Constructing Crime in a Database: Big Data and the Mangle of Social Problems Work

This paper argues for programmatic change within social constructionist approaches to social problems by attending to materiality in the theoretical conception of social context. To illustrate how this might be done, we place the interplay between social problems construction and technology (what we...

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Veröffentlicht in:Qualitative sociology review : QSR Jg. 11; H. 2; S. 180 - 195
Hauptverfasser: Sanders, Carrie B., Christensen, Tony, Weston, Crystal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Lodz Uniwersytet Lodzki, Wydzial Ekonomiczno-Socjologiczny, Instytut Socjol 01.04.2015
Schlagworte:
Algorithms
Big Data
Constructionism
Crime
Data analysis
Data base management
Intelligence
Materialism
Problem solving
Social environment
Social problems
Social psychology
Sociology
ISSN:1733-8077, 1733-8077
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Zusammenfassung:This paper argues for programmatic change within social constructionist approaches to social problems by attending to materiality in the theoretical conception of social context. To illustrate how this might be done, we place the interplay between social problems construction and technology (what we refer to as the mangle of social problems work) at its center by examining how the advent of “big data” is impacting the construction of social problems. Using the growing field of intelligence-led policing (ILP) as our illustrative example, we will examine four effects the large scale collection and analysis of data has on the way social problems claims are made. We begin by arguing that big data offers a new method by which putative problems are discovered and legitimized. We then explore how large data sets and algorithmic data analysis are increasingly used for predicting future problems. Following this, we illustrate how big data is used to construct and implement solutions to future problems. Lastly, we use the interplay between big data and those who use it to illustrate “the mangle of social problems work,” where data is made meaningful and actionable through the interpretive and analytic processes of analysts and police officers.
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ISSN:1733-8077
1733-8077
DOI:10.18778/1733-8077.11.2.12