The data deposited include: 1. South Africa wards on consistent spatial boundaries for 2001 and 2011 with Index of Multiple deprivation and domain scores (ArcGIS TM shapefile format ward boundaries, attributes in comma separated values (csv) format) 2. Cape Town population grid for 2001: unemployment rates (ArcGIS TM shapefile format grid square boundaries with linked atrributes) 3. Cape Town population grid for 2011: unemployment rates (ArcGIS TM shapefile format grid square boundaries with linked atrributes) In each case, a metadata file is provided in comma separated values (csv) format. The project also funded inclusion of a bespoke question on inequalities in the 2017 round of the South African Social Attitudes Survey (SASAS). The 2017 SASAS data are available through the Human Sciences Research Council: http://www.hsrc.ac.za/en/departments/sasasThis project provides an innovative analysis of how people's lived experiences of socio-economic inequality are shaped by the complex dynamics of urban change in South Africa and how such experiences in turn shape the country's urban social fabric. The collaboration was between Queen's University Belfast (QUB) (the project moved from the University of Liverpool (UoL)), Southern African Social Policy Research Insights (SASPRI) and the Human Sciences Research Council (HSRC) and comprised an inter-disciplinary team (Geography, Demography, Social Policy and Urban Planning) with complementary areas of expertise in relation to socioeconomic inequality and urban population change. The project relates to the themes of diversity, migration and practice. South Africa continues to be a deeply unequal society with markedly different standards of living across population groups (or race) and spatially. The current evidence base concerning inequality in South Africa is relatively small, and says little about the changing geographies of inequalities, the associated impacts which are felt on the ground as individuals' 'lived experience' of inequality, and consequences for the urban social fabric of the country. In this project quantitative and qualitative methods were combined to examine the interplay between urban spatial transformation and social attitudes towards inequality, attachment to place, and social inclusion. The three-year research programme had four parts: (i) Mapping the changing geographies of inequality across South Africa between 1996 and 2011. Measures of spatial evenness and clustering were generated to characterise the spatial context of areas. (ii) Focus groups were undertaken in Cape Town to explore the factors and processes that shape people's experiences of inequality, and whether people's experiences of inequality affect their attachment to place and sense of social inclusion. (iii) Surveying people's experiences of inequality and their attitudes to inequality. A new module of inequality-related questions was included in the 2017 round of the nationally representative South African Social Attitudes Survey (SASAS). (iv) Testing whether people's attitudes to inequality are associated with their experiences of inequality using new/refined dependent and independent variables in multilevel regression models. The quantitative spatial measures developed in (i) were linked to the SASAS 2017 data to develop a more nuanced analytical appreciation of how inequality impacts on residents' lives and their attitudes about inequality and redress. The results of this project offer important new insights which will support national and local government when developing evidence-based policies to tackle inequality. It will enable policies in the areas of housing, urban planning and poverty alleviation to be informed by analysis of the lived experience of inequality, derived from an inter-play of highly context-specific qualitative enquiry and cutting-edge quantitative techniques.

Census wards and population grids derived from the 2001 and 2011 Censuses of South Africa. Questions incorporated in the 2017 round of the South African Social Attitudes Survey (SASAS) - a nationally representative, repeated cross-sectional survey.