Software-sorted geographies

By S. Graham. 2005

409 citations recorded by the source corpus.

This paper explores the central role of computerized code in shaping the social and geographical politics of inequality in advanced societies. The central argument is that, while such processes are necessarily multifaceted, multiscaled, complex and ambivalent, a great variety of `software-sorting' techniques is now being widely applied in efforts to try to separate privileged and marginalized groups and places across a wide range of sectors and domains. This paper's central demonstration is that the overwhelming bulk of software-sorting applications is closely associated with broader transformations from Keynesian to neoliberal service regimes. To illustrate such processes of software-sorting, the paper analyses recent research addressing three examples of software-sorting in practice. These address physical and electronic mobility systems, online geographical information systems (GIS), and face-recognition closed circuit television (CCTV) systems covering city streets. The paper finishes by identifying theoretical, research and policy implications of the diffusion of software-sorted geographies within which computerized code continually orchestrates inequalities through technological systems embedded within urban environments.

View Paper: https://www.semanticscholar.org/paper/9f1e22dd34015608654d59504559b688144e9ec4

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Citations in the corpus

The ethics of smart cities and urban science (2016, background): “Or in the case of urban science to socially sort places to receive certain policy interventions or marketing as practised by the geodemographics industry [71].”
Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (2022, background): “Computing research has traced how marginalized communities — referring to communities that face structural forms of social exclusion [130] — disproportionately experience sociotechnical harms from algorithmic systems [90, 96].”
Digital turn, digital geographies? (2018, background): “One manifestation of such control is socio-spatial sorting, whereby people are evaluated via algorithms that calculate and enforce differential access with respect to perceived worth (e.g., customer, credit and crime profiling) (Graham, 2005).”
Programming Environments: Environmentality and Citizen Sensing in the Smart City (2014, background): “…the intersection of computation and space, making the point that computing—often in the form of software or code—has a considerable influence on the ways in which spatial processes unfold or even cease to function when software fails (Graham, 2005; Kitchin and Dodge, 2011; Thrift and French, 2002).”
Transactions After 9/11: The Banal Face of the Preemptive Strike (2008, background): “It is important to emphasise here that we are not arguing that the use of transactions data after 9/11 is unique or unprecedented – there is ample historical evidence of risk profiling via data prior to 9/11 (Haggerty and Ericson 2000; Andreas and Snyder 2000; Thrift and French 2002; Graham 2005).”
Power through the algorithm? Participatory web cultures and the technological unconscious (2009, background): “Web 2.0 now needs to be incorporated into the analysis of the ‘very guts’ (Graham, 2005: 10) of these emergent systems that constitute the ‘technological unconscious’ (Thrift, 2005). described elsewhere as the ‘products of the global culture industry’ and the ‘sociology of objects’ (Lash and Lury,…”
Critical Data Studies: A dialog on data and space (2016, background): “Code and data mediate, saturate and sustain global capital (Graham, 2005).”
Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction (2022, background): “, [80, 85]), including the inequitable distribution of resources [54], hierarchical representations of people and communities [215], disparate performance based on identity [124], and entrenchment of social inequalities (e.”
A New Algorithmic Identity (2011, background): “This means that those who are not categorized as male may not experience the same advertisement and opportunities, enacting the consequences of what was already referred to as ‘software-sorting’ (Graham, 2005).”
Towards Critical Data Studies: Charting and Unpacking Data Assemblages and Their Work (2014, background): “…sort customers, identifying some for preferential treatment and excluding others, and to predict the likelihood that customers might be able to meet payments, or their projected lifetime value if they remain loyal, and how likely they are to move their custom (Graham 2005; Minelli et al. 2013).”
Engaging rational discrimination: exploring reasons for placing regulatory constraints on decision support systems (2010, unknown): “63 Jost et al. (2008). 64 Wilson (2005).”