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      Informal settlements, the emerging response to COVID and the imperative of transforming the narrative


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          The COVID pandemic has exposed several faultlines of urbanism in India. This paper is a narrative of the remarkable continuities between the past legacies of governance of informal settlements, pandemic response and emerging ideas of alternate urbanisms and their inability to address issues of inequity, exclusion and vulnerability. The pandemic and the resultant situation exposes the limits of the current policies, programming linked to informal settlements, their imagination of informality and outlines the urgent need to escape the trap of bracketing of informal settlements as an ‘issue’ within itself delinked from the dynamic and ever-changing processes of urbanization through community led policy responses and effective local governance. In the absence of effective state response, informal settlements authored their own script of coping with the challenges thrown by the pandemic; their presence, participation and centrality in scripting future policies is a much-needed transformation of the narrative.

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            Becoming a Slum: From Municipal Colony to Illegal Settlement in Liberalization-Era Mumbai

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              Is Open Access

              Survey-based socio-economic data from slums in Bangalore, India

              In 2010, an estimated 860 million people were living in slums worldwide, with around 60 million added to the slum population between 2000 and 2010. In 2011, 200 million people in urban Indian households were considered to live in slums. In order to address and create slum development programmes and poverty alleviation methods, it is necessary to understand the needs of these communities. Therefore, we require data with high granularity in the Indian context. Unfortunately, there is a paucity of highly granular data at the level of individual slums. We collected the data presented in this paper in partnership with the slum dwellers in order to overcome the challenges such as validity and efficacy of self reported data. Our survey of Bangalore covered 36 slums across the city. The slums were chosen based on stratification criteria, which included geographical location of the slum, whether the slum was resettled or rehabilitated, notification status of the slum, the size of the slum and the religious profile. This paper describes the relational model of the slum dataset, the variables in the dataset, the variables constructed for analysis and the issues identified with the dataset. The data collected includes around 267,894 data points spread over 242 questions for 1,107 households. The dataset can facilitate interdisciplinary research on spatial and temporal dynamics of urban poverty and well-being in the context of rapid urbanization of cities in developing countries.

                Author and article information

                J. Soc. Econ. Dev.
                Journal of Social and Economic Development
                Springer India (New Delhi )
                3 November 2020
                : 1-10
                GRID grid.419871.2, ISNI 0000 0004 1937 0757, School of Habitat Studies, Tata Institute of Social Sciences, ; Mumbai, India
                © Institute for Social and Economic Change 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                Research Paper


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