The datafication revolution in criminal justice: An empirical exploration of frames portraying data-driven technologies for crime prevention and control - Anita Lavorgna (SAGE Publishing, 2021)
The proliferation of big data analytics in criminal justice suggests that there are positive frames and imaginaries legitimising them and depicting them as the panacea for efficient crime control. Criminological and criminal justice scholarship has paid insufficient attention to these frames and their accompanying narratives. To address the gap created by the lack of theoretical and empirical insight in this area, this article draws on a study that systematically reviewed and compared multidisciplinary academic abstracts on the data-driven tools now shaping decision-making across several justice systems. Using insights distilled from the study, the article proposes three frames (optimistic, neutral, oppositional) for understanding how the technologies are portrayed. Inherent in the frames are a set of narratives emphasising their ostensible status as vital crime control mechanisms. These narratives obfuscate the harms of data-driven technologies and evince idealistic imaginaries of their capabilities. The narratives are bolstered by unequal structural arrangements, specifically the unevenly distributed digital capital with which some are empowered to participate in technology development for criminal justice application and other forms of penal governance. In unravelling these issues, the article advances current understanding of the dynamics that sustain the depiction of data-driven technologies as prime crime prevention and law enforcement tools.