TY - ABST

T1 - Grey gumshoes

AU - Schwarz, Benjamin

AU - Bagger, Christoffer

AU - Søe, Sille Obelitz

N1 - Conference code: 10

PY - 2024/9

Y1 - 2024/9

N2 - Abstract:“Data, data, data! … I can’t make bricks without clay.”- The detective Sherlock Holmes in the Adventure of the Copper Beeches (Doyle, 1892)Recent scholarship has brought attention the role of datafication and automation in digital welfare states (Bagger et al., 2023; Kaun et al., 2022) and how this increases inequalities (Iversen & Rehm, 2022). In this paper, we argue that discussions about how digital systems reconfigure welfare must be supplemented by an account of the caseworkers working on behalf of these systems. Empirically, we proceed from on an organizational ethnographic investigation into the Danish authority, Payout Denmark and select Danish municipalities by the first author. These organizations are responsible for payment of various benefits to Danish citizens, and investigating potential fraud with these (Zajko, 2023). This makes these sites both central to the tenets of the welfare state (Esping-Andersen, 1990) and sites fraught with moral conundrums for citizens and caseworkers alike (Ranchordás, 2022). We present an exploration of how the caseworkers perform “detective work” in extension of – and addition to – the data collection and automated decision-support systems which surround them. We derive the figure of the “detective” as a “sensitizing concept” (Blumer, 2006) from the fieldwork. Metaphors and images of detection abound in the self-representations of the work and methods used by caseworkers. Theoretically, we draw on a combination of policing studies, intelligence studies, and cultural studies more broadly. From policing studies, we draw on the concept of ‘plural policing’ to discuss how police functions have disseminated, in this case, into other state and municipal authorities (Stenström, 2020). From intelligence studies, we derive insights about how investigators justify their actions in the face of “missing” or “absent” data as well as how they load their interpretations with claims of objectivity (Genot, 2018; Rønn, 2022). Finally, from general cultural studies, our central argument is that this self-perception of being a detective has profound implications for the role of caseworkers. The figure of the detective is viewed both as authoritative and rational (Saler, 2012) and overlaps with the figure of the police officer as an agent of social order (Hall et al., 2017; Hatrick & González, 2022). Furthermore, this is a figure who is justified in intimately investigating others (Rønn & Søe, 2019; Vitale, 2021) by means of datafication if necessary (O’Neill, 2016). We make the case that the detective-like caseworker is a productive prism for exploring the emerging automated welfare state – a state that incessantly reassesses its citizens and their relative deservingness (Tošić & Streinzer, 2022) while painting such practices in non-moralistic and non-controversial terms. The central implication of our study is that the increased call for data-supported automated decision-making in welfare states should indeed be supplemented by a human-centric focus (Lomborg, Kaun & Scott Hansen, 2023), one which can consider the agency, discretionary power (Dubois, 2019) and, more sweepingly, the ‘world-images’ (Boland & Griffin, 2018) of caseworkers and bureaucrats. As previous research has shown (e.g. Madsen, 2018), bureaucrats may have diverging visions of data, even in the age of automated welfare. References:Bagger, C., Einarsson, A. M., Andelsman Alvarez, V., Klausen, M., & Lomborg, S. (2023). Digital Resignation and the Datafied Welfare State. Big Data & Society, 10(2). https://doi.org/10.1177/20539517231206806Blumer, H. (2006). What Is Wrong with Social Theory? In Sociological Methods. Routledge.Boland, T., & Griffin, R. (2018). The purgatorial ethic and the spirit of welfare. Journal of Classical Sociology, 18(2), 87-103. https://doi.org/10.1177/1468795X17722079 Doyle, A. C. (1892). The Adventure of the Copper Beeches. In The Adventures of Sherlock Holmes. Harper Brothers; Wikisource.Dubois, V. (2019). Welfare Fraud Inspectors Between Standardization and Discretion. In Van de Walle, S., Raaphorst, N. (eds) Inspectors and Enforcement at the Front Line of Government. Palgrave Macmillan. pp. 167-186. Esping-Andersen, G. (1990). The Three Worlds of Welfare Capitalism. Princeton University Press.Genot, E. J. (2018). Strategies of inquiry: The ‘Sherlock Holmes sense of deduction’ revisited. Synthese, 195(5), 2065–2088. https://doi.org/10.1007/s11229-017-1319-xHall, S., Critcher, C., Jefferson, T., Clarke, J., & Roberts, B. (2017). Policing the Crisis: Mugging, the State and Law and Order. Bloomsbury Publishing.Hatrick, J., & González, O. (2022). Watchmen, Copaganda, and Abolition Futurities in US Television. Lateral, 11(2). https://doi.org/10.25158/L11.2.2Iversen, T., & Rehm, P. (2022). Big Data and the Welfare State: How the Information Revolution Threatens Social Solidarity (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781009151405Kaun, A., Lomborg, S., Pentzold, C., Allhutter, D., & Sztandar-Sztanderska, K. (2023). Crosscurrents: Welfare. Media, Culture & Society, 45(4), 877–883. https://doi.org/10.1177/01634437231154777Lomborg, S., Kaun, A., & Scott Hansen, S. (2023). Automated decision-making: Toward a people-centred approach. Sociology Compass, 17(8), e13097. https://doi.org/10.1111/soc4.13097Madsen, A. K. (2018). Data in the smart city: How incongruent frames challenge the transition from ideal to practice. Big Data & Society, 5(2), 205395171880232. https://doi.org/10.1177/2053951718802321O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.Ranchordás, S. (2022). Empathy in the Digital Administrative State. Duke Law Journal, 71(6), 1341–1389. https://doi.org/10.2139/ssrn.3946487Rønn, K. V. (2022). The multifaceted norm of objectivity in intelligence practices. Intelligence and National Security, 37(6), 820–834. https://doi.org/10.1080/02684527.2022.2076331Rønn, K. V., & Søe, S. O. (2019). Is social media intelligence private? Privacy in public and the nature of social media intelligence. Intelligence and National Security, 34(3), 362–378. https://doi.org/10.1080/02684527.2019.1553701Saler, M. T. (2012). As if, modern enchantment and the literary pre-history of virtual reality. Oxford University Press.Strenström, A. (2020). The Plural Policing of Fraud Power and the investigation of insurance and welfare fraud in Sweden. Doctoral Thesis. Tošić, J., & Streinzer, A. (2022, eds.). Ethnographies of Deservingness: Unpacking Ideologies of Distribution and Inequality. Berghahn Books.Zajko, M. (2023). Automated Government Benefits and Welfare Surveillance. Surveillance & Society, 21(3), 246–258. https://doi.org/10.24908/ss.v21i3.16107Vitale, A. S. (2021). The End of Policing. Verso Books.

AB - Abstract:“Data, data, data! … I can’t make bricks without clay.”- The detective Sherlock Holmes in the Adventure of the Copper Beeches (Doyle, 1892)Recent scholarship has brought attention the role of datafication and automation in digital welfare states (Bagger et al., 2023; Kaun et al., 2022) and how this increases inequalities (Iversen & Rehm, 2022). In this paper, we argue that discussions about how digital systems reconfigure welfare must be supplemented by an account of the caseworkers working on behalf of these systems. Empirically, we proceed from on an organizational ethnographic investigation into the Danish authority, Payout Denmark and select Danish municipalities by the first author. These organizations are responsible for payment of various benefits to Danish citizens, and investigating potential fraud with these (Zajko, 2023). This makes these sites both central to the tenets of the welfare state (Esping-Andersen, 1990) and sites fraught with moral conundrums for citizens and caseworkers alike (Ranchordás, 2022). We present an exploration of how the caseworkers perform “detective work” in extension of – and addition to – the data collection and automated decision-support systems which surround them. We derive the figure of the “detective” as a “sensitizing concept” (Blumer, 2006) from the fieldwork. Metaphors and images of detection abound in the self-representations of the work and methods used by caseworkers. Theoretically, we draw on a combination of policing studies, intelligence studies, and cultural studies more broadly. From policing studies, we draw on the concept of ‘plural policing’ to discuss how police functions have disseminated, in this case, into other state and municipal authorities (Stenström, 2020). From intelligence studies, we derive insights about how investigators justify their actions in the face of “missing” or “absent” data as well as how they load their interpretations with claims of objectivity (Genot, 2018; Rønn, 2022). Finally, from general cultural studies, our central argument is that this self-perception of being a detective has profound implications for the role of caseworkers. The figure of the detective is viewed both as authoritative and rational (Saler, 2012) and overlaps with the figure of the police officer as an agent of social order (Hall et al., 2017; Hatrick & González, 2022). Furthermore, this is a figure who is justified in intimately investigating others (Rønn & Søe, 2019; Vitale, 2021) by means of datafication if necessary (O’Neill, 2016). We make the case that the detective-like caseworker is a productive prism for exploring the emerging automated welfare state – a state that incessantly reassesses its citizens and their relative deservingness (Tošić & Streinzer, 2022) while painting such practices in non-moralistic and non-controversial terms. The central implication of our study is that the increased call for data-supported automated decision-making in welfare states should indeed be supplemented by a human-centric focus (Lomborg, Kaun & Scott Hansen, 2023), one which can consider the agency, discretionary power (Dubois, 2019) and, more sweepingly, the ‘world-images’ (Boland & Griffin, 2018) of caseworkers and bureaucrats. As previous research has shown (e.g. Madsen, 2018), bureaucrats may have diverging visions of data, even in the age of automated welfare. References:Bagger, C., Einarsson, A. M., Andelsman Alvarez, V., Klausen, M., & Lomborg, S. (2023). Digital Resignation and the Datafied Welfare State. Big Data & Society, 10(2). https://doi.org/10.1177/20539517231206806Blumer, H. (2006). What Is Wrong with Social Theory? In Sociological Methods. Routledge.Boland, T., & Griffin, R. (2018). The purgatorial ethic and the spirit of welfare. Journal of Classical Sociology, 18(2), 87-103. https://doi.org/10.1177/1468795X17722079 Doyle, A. C. (1892). The Adventure of the Copper Beeches. In The Adventures of Sherlock Holmes. Harper Brothers; Wikisource.Dubois, V. (2019). Welfare Fraud Inspectors Between Standardization and Discretion. In Van de Walle, S., Raaphorst, N. (eds) Inspectors and Enforcement at the Front Line of Government. Palgrave Macmillan. pp. 167-186. Esping-Andersen, G. (1990). The Three Worlds of Welfare Capitalism. Princeton University Press.Genot, E. J. (2018). Strategies of inquiry: The ‘Sherlock Holmes sense of deduction’ revisited. Synthese, 195(5), 2065–2088. https://doi.org/10.1007/s11229-017-1319-xHall, S., Critcher, C., Jefferson, T., Clarke, J., & Roberts, B. (2017). Policing the Crisis: Mugging, the State and Law and Order. Bloomsbury Publishing.Hatrick, J., & González, O. (2022). Watchmen, Copaganda, and Abolition Futurities in US Television. Lateral, 11(2). https://doi.org/10.25158/L11.2.2Iversen, T., & Rehm, P. (2022). Big Data and the Welfare State: How the Information Revolution Threatens Social Solidarity (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781009151405Kaun, A., Lomborg, S., Pentzold, C., Allhutter, D., & Sztandar-Sztanderska, K. (2023). Crosscurrents: Welfare. Media, Culture & Society, 45(4), 877–883. https://doi.org/10.1177/01634437231154777Lomborg, S., Kaun, A., & Scott Hansen, S. (2023). Automated decision-making: Toward a people-centred approach. Sociology Compass, 17(8), e13097. https://doi.org/10.1111/soc4.13097Madsen, A. K. (2018). Data in the smart city: How incongruent frames challenge the transition from ideal to practice. Big Data & Society, 5(2), 205395171880232. https://doi.org/10.1177/2053951718802321O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.Ranchordás, S. (2022). Empathy in the Digital Administrative State. Duke Law Journal, 71(6), 1341–1389. https://doi.org/10.2139/ssrn.3946487Rønn, K. V. (2022). The multifaceted norm of objectivity in intelligence practices. Intelligence and National Security, 37(6), 820–834. https://doi.org/10.1080/02684527.2022.2076331Rønn, K. V., & Søe, S. O. (2019). Is social media intelligence private? Privacy in public and the nature of social media intelligence. Intelligence and National Security, 34(3), 362–378. https://doi.org/10.1080/02684527.2019.1553701Saler, M. T. (2012). As if, modern enchantment and the literary pre-history of virtual reality. Oxford University Press.Strenström, A. (2020). The Plural Policing of Fraud Power and the investigation of insurance and welfare fraud in Sweden. Doctoral Thesis. Tošić, J., & Streinzer, A. (2022, eds.). Ethnographies of Deservingness: Unpacking Ideologies of Distribution and Inequality. Berghahn Books.Zajko, M. (2023). Automated Government Benefits and Welfare Surveillance. Surveillance & Society, 21(3), 246–258. https://doi.org/10.24908/ss.v21i3.16107Vitale, A. S. (2021). The End of Policing. Verso Books.

M3 - Conference abstract for conference

Y2 - 24 September 2024 through 27 September 2024

ER -