Abstract
Original language | English |
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Publication status | Published - Apr 2018 |
Event | Academy of Management Specialized Conference 2018: Big Data and Managing in a Digital Economy - University of Surrey, Surrey, United Kingdom Duration: 18 Apr 2018 → 20 Apr 2018 http://bigdata.aom.org/ehome/index.php?eventid=245645& |
Conference
Conference | Academy of Management Specialized Conference 2018 |
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Abbreviated title | AOM big data 2018 |
Country | United Kingdom |
City | Surrey |
Period | 18/04/18 → 20/04/18 |
Internet address |
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Predictive policing : How algorithms inscribe the understanding of crime in police work. / Waardenburg, L.; Sergeeva, A.; Huysman, Marleen.
2018. Abstract from Academy of Management Specialized Conference 2018, Surrey, United Kingdom.Research output: Contribution to Conference › Abstract › Professional
TY - CONF
T1 - Predictive policing
T2 - How algorithms inscribe the understanding of crime in police work
AU - Waardenburg, L.
AU - Sergeeva, A.
AU - Huysman, Marleen
PY - 2018/4
Y1 - 2018/4
N2 - This research focuses on the consequences of the shift to data-driven work for daily police work. Our ongoing ethnographic field study of a team of police officers shows that predictive policing algorithms inscribe a different crime theory-in-use-i.e., the understanding of why crime occurs and how it should be prevented-that influences daily police work. Instead of having a social-environmental crime perspective, police officers are shifting attention towards features of the physical environment as explanations of why crime occurs. Our preliminary findings have implications for debates on the consequences of data analytics by showing how the different theory-in-use inscribed in data-driven work influences traditional work practices.
AB - This research focuses on the consequences of the shift to data-driven work for daily police work. Our ongoing ethnographic field study of a team of police officers shows that predictive policing algorithms inscribe a different crime theory-in-use-i.e., the understanding of why crime occurs and how it should be prevented-that influences daily police work. Instead of having a social-environmental crime perspective, police officers are shifting attention towards features of the physical environment as explanations of why crime occurs. Our preliminary findings have implications for debates on the consequences of data analytics by showing how the different theory-in-use inscribed in data-driven work influences traditional work practices.
M3 - Abstract
ER -