Building Equality: A "Litmus Test" for Recognising and Evidencing Inequalities and Segregation in the Built Environment
In: Urban Planning, Band 8, Heft 1, S. 372-387
Abstract
The current convergence of global challenges, particularly the climate change emergency, the Covid-19 pandemic, and the Black Lives Matter movement, have highlighted the need for a new lens to challenge and interrogate key urban planning assumptions related to spatial urban inequality. Yet urban inequality is often and invariably described from a limited economic perspective, commonly interpreted and measured as income inequality. This is an overtly statistical measure, or Gini-Type index, often giving limited and unsatisfactory results. Yet, in practice, the spatial distribution and concentration of income inequality is a multi-scalar, multi-variant, and multi-disciplinary issue and has links with other and wider dimensions of inequality and well-being. As such, this article argues for a holistic understanding of urban inequality that goes beyond narrow empirical and quantitative models. It presents collaborative research that aims to impact the actions of urban professionals, to accurately identify and adequately respond to urban inequalities. Through the establishment of an interdisciplinary expert panel, we have uncovered a series of provisional mechanisms and responses to aid practitioners to achieve more spatial equality. We introduce an integrated analytical method, the "litmus test," that acts as a planning tool for understanding, evaluating, and responding to inequalities and segregation present in the built environment. This novel methodology and procedural framework will assist us in (a) identifying and defining different forms of inequality and segregation beyond the current scope of physical and agency-based forms; (b) measuring and demonstrating the latter with a combination of qualitative, empirical sources that are materially significant in supporting and evidencing planning strategies; and (c) setting out a series of planning and built environment specific responses.
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