Appel à communications: “Governing by numbers: Key indicators and the politics of expectations”, Martin-Luther-University Halle-Wittenberg, 5-7 octobre 2017
Governing by numbers: Key indicators and the politics of expectations
Workshop announcement and call for papers
Organizers: Walter Bartl, Audrey Terracher-Lipinski
Advisory committee: Petra Dobner, Oliver Holtemöller, Christian Papilloud, Richard Rottenburg, Reinhold Sackmann, Konstanze Senge
October 5–7, 2017, Martin-Luther-University Halle-Wittenberg
Politics in the 20th century created a whole array of indicators, such as gross domestic product (GDP) or unemployment indicators, that became crucial for the structuration of entire policy fields. Politics in the 21st century, inspired by the new public management discourse, complemented this trend by developing not only more indicators but also by inventing new forms of regulation (Power 1997) and new ways of modelling political expectations about the future. In the sociology of quantification (Espeland, Stevens 2008; Diaz-Bone, Didier 2016), the relevance of numbers in democratic politics and democratic representation was among the earliest issues addressed (Rose 1991; Desrosières 2005). A basic assumption in this line of reasoning is that there is an inherently political dimension to what seems to be methodological or technocratic issues in the quantification process. While research has become more diversified, there is also growing need for systematizing theoretical approaches and empirical findings as well as pursuing a strategic approach in defining desiderata for further research so as to build a more coherent stock of knowledge about the politics of quantification.
The planned workshop seeks to advance this endeavor by focusing on specific aspects of governing by numbers and particularly on the relevance of key indicators to a ‘politics of expectations’:
Key indicators and politics: The power of indicators to structure entire policy fields is very much debated. On the one hand, there is evidence that particular key indicators are so widely used in society that they have become crucial to the regulation of social life―such as GDP with respect to economic policy. Among the evidence supporting this view is that the effects of some key indicators have a visible impact on policy fields―a case in point is the controversial PISA indicators and their impact on education policy. Other indicators operate largely hidden from public scrutiny―for example, the input indicators defining electoral districts or intergovernmental fiscal relations. On the other hand, very often the power of indicators is also questioned―as in the case of environmental indicators in politics. However, the processes by which indicators become institutionalized as key elements of collective efforts to achieve larger social goals are still poorly understood. The same can be said about conflicts over alternative indicators. With regard to the potential power of indicators, the organizers encourage contributions addressing the following questions:
a. How can we systematically describe institutionalization processes of key indicators?
b. How are key indicators used by different groups of actors, and which conflicts arise from divergent practices?
c. How do practices related to input indicators differ from those related to output indicators?
The politics of expectations: The future is essentially uncertain. Yet political actors have to build expectations about the future in order to make plans and collectively binding decisions. Expectations are fictional in the sense that those who rely on them treat them as if they were certain to become reality. This creates an incentive for actors to try to influence the expectations of others by creating credible accounts of future states of the world. How are expectations about the future symbolized and narrated in politics? With regard to a politics of expectations based on indicators, a crucial question seems to be whether indicators measure past developments, implicitly assuming that these developments will continue in the future, or whether they project future developments, explicitly aiming to account for the contingency of the future―such as in population projections that display different possible scenarios. Recently, there seems to be an increasing relevance of prospective indicators. Such a shift towards explicitly articulating future expectations is obvious, for example, in inflation targeting when central banks communicate expected inflation rates (Bernanke, Mishkin 1997) or when policy targets are formulated as quantitative indicators such as in the European Union’s Open Method of Coordination or in the global governance of development. While it can be assumed that the use of future oriented indicators intends to mobilize collective action (Büttner 2012), it seems equally plausible to assume that a projection of future developments will more likely demotivate genuine political decision-making by suggesting overwhelming factual constraints (Messerschmidt 2014). Recently, a “politics of expectations” has also been observed in the economy (Beckert 2016). Why is this the case? The increasing use of prospective indicators is even more in need of explanation since it has been attributed as a cause of rising volatility of the economy (Esposito 2011). Workshop contributions focusing on the following questions would be highly welcome:
a. How do indicators operate as instruments of imagination?
b. Which strategies of quantification/opposing quantification do social actors pursue in their politics of expectations?
c. How can we systematically assess the assumed shift from retrospective to prospective indicators?
Governing by indicators: In a globalizing world of ever more complex social relations, there is a rising demand for accessible and comparable knowledge (Rottenburg et al. 2015). Since numbers are said to possess many features that cater to this demand, quantification has been observed as a pervasive feature of contemporary society. Indicators are a special form of quantification in that they emphasize the intentional use of numbers (Espeland 2015) and scripted (political) action. Indicators can be qualified, first, as numbers that use a limited set of measurable parameters to make phenomena visible that cannot be observed directly. Hence, otherwise latent phenomena become manifest by operationalizing them using certain indicators. For example, the American census created racial categories that consequently came to represent heterogeneous populations as homogeneous groups of society (Prewitt 2013). Second, since indicators simplify complex phenomena, their interpretation depends on concepts that ensure their communicability (Lehtonen 2015). Concepts aid interpretation by relating the phenomena of interest to the chosen measure. However, these concepts (implicitly) contain causal attributions and, hence, suggest scripts for (political) action. Whereas the concepts of indicators might be explicit in academic discourse, this is not necessarily the case when they are transferred to the political sphere (e.g., Thielemann et al. 2010). One could even assume that indicators have to rely on conventional forms as much as possible in order to function successfully as objects of compromise between conflicting actors (Boltanski, Thévenot 2006). In this line of reasoning, we encourage contributions addressing the following questions:
a. Which subject matters are/are not amenable to quantification?
b. Which contexts necessarily require quantification to render subject matters politically effective? To which extent does the genesis of indicators rely on explicit (analytical or normative) concepts?
We believe that social science has much to gain from a more coherent understanding of how indicators are produced and used in politics.
Please send an abstract (about 500 words) outlining your intended contribution by April 15, 2017 to the organizers of the workshop: c/o Walter Bartl, walter.bartl@soziologie.uni-halle.de.
The workshop is hosted by the Political Sociology Section of the German Sociological Association (DGS), Research Council Sociology of Population (RC41) of the International Sociological Association (ISA), Research Cluster Society and Culture in Motion of the Martin-Luther-University Halle-Wittenberg, and Halle Institute for Economic Research (IWH) – Member of the Leibniz Association.
References
Beckert, Jens (2016): Imagined Futures. Fictional Expectations and Capitalist Dynamics. Cambridge, MA: Harvard University Press.
Bernanke, Ben Shalom; Mishkin, Frederic S. (1997): Inflation targeting. A new framework for monetary policy? In The Journal of Economic Perspectives 11 (2), pp. 97–116.
Boltanski, Luc; Thévenot, Laurent (2006): On Justification. Economies of Worth. Princeton: Princeton University Press.
Büttner, Sebastian M. (2012): Mobilizing Regions, Mobilizing Europe. Expert Knowledge and Scientific Planning in European Regional Development. London: Routledge.
Desrosières, Alain (2005): Die Politik der großen Zahlen. Eine Geschichte der statistischen Denkweise. Berlin: Springer.
Diaz-Bone, Rainer; Didier, Emmanuel (2016): The sociology of quantification. Perspectives on an emerging field in the social sciences. In Historical Social Research 41 (2), pp. 7–26.
Espeland, Wendy (2015): Narrating numbers. In Richard Rottenburg, Sally E. Merry, Sung-Joon Park, Johanna Mugler (Eds.): The World of Indicators. The Making of Governmental Knowledge through Quantification. Cambridge: Cambridge University Press, pp. 56–75.
Espeland, Wendy; Stevens, Mitchell L. (2008): A sociology of quantification. In European Journal of Sociology 49 (03), pp. 401–436. DOI: 10.1017/S0003975609000150.
Esposito, Elena (2011): The Future of Futures: The Time of Money in Financing and Society. Cheltenham, UK: Edward Elgar.
Lehtonen, Markku (2015): Indicators: Tools for informing, monitoring or controlling? In Andrew Jordan, John Turnpenny (Eds.): The Tools of Policy Formulation. Cheltenham: Edward Elgar Publishing, pp. 76–99.
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Rottenburg, Richard; Merry, Sally E.; Park, Sung-Joon; Mugler, Johanna (Eds.) (2015): The World of Indicators. The Making of Governmental Knowledge through Quantification. Cambridge: Cambridge University Press.
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