Classification Situations A New Field of Research for Valuation Studies?
This conference note adds to recent discussions about the sociological implications of the spread of digital techniques for classifying market actors, specifically with regard to processes of social stratification. We first present some of the contributions to the conference "Classification Situations in Markets" and then discuss their implications for future research in general and the field of valuation studies in particular. We suggest three themes related to the conference that deserve further attention by students of valuation and related social processes: (a) the challenges posed by the rise of big data and algorithmic classifications to the study of classification and valuation; (b) the feedback loops of valuation regimes, in particular their consequences for conceptions of the self; and (c) the relation between classification situations and larger institutional settings, which implies a more explicitly comparative orientation. Key words: classification; sociology of algorithms; big data; credit scoring; stratification On May 6, 2015, the Mayor of New York City, Bill de Blasio, signed into law the Stop Credit Discrimination in Employment Act which prohibits employers to make employment and promotion decisions on the basis of job applicants' and current employees' consumer credit histories. When the law went into effect on September 3, 2015, an accompanying city wide outreach campaign was launched to educate New Yorkers about their new rights and responsibilities. Comprising Julian Jurgenmeyer (corresponding author) Columbia University, Department of Sociology, julian.jurgenmeyer@columbia.edu Karoline Krenn, Universitat Luzern, karoline.krenn@mailbox.org (c) 2016 Authors LiU Electronic Press, DOI 10.3384/VS. 2001 5992.1642177 http:/valuationstudies.liu.se Valuation Studies 178 training sessions, street outreach walks, and brochures in no less than nine languages, the campaign's most visible feature were the large scale advertisements posted in subway stations across the city. In huge letters, their tagline read "You are more than your credit score" or, in the Spanish version, "Tu vales mas que tu historial de credito" "You are worth more than your credit history." Why would someone's credit score serve as a yardstick of individual worth in the first place? The city's public counter valuation points to the emergence of a valuation regime which exploits the ever more abundant digital traces of our everyday lives to algorithmically sort and slot people into classificatory schemes. Marion Fourcade and Kieran Healy (2013) have suggested the succinct notion of "classification situations," a variation on the Weberian "class situation," to capture the far reaching pervasiveness and consequences of this process. Based on the tracking of past individual behavior and predictions of future outcomes, classification situations condition the access to economic and other resources, from health care and credit to employment and insurance. While this development is particularly pronounced in the United States, other parts of the world are already following suit or likely to do so. In this essay cum report, we want to add to this recent discussion about the sociological implications of the avalanche of digital numbers we are currently living through. In order to do so, we will first present some of the contributions to the conference "Classification Situations in Markets," held at Humboldt University of Berlin on June 17, 2015, and then discuss their implications for future research in general and the field of valuation studies in particular. We will suggest three themes related to the conference that deserve further attention by students of valuation and related social processes: (a) the challenges posed by the rise of big data and algorithmic classifications to the study of classification and valuation; (b) the feedback loops of valuation regimes, in particular their consequences for conceptions of the self; and (c) the relation between classification situations and larger institutional settings, which implies a more explicitly comparative orientation. Classif icat ion Situations in Markets: New Technologies, New Inequali t ies? Borrowing its title from Fourcade and Healy's (2013) article, the conference sought to illuminate how this new regime and its classificatory logic shape market activities and outcomes, regulate economic behavior, and distribute life chances. The speakers addressed these issues from two angles: the first focused on different conceptual approaches to classification more generally, such as their coordinating functions in markets as conceived by the French Economics of Conventions school (Rainer Diaz Bone, University of Lucerne) their interactional dimension (Andreas Pettenkofer, University of Erfurt) as Classification Situations 179 well as their relationship to value systems (Anne Kruger and Martin Reinhart, Humboldt University of Berlin) The second angle was decidedly more empirical and analyzed the relationship between the new data infrastructure and contemporary classification practices in markets. In the following, we concentrate on the latter approach. 1 Marion Fourcade (University of California, Berkeley) further developed the original argument about classification situations in her keynote address "Seeing Like a Market." Arguing that with the rise of actuarial algorithmic techniques, new classificatory regimes produce new forms of moralized inequality, Fourcade proposed a novel concept: ubercapital. Extending the Bourdieusian inventory of capitals, ubercapital is the product of individuals' trajectory and position in various scorings, categorizations, ratings, and gradings, and it is accumulated and operative across different social fields. The concept thus tries to capture the proliferation of algorithmic classifications in various settings of social life and their use in contexts for which they were not originally intended as in the case of employers relying on credit scores to evaluate a job candidate against which the NYC Stop Credit Discrimination campaign is directed. With access to resources becoming increasingly dependent on ubercapital, it becomes necessary, Fourcade contended, to orient one's behavior to the imperatives of the classifying principles: leave digital traces, go into debt and repay it, demonstrate your financial literacy, and so on. Being a citizen in the contemporary economy thus increasingly means being "traceable, tractable, and extractable," as Fourcade put it. "Seeing like a market," then, is seeing through the lens of scores, categories, and ratings that are based on individual behavior and produce stratifying outcomes. This perspective suggests understanding the unequal distribution of resources and life chances as the result of individual will rather than of structural conditions and to make inequality, therefore, a moral phenomenon. As the German prefix uberindicates, Fourcade and Healy regard the term as a form of meta capital which transcends other forms. Its precise relation to the more traditional and usually analogue forms of capital, however, has not yet been fully elaborated. Does it, for instance, simply absorb economic capital ultimately Bourdieu's own form of meta capital (Bourdieu 1986) or is there a more complex transformation process going on? Fourcade's likening of ubercapital to the letter of introduction the traveling gentleman in early modern Europe carried with him to sustain his reputation even suggests that ubercapital may just be the digitized form of symbolic capital. The We deliberately restrict our coverage of the conference here in order to focus on our 1 argument. Please note that all contributions will appear, with additional papers by Eve Chiapello, Simone Schiller Merkens, Jason Pridmore, and others, in 2017 in a special issue of Historical Social Research (Krenn forthcoming) Valuation Studies 180 concept would therefore benefit from a more explicit positioning in relation to Bourdieu's own forms of capital. Moreover, while Fourcade made a strong empirical case for the offline effects of online behavior, indeed for the entanglements of the analogue and the digital, these transformation dynamics also require further conceptual work. One crucial aspect here is how ubercapital matters differently in different fields. In the economic field, ubercapital does seem to be of increasing relevance. But what role does it play in, say, the political or scientific fields? While digital metrics such as the hor i citation indices from Google Scholar and elsewhere undoubtedly have an increasing impact on academic careers, they still are essentially digital renderings of the already dominant forms of capital within the field. Seen from this perspective, we may wonder whether ubercapital should be considered a new, digital state of capital, in addition to the embodied, institutionalized, and objectified states, rather than a new form of capital, in parallel to cultural, social, and economic capital. Fourcade's co author Kieran Healy (Duke University) further elaborated on the new regime of moralized classification backed by algorithmic techniques. Healy presented data on how classification situations arising from credit rating scores connect to more familiar stratification patterns, particularly to the categorical inequalities of race, class, and gender. Developed in response to the 1974 Equal Credit Opportunity Act, these scores were initially considered a solution to group based discrimination because they promised to measure only actual individual behavior rather than categorical affiliation (Hyman 2011: ch. 6) In fact, today's proponents of databased metrics of individual worth argue on exactly the same grounds: from their perspective, these tools "provide detailed information about individuals, thereby reducing the temptation for decision makers to rely on group based stereotypes" (Strahilevitz 2012: 64) Healy, however, argued that c