. 2020. Principal component analysis applied to multidimensional social indicators longitudinal studies: Limitations and possibilities. GeoJournal. doi: 10.1007/s10708-020-10322-0.
   Web of Science ®Google Scholar
• Liu, Y., and Y. Xu. 2016. A geographic identification of multidimensional poverty in rural China under the framework of sustainable livelihoods analysis. Applied Geography 73:62–76. doi: 10.1016/j.apgeog.2016.06.004.
   Web of Science ®Google Scholar
• Luque, M., S. Pérez-Moreno, J. A. Robles, and B. Rodriguez. 2017. Measuring child and maternal health in developing countries: A proposal of new hybrid MDG composite indices. Applied Research in Quality of Life 12 (3):737–58. doi: 10.1007/s11482-016-9487-2.
   Web of Science ®Google Scholar
• Martínez-Vega, J., S. Mili, and P. Echavarría. 2016. Assessing forest sustainability: Evidence from Spanish provinces. Geoforum 70:1–10. doi: 10.1016/j.geoforum.2015.12.013.
   Web of Science ®Google Scholar
• Martins, J. S. d. 1996. Exclusão social e a nova desigualdade. São Paulo: Paulus.
   Google Scholar
• Mashhoodi, B., D. Stead, and A. van Timmeren. 2019. Spatial homogeneity and heterogeneity of energy poverty: A neglected dimension. Annals of GIS 25 (1):19–31. doi: 10.1080/19475683.2018.1557253.
   Web of Science ®Google Scholar
• Mazziotta, M., and A. Pareto. 2019. Use and misuse of PCA for measuring well-being. Social Indicators Research 142 (2):451–76. doi: 10.1007/s11205-018-1933-0.
   Web of Science ®Google Scholar
• Melazzo, E. S., and R. B. Guimarães. 2010. Exclusão social em cidades brasileiros: Um desafio para as políticas públicas. São Paulo: Editora Unesp.
   Google Scholar
• Mendonca, M. B., and D. R. da Silva. 2020. Integration of census data based vulnerability in landslide risk mapping-The case of Angra dos Reis, Rio de Janeiro. International Journal of Disaster Risk Reduction 50:101884. doi: 10.1016/j.ijdrr.2020.101884.
   Web of Science ®Google Scholar
• Menezes Filho, N., and C. Kirschbaum. 2019. Education and inequality in Brazil. In Paths of inequality in Brazil, 69–88. Cham: Springer.
   Google Scholar
• Millar, J. 2007. Social exclusion and social policy research: Defining exclusion. In Multidisciplinary handbook of social exclusion research, ed. A. Dominic, J. Christian, and D. Gordon, 1–16. Chichester: John Wiley & Sons.
   Google Scholar
• Mitra, S., and D. L. Brucker. 2017. Income poverty and multiple deprivations in a high‐income country: The case of the United States. Social Science Quarterly 98 (1):37–56. doi: 10.1111/ssqu.12291.
   Web of Science ®Google Scholar
• Miyazaki, L. C. P., and J. O. R. Nunes. 2018. Social-environmental vulnerability analysis of the city of Presidente Prudente/SP. Brazilian Geographical Journal-Geosciences and Humanities Research Medium 9 (2):51–85.
   Google Scholar
• Mota, A. A. 2006. A cidade de Maringá e as instituições de ensino superior: Novos espaços de concentração e exclusão. Acta Scientiarum. Human and Social Sciences 28 (2):249–55. doi: 10.4025/actascihumansoc.v28i2.156.
   Google Scholar
• Naik, N., J. Philipoom, R. Raskar, and C. Hidalgo. 2014. Streetscore-predicting the perceived safety of one million streetscapes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 779–85, Columbus, Ohio, USA.
   Google Scholar
• Nardo, M., M. Saisana, A. Saltelli, and S. Tarantola. 2005. Tools for composite indicators building. European Comission, Ispra 15 (1):19–20.
   Google Scholar
• Nardo, M., M. Saisana, A. Saltelli, S. Tarantola, H. Hoffman, and E. Giovannini. 2008. Handbook on constructing composite indicators: Methodology and user guide. Paris, France: Organisation for Economic Cooperation and Development (OECD).
   Google Scholar
• Ntsalaze, L., and S. Ikhide. 2018. Rethinking dimensions: The South African multidimensional poverty index. Social Indicators Research 135 (1):195–213. doi: 10.1007/s11205-016-1473-4.
   Web of Science ®Google Scholar
• Nunes, L. F., and F. L. de Paula Santil. 2020. A segregação socioespacial gerada pela produção do espaço habitacional na cidade de Maringá/PR. Geografia em Atos (Online) 3 (18):78–100. doi: 10.35416/geoatos.v3i18.6980.
   Google Scholar
• Otoiu, A., A. Pareto, E. Grimaccia, M. Mazziotta, and S. Terzi. 2021. Open issues in composite indicators. A starting point and a reference on some state-of-the-art issues, vol. 3. Roma TrE-Press, Roma.
   Google Scholar
• Otoiu, A., E. Titan, and R. Dumitrescu. 2014. Are the variables used in building composite indicators of well-being relevant? Validating composite indexes of well-being. Ecological Indicators 46:575–85. doi: 10.1016/j.ecolind.2014.07.019.
   Web of Science ®Google Scholar
• Oxford Poverty and Human Development Initiative. 2018. Global Multidimensional Poverty Index 2018: The most detailed picture to date of the world’s poorest people. Oxford: University of Oxford.
   Google Scholar
• Park, S., J. Cho, and Y. Chen. 2019. Subsidized housing and geographic accessibility to neighborhood resources for low-income older people: From later year social exclusion perspective. Geoforum 106:297–304. doi: 10.1016/j.geoforum.2019.09.002.
   Web of Science ®Google Scholar
• Paugam, S. 1998. Poverty and social exclusion: A sociological view. In The future of European welfare, ed. M. Rhodes and Y. Mény, 41–62. London: Palgrave Macmillan.
   Google Scholar
• Pearson, K. 1901. LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 2 (11):559–72. doi: 10.1080/14786440109462720.
   Google Scholar
• Piketty, T. 2015. The economics of inequality. Harvard University Press, Cambridge, Massachusetts, EUA.
   Google Scholar
• Piketty, T. 2018. Capital in the twenty-first century. Harvard University Press, Cambridge, Massachusetts, EUA.
   Google Scholar
• Qiao, M., C. Wong, and W. Zheng. 2019. Sustainable urbanisation and community well-being in suburban neighbourhoods in Beijing, China. International Journal of Community Well-Being 2 (1):15–39. doi: 10.1007/s42413-019-00019-9.
   Google Scholar
• Rego, R. L. O desenho urbano de Maringá e a idéia de cidade-jardim. Acta Scientiarum. Technology. 2001. 23, 1569–1577. doi: 10.4025/actascitechnol.v23i0.2801.
   Google Scholar
• Rigoldi, K. C., and V. Lima. 2020. A Influência da Gestão de Resíduos Sólidos na Qualidade Ambiental e nas Desigualdades Socioespaciais de Maringá–PR. Brazilian Geographical Journal 11 (1):85–96. doi: 10.14393/BGJ-v11n1-a2020-55724.
   Google Scholar
• Robinson, C., L. Sarah, and S. Bouzarovski. 2019. The spatially varying components of vulnerability to energy poverty. Annals of the American Association of Geographers 109 (4):1188–207. doi: 10.1080/24694452.2018.1562872.
   Web of Science ®Google Scholar
• Rodrigues, A. L. 2004. Características do processo de urbanização de Maringá, PR: Uma cidade de porte médio. Cadernos Metrópole 12:95–121.
   Google Scholar
• Rundle, A. G., M. D. M. Bader, C. A. Richards, K. M. Neckerman, and J. O. Teitler. 2011. Using Google Street View to audit neighborhood environments. American Journal of Preventive Medicine 40 (1):94–100. doi: 10.1016/j.amepre.2010.09.034.
   PubMed Web of Science ®Google Scholar
• Saisana, M., and S. Tarantola. 2002. State-of-the-art report on current methodologies and practices for composite indicator development, vol. 214. Ispra: European Commission, Joint Research Centre, Institute for the Protection and the Security of the Citizen, Technological and Economic Risk Management Unit.
   Google Scholar
• Saldner, S. 2020. Contextualising reintegration: Conceptualising and measuring ex-combatant reintegration relative to civilians. Civil Wars 22 (4):453–77. doi: 10.1080/13698249.2020.1765540.
   Web of Science ®Google Scholar
• Salesses, P., K. Schechtner, and C. A. Hidalgo. 2013. The collaborative image of the city: Mapping the inequality of urban perception. PLoS One 8 (7):e68400. doi: 10.1371/journal.pone.0068400.
   PubMed Web of Science ®Google Scholar
• Santos, M. 2002. A natureza do espaço: Técnica e tempo, razão e emoção. São Paulo: Edusp.
   Google Scholar
• Santos, M. E., and P. Villatoro. 2018. A multidimensional poverty index for Latin America. Review of Income and Wealth 64 (1):52–82. doi: 10.1111/roiw.12275.
   Web of Science ®Google Scholar
• Scharf, T., C. Phillipson, and A. E. Smith. 2005. Social exclusion of older people in deprived urban communities of England. European Journal of Ageing 2 (2):76–87. doi: 10.1007/s10433-005-0025-6.
   PubMedGoogle Scholar
• Schwartzman, S. 2006. Poverty, social exclusion and modernity. 187. Oslo University Summer Schools, Oslo.
   Google Scholar
• Serneels, P., and S. Dercon. 2021. Aspirations, poverty, and education. Evidence from India. The Journal of Development Studies 57 (1):163–83. doi: 10.1080/00220388.2020.1806242.
   Web of Science ®Google Scholar
• Shalamzari, M. J., and W. Zhang. 2018. Assessing water scarcity using the water poverty index (WPI) in Golestan province of Iran. Water 10 (8):1079. doi: 10.3390/w10081079.
   Web of Science ®Google Scholar
• Shi, C., and K. C. Land. 2021. The data envelopment analysis and equal weights/minimax methods of composite social indicator construction: A methodological study of data sensitivity and robustness. Applied Research in Quality of Life 16 (4):1689–716. doi: 10.1007/s11482-020-09841-2.
   Web of Science ®Google Scholar
• Singer, P. 1998. Globalização e desemprego: Diagnóstico e alternativas. São Paulo: Editora Contexto.
   Google Scholar
• Smyth, C. G., and S. A. Royle. 2000. Urban landslide hazards: Incidence and causative factors in Niterói, Rio de Janeiro State, Brazil. Applied Geography 20 (2):95–118. doi: 10.1016/S0143-6228(00)00004-7.
   Web of Science ®Google Scholar
• Sorato, G. H., and V. Lima. 2019. Mapping of Rio Pirapó’s hydrographic basin through Google Earth Engine-Code Editor. Brazilian Geographical Journal 10 (1):113–30.
   Google Scholar
• Spoor, M. 2013. Multidimensional social exclusion and the ‘rural‐urban divide’ in Eastern Europe and Central Asia. Sociologia Ruralis 53 (2):139–57. doi: 10.1111/soru.12008.
   Web of Science ®Google Scholar
• Sposati, A. 1996. Social exclusion/inclusion map of the City of São Paulo. São Paulo: EDUC.
   Google Scholar
• Stiglitz, J. E. 2015. The price of inequality: How today’s divided society endangers our future, 379–99. In: Ramanathan, V., & Sorondo, M. S. (eds). Sustainable Humanity: Sustainable Nature; Our Responsibility. Pontificia Academia, Vaticano.
   Google Scholar
• Stiglitz, J. E. 2015. The price of inequality: How today’s divided society endangers our future, 379–99.
   Google Scholar
• Taschner, G. 2010. Cultura do consumo, cidadania e movimentos sociais. Ciências Sociais Unisinos 46 (1):47–52. doi: 10.4013/csu.2010.46.1.06.
   Google Scholar
• Travassos, G. F., A. B. Coelho, and M. P. Arends-Kuenning. 2020. The elderly in Brazil: Demographic transition, profile, and socioeconomic condition. Revista Brasileira de Estudos de População 37 (37):e0129.
   Google Scholar
• van Bergen, A. P., S. J. Hoff, H. Schreurs, A. van Loon, and A. M. van Hemert. 2017. Social Exclusion Index-for Health Surveys (SEI-HS): A prospective nationwide study to extend and validate a multidimensional social exclusion questionnaire. BMC Public Health 17 (1):1–13. doi: 10.1186/s12889-017-4175-1.
   PubMedGoogle Scholar
• Van Phan, P., and M. O’Brien. 2019. Multidimensional wellbeing inequality in a developing country: A case study of Vietnam. Social Indicators Research 145 (1):157–83. doi: 10.1007/s11205-019-02104-0.
   Web of Science ®Google Scholar
• Van Regenmortel, S., L. De Donder, A. S. Smetcoren, D. Lambotte, N. D. Witte, and D. Verté. 2018. Accumulation of disadvantages: Prevalence and categories of old-age social exclusion in Belgium. Social Indicators Research 140 (3):1173–94. doi: 10.1007/s11205-017-1817-8.
   Web of Science ®Google Scholar
• Whelan, C. T., B. Nolan, and B. Maître. 2014. Multidimensional poverty measurement in Europe: An application of the adjusted headcount approach. Journal of European Social Policy 24 (2):183–97. doi: 10.1177/0958928713517914.
   Web of Science ®Google Scholar
• Xu, Z., Z. Cai, S. Wu, X. Huang, J. Liu, J. Sun, S. Su, and M. Weng. 2019. Identifying the geographic indicators of poverty using geographically weighted regression: A case study from Qiandongnan Miao and Dong autonomous prefecture, Guizhou, China. Social Indicators Research 142 (3):947–70. doi: 10.1007/s11205-018-1953-9.
   Web of Science ®Google Scholar
• Yigitcanlar, T., A. Mohamed, M. Kamruzzaman, and A. Piracha. 2019. Understanding transport-related social exclusion: A multidimensional approach. Urban Policy and Research 37 (1):97–110. doi: 10.1080/08111146.2018.1533461.
   Web of Science ®Google Scholar
• Zhou, H., S. He, Y. Cai, M. Wang, and S. Su. 2019. Social inequalities in neighborhood visual walkability: Using street view imagery and deep learning technologies to facilitate healthy city planning. Sustainable Cities and Society 50:101605. doi: 10.1016/j.scs.2019.101605.
   Web of Science ®Google Scholar
• Zimek, A., and P. Filzmoser. 2018. There and back again: Outlier detection between statistical reasoning and data mining algorithms. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8 (6):e1280.
   Web of Science ®Google Scholar