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Christin, Angèle (2020)In: International Journal of Communication 14, pp. 1115-1134.ABSTRACT“This article offers an analytical framework for understanding the effects of data on the social world. Specifically, I ask: What happens when new data —digital or not—is introduced in a given context? Drawing on a mix of historical and contemporary examples, I provide a typology of 5 mechanisms: tracking, homogenizing, triaging, nudging, and valuating. I then demonstrate how this framework can change how we understand two empirical cases involving data-driven software programs, one in Web journalism and the other in criminal justice. Based on this analysis, the article makes three main points. First, at a time of rapid technological development, we should pay particular attention to what is not changing with digitization. Second, we need further theoretical integration in the rapidly growing field of critical data studies. Third, I suggest that the umbrella concept of “data” should be broken down into smaller and more manageable components depending on the mechanisms scholars are interested in studying.”EXTRACT“The trust we put in numbers as transparent and objective measurements of the “real” world has a long history (Espeland &#38; Stevens, 1998; Porter, 1996). Broader cultural and institutional factors have legitimized data as a valued way of representing the world and making decisions about it. Historians of science have analyzed the emergence of widespread beliefs in the higher value of “mechanical objectivity” and the aura of rationality that have accompanied numbers over the past three centuries (Daston &#38; Galison, 2007). They retraced the development of aesthetic and moral principles that make us see data as “valuable and beautiful” (Halpern, 2015, p. 5). Over time, these positive meanings attached to numbers and data moved beyond the realm of science and engineering, making their way into public administration, nonscientific institutions, and everyday life (Igo, 2008; Porter, 1996). A second and related thread of analysis ties the institutionalization of numbers and their growing legitimacy to economic production and to the cultural frames supporting the complexification of capitalism. Thus, social scientists have highlighted the longer arc of rationalization and quantification techniques. Key episodes in this long history include the rise of double-entry bookkeeping (Carruthers &#38; Espeland, 1991; Weber, 1978), the birth of public statistics (Desrosières, 2002), the commodification and monetization of domains previously protected from quantitative appraisal (Marx, 1992; Simmel, 2011; Zelizer, 2010), the role of numbers in sustaining colonialism and slavery (Browne, 2015), the development of quantitative measurements designed to increase worker productivity during and after the industrial revolutions (Edwards, 1979; Kellogg, Valentine, &#38; Christin, 2020), and the multiplication of data-driven standards to support complicated logistics and supply chains (Star &#38; Bowker, 2000). More recently, economic sociologists have pointed to the role of economics and ideologies of market fundamentalism in promoting numbers as well as quantitative frameworks, including cost–benefit analysis and mathematical equations, as fair and efficient assessments of value (Espeland &#38; Stevens, 1998; Fourcade, 2011).” (pp 1117-1118) Download link 