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PP 350
Not Just a Number? NEETs, Data and Datalogical Systems
H. Thornham
1
, E. Gómez Cruz
2
1
University of Leeds, Media and Communication, Leeds, United Kingdom
2
RMIT, Digital Ethnography Research Centre, Melbourne, Australia
This paper draws on a four year empirical research project with NEET populations (16–24 year olds not in education, employment or training), in order to
engage with issues around identification, data and metrics produced through datalogical systems. Our aim is to bridge contemporary discourses around
data, digital bureaucracy and datalogical systems with empirical material drawn from a long-term ethnographic project with NEET groups in Leeds, UK in
order to highlight the way datalogical systems ideologically and politically shape peoples lives. We argue that the contemporary arguments around data
and big data in particular are part of a long-term trend towards digital bureaucratisation (a term borrowed from David Graeber 2015) and datalogical sys‑
tems (see Clough et. al 2015, Thrift 2007). At the same time, juxtaposing empirical material with theoretical and conceptual considerations also articulates
what is at stake here in terms of digital inequalities and the reach of these systems ideologically and politically as they shape peoples lives. Taken together,
our research raises a number of questions about the politics of datalogical systems that are used to measure and capture experiences and activities of certain
populations in particular ways and that also generate normative and ideological behavioural standards and practices. Our research also demands that we
consider and question our own roles in the long-term normative constitution of data not least because our research also implicates us as digital researchers
and raises a number of epistemological issues around the politics of research and digital methods. In the end, we ask about our own (active) roles as digital
researchers in the long-term trend towards digital bureaucratization and datalogical systems, as well as our complicity in constructing the values of those
systems as normative.We argue that if we are to seek interventions that move us beyond our own complicity in being primarily and ultimately reconfigured
through the values of that datalogical system, maybe we need to start much closer to home.