You don’t have to live next to me

Demobilising individualistic bias in computational approaches to urban segregation

The primary image discusses the interconnected four spheres of perpetuation of individualistic bias – Education, Computational modelling, policy-making and public discourse. Education especially on computational methods, continues to be an elitist project, which directly shapes who get to inform policy-making and become power brokers that determines peoples’ lives within a city. This is also reflected in what is reproduced in public discourse.

The explicit and implicit building blocks of computational approaches to segregation

This image introduces the readers to the spatial context wherein we are studying the different ways segregation impacts “agents” – People with multifaceted identities are here modelled as anonymous agents and reduced to single identity lines, such as race, caste or ethnicity. Resources too are gatekept by power brokers who decide how to distribute it and in extension shape policy.

The Schelling model (an example of other urban models) abstracts the ground reality and everyday experiences, obscuring the different processes that actually lead to segregated neighbourhoods.

Here, the timesteps of the Schelling model of both the ingroup (residents moving into a gentrifying neihbourhood) and outgroup (residents moving out to a more deteriorated neighbourhood) agents are shown alongside the ground reality in these two neighbourhoods.

This image expands on the benefits of living a segregated life

Spatial inequalities exacerbate the skewed resource distribution along the different axes drawn above in the form of cards – such as labour, education, health, social networks, and gated resources. These axes manifest differently in the advantaged (top) and disadvantaged(bottom) neighbourhoods.