An analysis of microscale segregation and socio-economic sorting in Gauteng

The negative social and spatial effects of apartheid are prominent legacies that shape urban development. This Occasional Paper analyses racial segregation and socio-economic sorting in Gauteng. In this research, a specific microscale analysis is added to the existing knowledge of segregation and socio-economic sorting patterns in Gauteng. A microscale representation of segregation is an important lens through which to view progress toward spatial transformation; it reveals how factors, such as residential expansion, the property market, and the character of neighbourhoods, influence racial segregation and socio-economic sorting.

The research includes three points of inquiry about racial-residential segregation and socio-economic sorting in Gauteng. The first considers the relationship between racial diversity and residential expansion. Between 1990 and 2020, the residential footprint of Gauteng increased by roughly 905 km². The study investigated whether residential growth contributes to desegregation or perpetuates segregation. The analysis shows that areas of residential expansion tend to reproduce the racial composition of the areas from which they expanded. However, public housing programmes and inclusionary housing policies hold significant potential for desegregation at multiple scales.

The second inquiry of this study analyses the extent to which racial mixing contributes to class mixing and income equality in desegregated neighbourhoods. In South African cities, middle-class neighbourhoods have been celebrated for becoming racially integrated. However, behind this undoubtedly important transformation, this study finds a largely unrecognised feature: in racially mixed wards, the mean household income of the white residents is significantly higher than the mean household income of black African residents. Racially-inflected income inequality in neighbourhoods therefore remains discernable even in the context of considerable racial desegregation.

The third inquiry is concerned with patterns of microscale socio-economic sorting in desegregated neighbourhoods, and specifically how this is associated with the housing characteristics that shape neighbourhoods. The analysis can illustrate how the affordability of housing and the social character of neighbourhoods influences socio-economic sorting.

Together, the three inquiries highlight continued segregation, but also nuances in the nature of desegregation in the Gauteng province at various macro- and microscales. Macroscale analysis in Gauteng shows that racial-residential segregation continues to happen in and around townships and is associated with low-cost housing developments. Desegregation is evident in the central suburban areas and is associated with mostly middle- to high-income housing. Although significant racial-residential desegregation has taken place in former whites-only neighbourhoods, the association between space and class in Gauteng has not changed significantly and spatial transformation is slow. The local-level, data-driven analysis reveals that desegregation is uneven in some neighbourhoods and the socio-economic sorting happens based on the characteristics (including quality, quantity and affordability) of the available housing stock.

The research argues that a multiscalar view of segregation and socio-economic sorting is essential to understand urban form and function. Microscale analysis reveals both barriers and opportunities for future spatial transformation. Residential expansion, whether by the public or private sectors, should be strategically driven with diversified housing at different affordability levels, while neighbourhood-level developments should foster socio-economic inclusion. In this way, desegregation and socio-economic integration are facilitated at different geographic scales, and more equitable access to opportunities in the city is enabled.

Suggested citation: Hamann, C. (2024). An analysis of microscale segregation and socio-economic sorting in Gauteng. GCRO Occassional Paper, April 2024. https://doi.org/10.36634/DZPT2443