# The New Politics of Numbers

Andrea Mennicken, Robert Salais

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# The New Politics
of Numbers

## Utopia, Evidence and Democracy

Edited by
Andrea Mennicken · Robert Salais

OPEN ACCESS

palgrave
macmillan
Executive Politics and Governance

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Kutsal Yesilkagit, University of Utrecht, the Netherlands

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Andrea Mennicken · Robert Salais
Editors

# The New Politics
of Numbers

Utopia, Evidence and Democracy

palgrave
macmillan
Editors

Andrea Mennicken
Department of Accounting and
Centre for Analysis
of Risk and Regulation
London School of Economics and
Political Science
London, UK

Robert Salais
Institutions et dynamiques historiques
de l'économie et de la Société
(IDHES)
École Normale Supérieure
Paris-Saclay
Gif-sur-Yvette, France

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Executive Politics and Governance

ISBN 978-3-030-78200-9

ISBN 978-3-030-78201-6 (eBook)

https://doi.org/10.1007/978-3-030-78201-6

© The Editor(s) (if applicable) and The Author(s) 2022. This book is an open access publication.

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*In Memory of Alain Desrosières and Anthony Hopwood*
# FOREWORD: WHAT NUMBERS DO

Numbers do things. They highlight and obscure. They integrate and disaggregate. They mark and measure. They represent and intervene. They tame and inflame. They structure people's interactions. They create new objects and new kinds of people. They possess a power that hides itself. They are rhetoric that is anti-rhetorical. What all of these features of numbers share is that they express a certain agency. They perform.

The agency of numbers is not the same as human agency. It is not the creative human action that invents numbers and finds new uses and contexts for them. But it is agency, nonetheless, because numbers order and make possible specific kinds of cognition and action and preclude others. For example, numbers make it almost impossible not to compare the entities that share a scale. In doing so, numbers give rise to extraordinary amounts and kinds of comparisons. Our understanding of what is shared and what is unique requires comparison. Numbers make it possible to reduce complex, diverse information into a 'sense-able' sequence. Once we know a number, it is difficult not to think in terms of quantity, whether this is time, distance, price, or some other unit (an exception constitute phone numbers, or street addresses). Numbers produce hierarchy where more is typically better than less. Difference is in degrees, not kind.

We form relationships through and to numbers. Those that took the same standardized test now share a tie with one another, one that is abstract but sometimes fateful. And people become invested in particular numbers or even particular kinds of numbers. Witness the fixation on the
country risk index in Argentina that de Santos (2009) describes. Or the way that measures of sexual behavior shaped the gay rights movement in the United States where the 10% became the widely accepted estimate of the gay population (Espeland and Michaels 2018). Numbers dehumanize, too, as the tattoos of Jews during the Holocaust attest. But they can also humanize, as being counted in a national census offers a sense of inclusion and potency (Rodríguez-Muñiz 2017).

This volume takes the agency of numbers seriously. In different domains, the chapters it contains address how distinctive combinations of human agency and the agentic properties of numbers give rise to particular modes of coordination, administration and governance. Coordination, the art of breaking down complex tasks into actionable (and complementary) units, depends heavily on numbers. We use metrics to synchronize our machines. We use accounting to assess what we have, what is owed, and what worked in the past. We use numbers to project ourselves into uncertain futures when we analyse risk. And we hold leaders accountable with numbers: crime rates, budgets, votes, cost-benefit ratios, rankings, economic indicators, and returns on investments. As the seminal work of Miller and Rose (1990) established, numbers permit states to govern from a distance. But exactly how this governing happens in different institutional contexts is less established. This volume helps to fill that empirical and theoretical gap.

Numbers are like any symbol in that they are a form that systematically includes, excludes, and organizes information. What is distinctive about numbers is how scrupulously they edit the world and the nature of their authority. We associate numbers with precision, rigor, objectivity, and rationality. Numbers are firm while words are malleable. We believe that the rules for constructing measures are constraining such that numbers are less easy to manipulate, less open to multiple interpretations, than other kinds of information. The discipline needed to make numbers is enough to tame the self-interest or politics that threaten their objectivity.

But numbers are rarely as innocent as they seem. They make possible new forms of surveillance that inform and control. As Ota De Leonardis demonstrates, the quantification of poverty translates inequalities into distance, something which mutes discussions of political power. Similarly, Ousmane Sidibé describes how the advent of benchmarking with performance indicators has contributed to undermining public politics around development in Africa. Tong Lam examines how with the advent of big data, algorithms now construct profiles of individuals that informs their
credit, their politics, and their consumption. Robert Salais shows how the transformation to governance by numbers, with its emphasis on efficiency, neglects the ‘fair balance’ between the state and its citizens.

But numbers can also constrain power. In times of political upheaval, measurement has often been a pressing issue, bound up with issues of equity and fairness. The Magna Carta, for example, declared that there should be ‘one measure of wine throughout our whole realm, and one measure of ale and one measure of corn [...]’ in order to protect common people from being cheated with the use of arbitrary measures. And the French Revolution famously introduced the meter and the metric system to the world (Alder 2002). Witold Kula (1986) sees conflict over measures as a fundamental part of class struggle. Isabelle Bruno, Emmanuel Didier, and Tommaso Vitale analyse forms of political action that mobilized statistics in struggles of various kinds, which they term statactivism (Bruno et al. 2014) (see also Boris Samuel’s contribution in this book).

It is easy to underestimate the work and infrastructure that is required to produce numbers that others find credible. As Laurent Thévenot shows, quantification depends on prior processes of formatting and coding, all of which require discipline and standardizing. For example, coding, a process for turning disparate qualitative information into standardized ‘data’ is a complex intervention that requires often hundreds of decisions about whether something is or isn’t an instance of some pre-established category. Coding is governed by established, written protocols that must be learned by those making the coding decisions. And all this transformation takes resources, time, training, and imagination—in other words, administrative capacity. Corine Eyraud describes the developmental stages of the indicators used to measure education in France showing how these operate at different analytical levels. And Thomas Amossé shows how France’s statistical infrastructure has shifted over time, and how its representative household survey, biographical investigation, and matched panel are statistical practices that articulate specific ways of revealing the world, social science theory, methods and conceptions of public action.

Particularly for English-speaking readers, this volume is a welcome introduction to some of the most important theorists of quantification. Together the original essays it contains offer sophisticated and detailed analyses that reveal the administrative capacity that is required to make and use numbers and their power to reshape our core institutions. They allow us to see how decisions to make and use numbers set in motion
consequences that were never envisioned. They reveal how numbers hide their power. After reading this volume, it is impossible to take numbers at face value, a worthy accomplishment.

Wendy Nelson Espeland
Department of Sociology
Northwestern University
Evanston, USA

REFERENCES

Alder, K. (2002). The measure of all things: The seven-year Odyssey and hidden error that transformed the world. The Free Press.

Bruno, I., Didier, E., & Vitale, T. (2014). Statactivism: Forms of action between disclosure and affirmation. *PaCo: Partecipazione & Conflitto*, 7(2), 198-220.

de Santos, M. (2009). Fact-totems and the statistical imagination: The public life of a statistic in Argentina. *Sociological Theory*, 27(4), 466-489.

Espeland, W. N., & Michaels, S. (2018). The history of 10%: Measures of sexual behavior and the gay rights movement in the U.S. Paper presented at the Swedish Collegium for Advanced Study, Uppsala University, Uppsala, Sweden, Kula, W. (1986). Measures and men. Princeton University Press.

Miller, P., & Rose, N. (1990). Governing economic life. *Economy and Society*, 19(1), 1-31.

Rodríguez-Muñiz, M. (2017). Cultivating consent: Nonstate leaders and the orchestration of state legibility. *American Journal of Sociology*, 123, 1-41.

**Wendy Nelson Espeland** is Professor of Sociology at Northwestern University. She works in the fields of culture, organizations, law, and knowledge production, with an emphasis on quantification and accountability. She has written about the effects of quantification on indigenous populations (*The Struggle for Water: Politics, Rationality, and Identity in the American Southwest*, University of Chicago Press, 1998) and, with Michael Sauder, on the effects of university rankings on higher education (*Engines of Anxiety: Academic Rankings, Reputation, and Accountability*, Russell Sage Foundation, 2016). She is also conducting research, with Stuart Michaels, on the relationship between measures of sexual behavior and the gay rights movement. Her articles have appeared in the *American Journal of Sociology*, the *American Sociological Review*, *Law & Society Review*, the *Annual Review of Sociology*, the *European Journal of Sociology*, and the *Annual Review of Law and Social Science*. She has received fellowships from the Russell Sage Foundation, the Australian National University, the Radcliffe Institute for Advanced Study, the Wissenschaftskolleg zu Berlin, and the Swedish Collegium for Advanced Study.
ACKNOWLEDGMENTS

The idea for this book originated at a workshop held at the Wissenschaft-
skolleg zu Berlin in April 2014. The workshop brought together the
Wissenschaftskolleg’s Quantification Focus Group and a group of scholars
working on quantification selected by the Nantes Institute for Advanced
Study (IAS-Nantes) in France. Alain Supiot, who was then the Director
of the IAS-Nantes, had proposed this meeting given that in France,
under the initiative of Alain Desrosières and other scholars, who were
located mainly within the milieu of public statisticians (especially the
INSEE—Institut National de la Statistique et des Etudes Economiques),
a vibrant field of research on quantification had developed studying statis-
tical tools and their history, conventions of measurement, categories, and
classification.

The Quantification Focus Group was composed of the following 2013–
2014 Fellows: Bruce Carruthers (Northwestern University, USA), John
Carson (University of Michigan, USA), Lorraine Daston (Permanent
Fellow at the Wissenschaftskolleg and Director of the Max Planck Insti-
tute for the History of Science, Germany), Emmanuel Didier (CNRS,
France), Wendy Nelson Espeland (Convenor of the Group, Northwestern
University, USA), Tong Lam (University of Toronto, Canada), Andrea
Mennicken (London School of Economics and Political Science, UK),
Jahnavi Phalkey (King’s College London, UK), Theodore Porter (Univer-
sity of California, Los Angeles, USA). The Nantes Group consisted
of Thomas Amossé (Centre d’Etudes de l’Emploi), Ota De Leonardis
(Università degli Studi di Milano-Bicocca, Italy), Corine Eyraud (Aix-Marseille University), Samuel Jubé (IAS-Nantes and University of Nantes), Martine Mespoulet (University of Nantes), Robert Salais (Ecole Normale Supérieure de Cachan), Ousmane Sidibé (Bamako University, Mali), Alan Supiot (University of Nantes, IAS-Nantes), Laurent Thévenot (Ecole des Hautes Etudes en Sciences Sociales, EHESS, Paris).

Considering the fecund and lively nature of the exchanges at the workshop, the two groups decided to further intensify their collaboration and engage in the production of a jointly edited book. Andrea Mennicken (then Fellow at the Wissenschaftskolleg) and Robert Salais (Fellow at the IAS-Nantes in 2011–2012 and Fellow at the Wissenschaftskolleg in 2005–2006) were selected as coordinators of the project—a project which eventually resulted in the publication of this volume.

Two further workshops facilitated the development of the book; one of these was held at the IAS-Nantes in April 2015 and one at the ENS Cachan (now ENS Paris-Saclay) in April 2016. We gratefully acknowledge the financial and logistical support we received from the Fellow Forum of the Wissenschaftskolleg, the IAS-Nantes, and ENS Cachan for the organization of these meetings, where earlier versions of the works presented in this edited volume were discussed.

From the Wissenschaftskolleg, four Fellows of the 2013–2014 Quantification Focus Group contribute to this volume: Emmanuel Didier, Wendy Nelson Espeland, Tong Lam, and Andrea Mennicken. From the Nantes Group contributions were received from Thomas Amossé, Ota De Leonardis, Corine Eyraud, Martine Mespoulet, Robert Salais, Ousmane Sidibé, and Laurent Thévenot, which gave room to invite further contributors: Peter Miller (London School of Economics and Political Science), Boris Samuel (Sciences-Po Paris and Fellow at the IAS-Nantes in 2014–2015) and Uwe Vormbusch (FernUniversität Hagen, Germany), who participated also in the meetings held at the IAS-Nantes and ENS Cachan.

This book is the result of a lengthy process of discussions, several rounds of reviews and revisions, copyediting and translation. We warmly thank the contributors to this volume for their unfailing patience, commitment, reactivity, and support, which have made our work on this book a truly collective undertaking. We also thank the editors and editorial managers of the Executive Politics and Governance series at Palgrave Macmillan for their excellent service and assistance.

Andrea Mennicken gratefully acknowledges the financial support provided by the Economic and Social Research Council (Grant Ref:
ES/N018869/1) under the Open Research Area Scheme (Project Title: QUAD—Quantification, Administrative Capacity, and Democracy), co-funded by the Agence Nationale de la Recherche (ANR, France), Deutsche Forschungsgemeinschaft (DFG, Germany), Economic and Social Research Council (ESRC, UK), and the Nederlands Organisatie voor Wetenschappelijk Onderzoek (NWO, Netherlands).

Last not the least, we especially thank the Wissenschaftskolleg zu Berlin and the IAS-Nantes, where the seeds for this undertaking were planted, for their confidence in our capability to handle this project and drive it to its end.

Andrea Mennicken
Robert Salais
# CONTENTS

1 The New Politics of Numbers: An Introduction 1
Andrea Mennicken and Robert Salais

## Part I Quantification as Utopia

2 Creating a Socialist Society and Quantification in the USSR 45
Martine Mespoulet

3 The People's Algorithms: Social Credits and the Rise of China's Big (Br)other 71
Tong Lam

4 Accounting for Who We Are and Could Be: Inventing Taxonomies of the Self in an Age of Uncertainty 97
Uwe Vormbusch

5 Quantifying Inequality: From Contentious Politics to the Dream of an Indifferent Power 135
Ota De Leonardis
## Part II The Politics of Evidence

6 Homo Statisticus: A History of France's General Public Statistical Infrastructure on Population Since 1950 169
Thomas Amossé

7 A New Calculable Global World in the Making: Governing Through Transnational Certification Standards 197
Laurent Thévenot

8 Do Performance Indicators Improve the Effectiveness of Development Aid? 253
Ousmane Oumarou Sidibé

9 Archaeology of a Quantification Device: Quantification, Policies and Politics in French Higher Education 275
Corine Eyraud

## Part III Voicing for Democracy

10 Quantification = Economization? Numbers, Ratings and Rankings in the Prison Service of England and Wales 307
Andrei Guter-Sandu and Andrea Mennicken

11 The Shifting Legitimacies of Price Measurements: Official Statistics and the Quantification of *Pwofitasyon* in the 2009 Social Struggle in Guadeloupe 337
Boris Samuel

12 “La donnée n’est pas un donné”: Statistics, Quantification and Democratic Choice 379
Robert Salais

13 Free from Numbers? The Politics of Qualitative Sociology in the U.S. Since 1945 417
Emmanuel Didier
<table><tr><td>14 Afterword: Quantifying, Mediating and Intervening:<br/>The R Number and the Politics of Health<br/>in the Twenty-First Century<br/>Peter Miller</td><td>465</td></tr><tr><td>Index</td><td>477</td></tr></table>
NOTES ON CONTRIBUTORS

**Thomas Amossé** is a Public Statistician and Researcher in sociology at the Conservatoire National des Arts et Métiers (CNAM). His research interests revolve around three areas: the socio-economics of work and employment, the sociology of social class, and the socio-history of statistics. He has published several articles, for instance: 'Professions au féminin: Représentation statistique, construction sociale', in *Travail, genre et sociétés*, 2004; 'Hommes et femmes en ménage statistique: Une valse à trois temps', in *Travail, genre et sociétés*, 2011 (with Gaël De Peretti); 'La nomenclature socio-professionnelle: une histoire revisitée', in *Annales, Histoire, Sciences Sociales*, 2013; 'The Centre d'Etudes de l'Emploi (1970-2015): Statistics-on the Cusp of Social Sciences and the State', in *Historical Social Research*, 2016.

**Ota De Leonardis** is a retired Professor of Sociology at the Department of Sociology and Social Research, University of Milano-Bicocca. She is the President of the advisory board of the Nantes Institute for Advanced Study. She was a visiting scholar at UBA and FLACSO (Buenos Aires), EHESS (Paris), Université de Montréal, Université de Sherbrooke (Quebec), and the Institute for Advanced Study Nantes. She was involved in several national and European research projects, as well as in international research networks promoted by the Battelle Foundation, WHO, and Rockefeller Foundation. Her research focuses on institutions theory and methods, on the management and instrumentation of the public
sector, particularly in the social policies field, and on the transforma-
tions of the public sphere, citizenship, and democracy. She is the editor
with Negrelli and Salais of *Democracy and Capabilities for Voice. Welfare,
Work and Public Deliberation in Europe*, Brussels: Peter Lang, 2012,
and recently of *Covid-19. Tour du monde*, Paris: Editions Manucius,
forthcoming.

**Emmanuel Didier** is a Full Professor at the Centre Maurice Halbwachs at École Normale Supérieure, Paris, and a member of the Centre for the Study of Invention and Social Process at Goldsmiths, University of London. He is a founding member of EpiDaPo (Epigenetics, Data, Politics), initially a joint research unit of CNRS and UCLA. He taught at the University of Chicago and at UCLA and now teaches at Ecole Normale Supérieure and Ecole Nationale de la Statistique et de l'Administration Economique, both in Paris. He works on the sociology of quantification, statistics, and big data. He wrote several books, including *En quoi consiste l'Amérique, les statistiques le New Deal et la démocratie* (La découverte, 2009), *Benchmarking, l'Etat sous pression statistique* (La Découverte 2013, with Isabelle Bruno), and he edited with Isabelle Bruno and Julien Prévieux *Statactactivisme, comment lutter avec des nombres* (La Découverte 2014). Recently, he published *America by the Numbers: Quantification, Democracy, and the Birth of National Statistics* (MIT Press, 2020). Didier was a Fellow of the Wissenschaftskolleg zu Berlin (2013–2014).

**Corine Eyraud** is Associate Professor at the Department of Sociology at Aix-Marseille University. She is also an Associate of the Maison française d'Oxford and of the Centre for Higher Education Futures (Aarhus University, Denmark). Her work resides at the intersections of public policy, economic sociology, critical management studies, and sociology of quantification. Eyraud was a visiting scholar at Oxford University (Wolfson College, St Antony's College, Department of Politics and International Relations), Aarhus University, and at the Chinese Academy of Social Sciences. She has been involved in several national and European research projects and has been a member of the Reflection Group on ‘the Future of Official Statistics—Horizon 2030’ organized by Eurostat and the European Political Strategy Centre of the European Commission. Her recent publications include ‘Quantification Devices and Political or Social Philosophies. Thoughts inspired by the French State Accounting Reform’, in *Historical Social Research*, 2016; ‘Réflexions pour une sociologie de la quantification statistique et comptable’, in *Entreprises et Histoire*, 2015;
and the books *L'entreprise publique chinoise* (L'Harmattan 1999), *Le capitalisme au cœur de l'État. Comptabilité privée et action publique* (Editions du Croquant, 2013).

**Andrei Guter-Sandu** is ESRC Postdoctoral Fellow at the Centre for Analysis of Risk and Regulation, London School of Economics and Political Science. He obtained his PhD in International Political Economy from City, University of London, and currently works on a project investigating how managerialist ideas and instruments of quantification change the manner in which public services are governed and controlled. His latest publication includes 'Theorising resilience: Russia's reaction to US and EU sanctions' (with Elizaveta Kuznetsova), in *East European Politics*, 2020.

**Tong Lam** is Associate Professor of History at the University of Toronto and Director of the Global Taiwan Program at the Asian Institute. His research is on the modern and contemporary history of China, with emphases on empire and nation, governmentality, knowledge production, as well as urban space and ruins. He is the author of *A Passion for Facts: Social Surveys and the Construction of the Chinese Nation-State, 1900–1949* (Berkeley: University of California Press, 2011) which analyses the profound consequences of the emergence of the technologies of the 'social fact' and social survey research in modern China. Lam's ongoing research also examines the prevalence of designer architectures, urban ruins, and derelict spaces in post-socialist China's spectacular and speculative development. As a visual artist, Lam uses photographic techniques to carry out ethnographic studies of contemporary China's hysterical transformation. At present, he is working on a photo essay book on industrial and post-industrial ruins and abandonment from around the world. See here also his book *Abandoned Futures: A Journey to the Posthuman World* (Carpet Bombing Culture, 2013). Lam was a Fellow of the Wissenschaftskolleg zu Berlin (2013–2014).

**Andrea Mennicken** is Associate Professor of Accounting at the London School of Economics and Political Science and Co-Director of the Centre for Analysis of Risk and Regulation (LSE). She is associate editor of *Accounting, Organizations and Society* and *Valuation Studies*. Her work has been published in *Accounting, Organizations and Society*, *Financial Accountability and Management*, *Foucault Studies*, *Organization Studies*, *Sociologie du travail*, *Actes de la recherche en sciences sociales* and different
edited volumes. Recently, she has completed work on an international research project funded by the ESRC under the Open Research Area Programme for the Social Sciences, exploring the changing relationships between quantification, administrative capacity and democracy in health care, correctional services, and higher education. She was a Fellow of the Wissenschaftskolleg zu Berlin (2013–2014).

**Martine Mespoulet** is Professor emerita of Sociology at the University of Nantes and Researcher at the CNRS Centre of Sociology in Nantes (CENS). Her research focuses on two main fields: the use of quantification in public action and state and societies in Central and Eastern Europe. Her work has appeared in a wide range of sociology and history journals. Her books include *Construire le socialisme par les chiffres* (Ined, 2008), *L'anarchie bureaucratique. Statistique et pouvoir sous Staline* (La Découverte, 2003) with Alain Blum and *Statistique et révolution en Russie. Un compromis impossible (1880-1930)* (Presses Universitaires de Rennes, 2001).

**Peter Miller** is Professor of Management Accounting at the London School of Economics and Political Science, and an Associate of the Centre for Analysis of Risk and Regulation. He is an editor of *Accounting, Organizations and Society* and has published in a wide range of accounting, management, and sociology journals. He co-edited *The Foucault Effect* (1991), *Accounting as Social and Institutional Practice* (1994), and more recently *Accounting, Organizations, and Institutions* (2009). In 2008, he published (jointly with Nikolas Rose) *Governing the Present*.

**Robert Salais** is an Associated Researcher of the CNRS interdisciplinary laboratory ‘Institutions and Historical Dynamics of the Economy and the Society’ (IHDES). Working at the crossings of history and socio-economy, he is one of the founders of the economics of convention. He was a visiting researcher at the Institut Universitaire Européen, the Wissenschaftszentrum Berlin für Sozialforschung (WZB), the Centre Marc Bloch at Berlin (CMB), Warwick University, and the Norwegian Social Research (NOVA) at Oslo. He has published in a wide range of economical, historical, sociological and law reviews and edited books. He coordinated (EUROCAP, CAPRIGHT) or participated in several European research programmes on employment and social policies. Main books include *L'invention du chômage* (with Nicolas Baverez and Bénédicte Reynaud), Presses Universitaires de France, second edition 1999;
*Worlds of Production* (with Michael Storper), Harvard University Press, 1997 (French edition 1993); *Europe and the Politics of Capabilities* (editor with Robert Villeneuve), Cambridge University Press, 2005; *Le viol d'Europe. Enquête sur la disparition d'une idée*, Presses Universitaires de France, 2013; *Qualitätspolitiken und Konventionen* (editor with Marcel Streng und Jakob Vogel), Springer, 2019. He has received fellowships from the Wissenschaftskolleg zu Berlin (2005–2006) and the IAS-Nantes (2011–2012).

**Boris Samuel** is Researcher at the French National Research Institute for Sustainable Development (IRD), Centre d'études en sciences sociales sur les mondes africains, américains, et asiatiques (CESSMA), University of Paris. His research examines statistical and macroeconomic practices to provide an analysis of social relations and political trajectories. His current research projects deal with the new technologies of the social state in Morocco, with planning practices in Africa, and with the role of macro-economists and statisticians in francophone West-African countries. He holds a PhD in political science from Sciences Po Paris (2013). Before joining the academy, he has worked for ten years as an expert in statistics, public finance and macroeconomics for international organizations and governments in Africa. He currently teaches at Paris Dauphine University and at the Faculty of Human Sciences and Education Sciences of Bamako. Boris Samuel is co-editor of *Politique Africaine* and member of the edito-rial board of *Sociétés contemporaines*. He was a Fellow of the IAS Nantes in 2014–2015.

**Ousmane Oumarou Sidibé** is Professor of Law at the University of Bamako in Mali. His research interests centre around employment law and social security law and the use of performance indicators in public poli-cies in Africa. After graduating from the Ecole Nationale d'Administra-tion of Mali in 1978, he earned a doctorate in Law (option Employment Law) in Bordeaux in 1983. He previously held several positions: Minister for Employment, Civil Service and Labor, managing director of the Ecole Nationale d'Administration of Mali, Commissioner for Institutional Reform, African Program Coordinator for the participation of workers. Along with his administrative and political activities, he continued his academic career teaching at the University of Bamako since 1992.
**Laurent Thévenot** is Directeur d'études at the École des hautes études en sciences sociales. Following his research on 'social coding' and 'investment in (conventional) forms' he initiated with Luc Boltanski what has become known as pragmatic sociology: *On Justification: Economies of Worth*, Princeton University Press, 2006 (French edition 1991). He also co-founded with economists the critical institutionalist current of the economics of convention. More recently in *L'action au pluriel. Sociologie des régimes d'engagement* (La Découverte, 2006), he has identified several constructions of commonality (the liberal grammar of interests, the grammar of personal affinities to common-places) and various modes of engaging which confer both consistency and dynamism on the community and the personality, while allowing to extend the convention theory's critical analysis of power and oppression. His empirical investigations have focused on governance by standards and objectives, politics of quantification, and have drawn on collaborative programmes comparing architectures of communities and criticism in Western Europe (*European Journal of Cultural and Political Sociology*, special issue on 'Politics of Engagement in an Age of Differing Voices' co-edited with Eeva Luhtakallio, 2018 5[1–2]), Russia (Revue d'Etudes Comparatives Est-Ouest, special issue on 'Critiquer et agir en Russie' co-edited with Françoise Daucé et Kathy Rousselet, 2017 48[3–4]) and the United States (*Rethinking Comparative Cultural Sociology: Repertoires of Evaluation in France and the United States*, co-edited with Michèle Lamont, Cambridge University Press, 2000).

**Uwe Vormbusch** is Professor for the Analysis of Contemporary Societies at the Institute of Sociology of the FernUniversität Hagen in Germany. He has been a visiting scholar at the London School of Economics and Political Science in 2009. His research areas are the sociology of quantification and valuation; economic and financial sociology; and general sociology. Vormbusch recently completed a research project on the quantified-self movement funded by the German Research Foundation (DFG). Recent publications include *Wirtschafts- und Finanzsoziologie. Eine kritische Einführung*, Springer VS, 2019; Kalkulative Formen der Selbstthematisierung und das epistemische Selbst, in: *Psychosozial*, vol. 41, issue 3/2018, pp. 16–35 (with Eryk Noji); *Die Herrschaft der Zahlen. Zur Kalkulation des Sozialen in der kapitalistischen Moderne*, Campus Verlag, 2012; *Soziologie der Finanzmärkte* (with Herbert Kalthoff), transcript, 2012.
LIST OF FIGURES

<table><tr><td>Fig. 5.1</td><td>Examined semantic shifts</td><td>139</td></tr><tr><td>Fig. 7.1</td><td>From debated conceptions of the common good to certified qualities of market goods</td><td>211</td></tr><tr><td>Fig. 7.2</td><td>a, b Photographs of Open Space Technology (OST) in action (Source Photographs by Laurent Thévenot)</td><td>215</td></tr><tr><td>Fig. 7.3</td><td>a, b Photographs of Arifin, firstly embarrassed and hesitant in front of the Open Space Technology, then animating his “open space” group (Source Photographs by Laurent Thévenot)</td><td>221</td></tr><tr><td>Fig. 7.4</td><td>a, b, c Photographs of Arifin, at ease during a conversation at the cafeteria (Source Photographs by Laurent Thévenot)</td><td>221</td></tr><tr><td>Fig. 7.5</td><td>The transformation of familiar-customary landmarks (a) into quantifiable space markers; (b) recorded by the NGO technician (left) and the village chief (right) (Source Photographs by Laurent Thévenot)</td><td>229</td></tr><tr><td>Fig. 7.6</td><td>Photographs of the direct confrontation with the headquarters company directors. (a) (top photograph; right of the table, from left to right): Karlo (NGO Sawit Watch), Bondan (Sawit Watch), Yanti (Batu Ampar village chief), Nauli (NGO Wahli Jambi); (b) (bottom left): GAR (Singapore) director of communication; (c) (centre): Karlo; (d) (bottom right): Yanti (Source Photographs by Laurent Thévenot)</td><td>230</td></tr></table>
<table><tr><td>Fig. 11.1</td><td>Excerpt of the chart used by the LKP during the negotiations of the prices of the 100 “necessities” (Adapted from the original obtained by the author with permission from Alain Plaisir/LKP)</td><td>357</td></tr><tr><td>Fig. 13.1</td><td>“Breaking out of the Hothouse” (<i>Source Insurgent Sociologist</i>, Vol. 1, No. 2, p. 8. Reprinted with permission from <i>Critical Sociology</i>. Scan gratefully provided by the University of Michigan Library [Special Collections Research Center])</td><td>442</td></tr><tr><td>Fig. 13.2</td><td>Yearly distribution of the expressions “qualitative research”, “qualitative method”, “qualitative sociology” and “quantitative sociology” in the Jstor full database</td><td>454</td></tr></table>
LIST OF TABLES

<table><tr><td>Table 7.1</td><td>The local familiar and customary format of evidence</td><td>228</td></tr><tr><td>Table 9.1</td><td>French university funding system (from mid-1980s to 2012) (compiled by the author)</td><td>288</td></tr><tr><td>Table 11.1</td><td>Excerpt from INSEE's 2010 report based on a spatial price comparison</td><td>360</td></tr><tr><td>Table 11.2</td><td>Extract from the reported price differentials by the Senate's fact-finding Mission (Mission d'information parlementaire) from 2009</td><td>366</td></tr><tr><td>Table 12.1</td><td>Trends in the overall rate of employment (age 15-64), 1997-2005, in France, Germany and the UK</td><td>394</td></tr><tr><td>Table 13.1</td><td>Reproduced from Schwartz and Jacobs (1979, p. 5)</td><td>452</td></tr><tr><td>Table 13.2</td><td>Name of author and number of their articles containing the expression "qualitative sociology", 1945-1985</td><td>455</td></tr><tr><td>Table 13.3</td><td>Twenty most used keywords of papers using the expression "qualitative sociology" and their number of appearance, 1945-1985</td><td>455</td></tr><tr><td>Table 13.4</td><td>Twenty successive keywords beginning at the row 75 associated with the expression "qualitative sociology", 1945-1985</td><td>455</td></tr></table>
# The New Politics of Numbers: An Introduction

Andrea Mennicken and Robert Salais

The business of government is increasingly run with a calculator to hand. Both policymaking activities and administrative control are increasingly structured around calculations such as cost-benefit analyses, estimates of social impacts and financial returns, measurements of performance and risk, benchmarking, quantified impact assessments, ratings and rankings, all of which provide information in the form of a numerical representation. Through quantification, public services and policies have experienced a fundamental shifting from “government by democracy” towards “governance by numbers”, with implications not just for our understanding of the nature of public administration itself, but also for wider

<footnote>A. Mennicken (✉)</footnote>

<footnote>Department of Accounting and Centre for Analysis of Risk and Regulation,
London School of Economics and Political Science, London, UK</footnote>

<footnote>e-mail: a.m.mennicken@lse.ac.uk</footnote>

<footnote>R. Salais</footnote>

<footnote>Institutions et dynamiques historiques de l'économie et de la Société (IDHES),
École Normale Supérieure Paris-Saclay, Gif-sur-Yvette, France</footnote>
debates about the nature of citizenship and democracy. This book scrutinizes the relationships between quantification, administrative capacity and democracy across different policy sectors and countries. In so doing, it seeks to offer unique cross-national and cross-sectoral insight into how managerialist ideas and instruments of quantification have been adopted and how they have come to matter.

More than thirty years ago, Alonso and Starr (1989) edited the by now classic “The Politics of Numbers”, which was amongst the first books that scrutinized relations between quantification and democratic government in North America (but see also Cohen, 1982). Amongst other things, Alonso and Starr’s collection of essays showed how government statistics had become vital to pursuing essential goals of a democratic polity, such as accountability and representation of diverse interests. The book also highlighted that a nation’s number system creates new invisibilities (e.g. of minorities). It showed how and to what extent political judgements and bias are embedded in the statistical systems of the modern state, or as Rose (1991, p. 675) put it, “how the domain of numbers is politically composed and the domain of politics is made up numerically”.

In parallel, also European scholars had begun to question the relation between numbers and democracy, and between government and numbers. In France, in particular Alain Desrosières and his colleagues, including Robert Salais and Laurent Thévenot, who contributed to this volume and at the time worked with Desrosières for the French National Institute of Statistics and Economic Studies (INSEE), interrogated the conventions and classifications underpinning the production, use, and consequences of statistics (e.g. Desrosières, 1987 [1983]; Desrosières, 1998 [1993]; Thévenot, 1979, 1981; Salais, 1986; for useful overviews see also Diaz-Bone & Didier, 2016; Diaz-Bone & Salais, 2011). In the UK, it was first and foremost Anthony Hopwood who triggered a critical-reflexive turn in the study of numbers, focusing on the multifaceted roles of accounting in representing and intervening in social and organizational life (see e.g. Hopwood, 1983; Hopwood & Miller, 1994; S. Burchell et al., 1980; but see also Miller, 1992; Miller & Rose, 1990). Further important early works on the production, history and influence of statistics were conducted by scholars with backgrounds in the history and philosophy of science (Daston, 1988; Gigerenzer et al., 1989; Hacking, 1990; Krüger et al., 1987; Porter, 1986).
Since then, particularly over the past fifteen years or so, there has been an increased interest in, and surge of, articles and books on governance by numbers, albeit in different fields (for a review see Mennicken & Espeland, 2019). In the field of public administration and public policy, especially the rise of New Public Management led to heightened attention to the roles of performance indicators in the governance of public services (see also Bruno et al., 2016; Bruno & Didier, 2013; Supiot 2015). Here, consideration has not only been given to problems of measurement (i.e. the limits of performance measures to capture what matters), but also gaming (Bevan & Hood, 2006; Strathern, 1997), reactivity (Espeland & Sauder, 2007) and the “audit explosion”, characterized by the rise and expansion of formal systems of performance evaluation and assessment aimed at making elusive notions, such as quality, auditable (Power, 1997; Strathern, 2000).

Bevan and Hood (2006) showed how governance by targets changed the behaviour of individuals and organizations in the English National Health System (NHS). They coined the famous phrase “hitting the target and missing the point” (ibid., p. 521). Building on Goodhart’s eponymous law that “any observed statistical regularity will tend to collapse once pressure is placed on it for control purposes” (Goodhart, 1984, p. 94, cited in Bevan & Hood, 2006, p. 521), they queried to what extent “governance by targets” subverts public service ethos, contributes to output distortions and a general narrowing of quality definitions. Also, Strathern showed for the case of the higher education sector in the UK that “when a measure becomes a target, it ceases to be a good measure” (Strathern, 1997, p. 308). More recently, Espeland and Sauder (2007) investigated reflexive interactions between people and measures by looking at the reactivity of US law school rankings. Amongst other things, they showed that these rankings contributed to a proliferation of gaming strategies, the redefinition of work and a redistribution of resources (Espeland & Sauder, 2016; but see also Bruno et al., 2016). Research has also drawn attention to new practices and strategies of gaming and manipulation that have emerged in the academic world over the past few years (Biagioli & Lippman, 2020a). These practices are different from the predictable gaming of academic performance indicators and may take the form of “massaging the definition what counts as a ‘successful student’ in metrics about schools’ performance, or of what counts as a ‘peer-reviewed’ paper in faculty evaluation protocols” (Biagioli & Lippman, 2020b, p. 1).
Rankings, ratings and other governance indicators, such as the Human Development Index, Gender Inequality Index or Social Progress Index, rest on multiple levels of aggregation (Mennicken & Espeland, 2019, p. 232). They are seductive as they allow for easy comparison and ranking of countries and organizations, which can lead to oversimplification and homogenization if not grounded in qualitative, locally informed knowledge production (Davis et al., 2012; Merry, 2016; Rottenburg et al., 2015; Salais, 2006; Supiot, 2015; Thévenot, 2009). This and the rise and proliferation of “governance by numbers” makes it all the more important to understand how such numbers are produced, calculated and aggregated, and with what consequences.

The essays collected in this volume interrogate what has changed in the relation between numbers and democracy, and between government and numbers, since the publication of “The Politics of Numbers” (Alonso & Starr, 1989). What is “new” in the politics of numbers and our approach to their study?

First, we observe an unprecedented expansion, acceleration and intensification of quantification not only in political life but also in everyday life. To a large extent such an expansion and intensification of quantification has been aided by the rise of new computer technologies for (big) data collection and data processing. Such new digital technologies, including machine learning algorithms, have changed how public administrations deploy resources and make decisions. They promise new possibilities of governing, as the contribution of Lam in this volume on the rise of China’s social credit system shows (Chapter 3). They also transform how we understand ourselves, what we attend to and consider important, as Vormbusch’s study of the “quantified self” movement in Germany in this volume demonstrates (Chapter 4).

Second, we witness an increasing decline in the “trust in numbers” (Porter, 1995), an antipathy to government statistics, and a disillusionment and tiredness with New Public Management’s “governance by targets”. In the age of “post-truth” politics, many have come to believe that numbers are manipulated. As Davies (2017) argues, many well-recognized indicators have lost their legitimacy. He quotes a study from the US that discovered that 68% of Trump supporters distrusted the economic data published by the federal government. For the UK, Davies highlights “that a research project by Cambridge University and YouGov looking at conspiracy theories revealed that 55% of the population believes that the government ‘is hiding the truth about the number of immigrants”
living here” (Davies, 2017). Such distrust in numbers is further fuelled
by the increasing distance between two objectives of public services and
policies that service users have experienced over the past two decades: an
increasing distance between attempts aimed at truly improving the situa-
tions of the people concerned, on the one hand, and the maximizing of
quantitative performance, on the other hand. To counteract such devel-
opments, in the UK, an independent regulatory body was established in
2016, the Office for Statistics Regulation, to safeguard the “trustworthi-
ness, quality and value of statistics” and to assure that “statistics serve
the public good” acknowledging that statistics should meet the needs of
a much wider range of users than public policy-makers and parliamen-
tarians (see https://osr.statisticsauthority.gov.uk/publication/osr-vision,
accessed 30 October 2020).

At the same time, and ironically, the presence of numbers in our lives
seems to have never been greater. Such an increase in quantification
can be the result of an “overproduction” of an administrative policy, a
reaction (or even overreaction) to crisis, cognitive bias and uncertainty
(Maor, 2018, 2019). As Miller points out in the Afterword to this book
(Chapter 14), numbers have acquired an unassailable power, particularly
in the wake of the Covid-19 pandemic. As he writes, “the phrase ‘follow
the science’, and its numerical counterpart the ‘R’ number, has attained
an ascendancy that none of us could have imagined only a few months
ago”. The R number, and associated statistics, such as the 14-day or 7-day
notification rate of newly reported COVID-19 cases per 100,000 of the
population, have been used as devices to regulate our lives, to make deci-
sions about whether schools, shops, restaurants, and much else besides,
should be open or closed, whether, and in what constellation, one can
meet with others or not. Miller’s contribution to this volume also shows
that the R number is far from being a straightforward measure. It is not
only incredibly difficult to calculate, it can also be potentially misleading
or at least uninformative, because it does not necessarily tell you what is
happening in your local area.

The essays collected in this volume query the rise and spread, as well as
resistance to, and disappointment in, the tools of quantification that have
come to govern our lives. In so doing, they do not so much ask what
quantification *is*. Rather, they are interested in describing and analysing
what quantification *does*. This volume is concerned with the tracking and
unpacking of various practices of quantification and their manifold conse-
quences in different contexts of public and private life. Such a close-up
focus on quantification practice, or “quantification in action” to para-
phrase Hopwood (1983), contributes to our understanding of the roles
of numbers in public policy and public administration, and scholarship on
quantification more generally, in at least four distinct ways.

First, it helps in developing a more nuanced understanding of the capacities and roles of the various calculative practices that have come to populate different domains. The contributions to this book highlight that quantification does much more than provoke gaming and reactivity. They offer valuable insights into the inner workings of (different) accountability regimes, their changing nature and the emergence of new regulatory spaces and practices.

Second, the contributions show how quantification is implicated in
dreams and schemes of doing things differently, of creating new worlds
and bettering society. In many respects, it appears now that the socialist
countries have been pioneers in the political use of numbers. In the
USSR, statistics played not only a key role in the operationalization of
central planning; statistics were also inextricably linked to the articulation
and specification of the “socialist dream” (see Mespoulet’s contribu-
tion, Chapter 2). Likewise, China’s current social credit system has to
be seen as part of a bigger, long-term commitment to creating “good”
citizens via the controlling power of numbers (see Lam’s contribution,
Chapter 3). It is often such dreams and schemes, or programmatic ambi-
tions, as Miller and Rose (1990) would put it, that animate the rise and
spread of numbers and need to be attended to, rather than (unintended)
behavioural effects, if we want to understand what keeps the machinery
of quantification running despite its continuous failings.

Third, the book is concerned with providing deeper insight into how
quantification travels. This book brings together works on governing by
numbers by leading and emerging French, German, Italian, British and
Anglo-American scholars. In so doing, the book makes not only French,
Italian and German works on quantification accessible to an English-
speaking audience. It also enhances understanding of the implication of
quantification in different modes of regulating and governing. It gives
insight into how different forms of quantification have been developed
and deployed in the public administrations of varied countries (China,
Mali, Guadeloupe, USSR, UK, France) as well as European institutions
in different historical periods. The contributions collected here examine
whether and how quantification—the shift from government by democ-
racy to governance by numbers—has given rise to a shift in demands
on administrative capacities of public administrations (e.g. expectations regarding analytical skills, regulatory capabilities, legal staff or financial resources). To what extent do tools of quantification advance the capacities of public administrations, regulatory agencies, and other organizations across sectors and states in terms of being able to monitor and steer?

Fourth, and finally, the book revisits the power of numbers, and the changing relationship between numbers and democracy. It engages two central programmatic strands of research in a critical dialogue with each other: namely Foucault inspired studies of governmentality (see here in particular the contributions by Miller, Guter-Sandu and Mennicken, Vormbusch, Lam and De Leonardis), which first and foremost flourished in the English-speaking world, and studies of state statistics and economic conventions, which have their origins in France, in particular the INSEE (Institut national de la statistique et des études économiques) (see here the contributions by Thévenot and Salais, two of the founding fathers of the economics of conventions approach, and the chapters by Samuel, Mespoulet, Amossé, Didier and Eyraud). Such a critical dialogue helps advance debates about the power of numbers and relations between quantification and democracy, a topic that in our view is in need of renewed discussion and theoretical reflection. For when quantification becomes a “technology of government”, power may be understood, expressed and resisted differently, depending also on the specific characteristics of the instruments of quantification used and what these afford actors to do. For numbers are not only a device of rational rule, public administration and domination. As the contributions by Thévenot (Chapter 7), Samuel (Chapter 11) and Salais (Chapter 12) in this volume demonstrate, they can also aid social mobilization and empowerment, a theme that particularly more recently published works on quantification have often overlooked (but see the recent French works on statactivism published by Bruno et al., 2014).

While some recent literature, particularly social studies of finance, has devoted a lot of attention to the technological infrastructures of calculation, it has tended to neglect or downplay the roles that political ideas, programmes or myths play in articulating and mobilizing them. Foucault-inspired studies of the governmentality of quantification (Miller, 1992, 2001; Miller & O'Leary, 1987; Miller & Rose, 1990) emphasize that we need to attend to both instruments and ideas of calculation, and the interplay between them, as it is through that interplay that each dimension
finds its conditions of operation. Similarly, also the economics of conven-
tion approach (Desrosières, 1985; Diaz-Bone, 2016; Diaz-Bone & Salais,
2011; Eymard-Duvernay, 1989; Salais, 2016; Salais & Thévenot, 1986;
Thévenot, 2011) stresses the significance of ideas and conventions for
the shaping of practices of quantification, and it assumes a plurality of
possible ways in which numbers can come to govern. Yet, as Demor-
tain (2019) points out, whereas governmentality studies have tended
to approach quantification in terms of its (variable) political rationali-
ties and disciplinary effects, the economics of convention approach has
paid more attention to the collective mobilization capacities it offers (or
not). We argue that it is important to understand processes and conse-
quences of quantification from both angles. The contributions to this
volume show that it is important to look at quantification as both a “tech-
nology of government, that reproduces a power structure” and as “a tool
that can facilitate political action towards this structure, and its change”
(Demortain, 2019, p. 974).

In our view, the time is ripe for such a joined-up, historically and
contextually sensitive approach to get to grips with the multiplicity
of quantification and “governing by numbers”. This volume assembles
contributions from different disciplines and contexts to deepen our under-
standing of “quantification in action”. It is structured into three main
parts. The first (Part I), explores *Quantification as Utopia*. Here, contri-
butions scrutinize the implication of quantification in imaginaries of the
future, “the ideal city” or “imagined community” as Anderson (1983)
would say, that possesses highly desirable or nearly perfect qualities for
its citizens. Statistics and other forms of quantification offer the promise
of anchoring such ideals and imaginations in something tangible (Davies,
2017). But under what conditions and with what consequences?

The second part (Part II), revisits the roles of numbers in *Politics of Evidence*. Here, contributions probe the facticity of numbers and interro-
gate to what extent evidence-based quantification is in itself utopian. The
third and final part (Part III, entitled *Voicing for Democracy*) scrutinizes
changes in the relation between quantification and democracy. Nowadays
democracy is less than ever a peaceful and established social activity. New
relationships of power have emerged that dissimulate themselves under
the cloak of technicalities which can lead to a weakening of democratic
rights. Contributions in this part query the implication of quantification
in the rise of what Crouch (2004) has termed “post-democratic soci-
ety”, a society “that continues to have and to use all the institutions of
democracy, but in which they increasingly become a formal shell". Yet, we
also ask what would be needed to disrupt this trend. Under what condi-
tions can the exercise of political voice be made possible in and through
quantification (see here in particular Samuel's and Salais' contributions,
Chapter 11 and Chapter 12, but see also the contribution by Guter-Sandu
and Mennicken, Chapter 10)?

In the following, we introduce each of these parts and the individual
contributions that make them up in more detail to help readers navi-
gate and comprehend the overall architecture of the book. We conclude
our overview with a return to the question of where the economics of
convention approach meets Foucault and Foucauldian studies of govern-
mentality and what such a joining up brings to the furthering of debates
about quantification and governing by numbers.

QUANTIFICATION AS UTOPIA

As Frank Manuel and Fritzie Manuel's (1979) witty and erudite book
*Utopian Thought in the Western World* shows, imagining utopias has been
a long-term characteristic of the western world since the Ancient Greeks.
Yet, types, subjects, and political uses of utopia have changed over time
and place. Whereas in the seventeenth century "utopia came to denote
general programs and platforms for ideal society, codes and constitutions
that dispensed with fictional apparatus altogether" (Manuel & Manuel,
1979, p. 2), more rationalist, systematic utopias appeared around the end
of the eighteenth century. According to Manuel and Manuel (1979, p. 2),
"the means of reaching utopia was transformed from an adventure story
or a rite of passage to Elysium into a question of political action". The
way of attaining the ideal city came to affect the very nature of the city
itself (Manuel & Manuel, 1979, p. 3). This is still the case today. Utopias
can reveal themselves as good or bad, but that is not our concern here.
We are interested in the different ways utopian thought has influenced,
and continues to influence, the building of the knowledge a society has
of itself; concepts of the common good; the making of policies and their
implementation; and the roles that come to be ascribed to citizens and
their formatting.

Utopias could be said to set forth a horizon of expectations that is
believed to open a new future viewed as enlarging and facilitating the
actions of those who form it, ultimately aimed at making them more
powerful. These can be scientists, philosophers, ideologues, managers,
politicians, all people who more or less occupy the role of “conseillers du prince” in government matters. Policy-driven quantification often carries with it a utopian perspective. It is implicated in the promise and dream of creating an infrastructure that can facilitate the making of a new (better) order. In this respect, quantification is deeply ideational (Power, 2019; Miller & Rose, 1990); and it is often utopian thought that motivates its production and expansion.

Quantification is further sustained by beliefs in its own rationality. Simply put, the belief that often motivates in the political domain the recourse to quantification is the assumption that *more equals better*. Qualities are reduced to quantities, and difference is transformed into magnitude (Espeland & Stevens, 1998). As Espeland and Stevens (1998, p. 316) have highlighted, this transformation “allows people to quickly grasp, represent, and compare differences”. It offers “ways of constructing proxies for uncertain and elusive qualities” (ibid.). For us the key issue here is not so much of a technical nature (i.e. how this transformation is achieved), but concerns the shift in cognition it entails. How can we be sure that the resulting loss of information, the moving away from in-depth and shared qualitative knowledge, will not affect the very way political decisions are taken, the way political objectives are formulated, motivated and legitimized? How is it conceivable not to worry about the claim of a universal toolbox that is able to emancipate itself from all material, socio-historically-built and nationally-rooted specificities whatever the domain in which we are acting, as if such particularities should have no meaning and impact?

For by their very nature utopias cannot be achieved. The political and ethical prudence (Raynaud & Rials, 1992) should be to recognize this impossibility of realization and to conceive of utopian thought in terms of a series of markers that guide, but not determine, an endless pragmatic progress towards something that can only be loosely referred to. The problem with any utopia begins when the prince's advisors and the prince himself try to implement it as it is formulated, take it literally, as a blueprint for action and to transform social reality and expectations so that they come to strictly obey to the precepts of the utopia in question. In that case, far from liberating, utopia comes to confine freedom and initiative in a straitjacket, eventually destroying them and utopia itself.

In this volume, Martine Mespoulet (Chapter 2) examines how statistics and national accounting came to be invested with dreams and schemes aimed at creating a new socialist society and a new human being. Statistics
should help symbolically construct the (new) Soviet social and economic world, and reform collective spirit and behaviour. Mespoulet traces the tensions and twists and turns this involved. She shows how statistical debates were mingled with internal political rivalries and rifts. The new Bolshevik state had inherited an already well advanced statistical apparatus that had been developed in the Tsarist Empire in exchange with other western European countries. How could such an apparatus be adapted to the new political representations of society, where numbers were not only an information and decision support tool, but also an instrument of power designed to prove the soundness of state action?

The old guard of statisticians came to clash with the Bolsheviks. For the Bolsheviks, the production of figures was to be controlled by their immediate practical applicability, that is their usefulness in guiding actions and decisions. The autonomy of statistics as an independent science was thus questioned. The search for information became selective and had to satisfy political choices rather than statistical laws. As Mespoulet writes, “statistical law came to be perceived as contradicting the principle of political action, as it portrayed social processes as fatalistic [random, added] and the effects of political action on society as illusory”. A new quantification language had to be invented which did not resort to statistical theory as a resource (such as the law of large numbers and randomization). Yet, although national accounting seemed to provide such a new language (the accounting for input and output), statistics were never abandoned, Mespoulet shows. Statisticians learned to adapt to the new world. They “became a kind of ‘right hand’ providing the economistic planners with statistics needed for elaborating the plan, for instance for building blocks of flats, schools or leisure facilities”. Furthermore, a whole new area of statistics developed, based on economic forecasting and the construction of indexes. And especially from the 1950s onwards, Soviet statistics began to increasingly resemble those used in capitalist countries. As Mespoulet remarks, “the Soviet socialist system [...] had to demonstrate its superiority in the same economic and social fields as the capitalist countries, which meant that they tended to adopt the same tools, while re-interpreting their uses”. What separated socialist statistics from their western capitalist counterparts was thus far from clear. Such separation had to be actively forged, time and again and was often rooted in similarity.

Also Tong Lam (Chapter 3) investigates the multifaceted roles of numbers and calculative expertise in state-building, albeit of a different
kind. He turns our attention to China's new social credit system, a
national system that is currently being developed under Xi Jinping's
administration as part of the project of “The Chinese Dream” aimed at
rejuvenating the Chinese nation. For long, China's political and intellec-
tual elites have had the desire to create national citizens, motivated and
enlightened enough to participate in China becoming, as Lam puts it,
“a unified body politic to counter the encroachment of foreign coun-
tries”. More than one century later, the dream of engineering new
citizens is being drastically reformulated. Moving away from a paper-
based bureaucratic surveillance system that rests on the maintenance of
personal dossiers, Lam shows how the new social credit system seeks
to track, evaluate and modify the financial, moral, social and polit-
ical behaviour of citizens and companies with the help of new digital
“evaluative infrastructures” (Kornberger et al., 2017).

Lam highlights that this new system seeks to modulate behaviour
not via oppression, but gamification, individual responsibilization and
incentivization. Drawing on Foucault's writings on governmentality, he
points out that this system is “a technology of subjectivity and citizen-
ship that seeks to calibrate and modify the behaviour of individuals and
groups, compelling them to align themselves with the desired social and
political order as defined by the state”. Power is thus exercised indi-
rectly through what Foucault referred to as “the conduct of conduct”
(Foucault, 1991 [1979]). Responsibility and self-regulation are instilled
through a credit-point based reward and punishment system that affects
career and promotion prospects, possibilities of travel and mobility, and
much else besides. The numerical reward system creates incentives not
to simply obey, but to maximize one's score so as to enlarge one's field
of possibilities. The new focus, Lam argues, “is no longer on ideological
purity for political purposes but on trustworthiness as a basic condition
for economic efficiency”. In this respect, Chinese policy thinkers have
come to share many of the assumptions of (Western) rational choice and
game theorists. Lam cautions us to be careful not to demonize China as
the foreign Other, as the social credit system looks “at once dystopian
and strangely familiar”. Despite the many differences that exist between
China and Western market democracies, Lam emphasizes that the two
sides converge significantly in how their corresponding surveillance infras-
tructures have produced a new governing paradigm that, according to
Zuboff, has replaced “the engineering of souls with the engineering of
behavior” (Zuboff, 2019, p. 376, quoted in Lam).
Lam’s contribution prepares the ground for a number of questions on which other chapters in this volume seek to shed light. First, we should not forget that the effectiveness of the system relies on its ability to adequately capture the behaviour it seeks to modify, which is by no means a trivial (and often unattainable) task. Second, following the economics of convention (Diaz-Bone and Salais, 2011) social coordination does not necessarily obey to formal institutions, but is shaped by shared informal conventions of appropriate conduct. Such conventions are much more stable in the long run than the recourse to formal institutional rules. Hence, governing via credit scores might be much more difficult to achieve than envisaged, and we need to pay attention to the consequences of such uncertainty. Relatedly, we should also not underestimate people’s ability to game the system’s rules. Third, and finally, the chapter invites us to critically revisit and unpack what neoliberal governing entails. It reminds us of neoliberalism’s multiple manifestations and the increased blurring of differences between East and West.

Uwe Vormbusch’s chapter (Chapter 4) transposes us from dreams and schemes of national quantification to the Quantified Self (QS) movement. Born in California, the movement aims to obtain self-knowledge through self-tracking, using new digital mobile and wearable technologies. Self-tracking as such is not new (see e.g. the history of diaries and bathroom scales). Yet, digitization and automation equip quantifications of the self with new possibilities, allowing for ever more detailed and accelerated measurement that can be shared, compared and circulated on the web. Vormbusch explores how such quantifications bring forth new “taxonomies of the self” drawing special attention to the diversity of representational forms and moral conflicts contained in such taxonomies. Combining a Foucauldian approach (e.g. Miller, 1992) with studies of the economics of convention (Diaz-Bone & Salais, 2011; Boltanski & Thévenot, 2006 [1991]), which have highlighted the practical capabilities of individual actors enmeshed in conventions, he argues that self-quantification emerges as a contemporary “institution of the self” that does not displace but co-exists with other established “technologies of the self” (Foucault, 1988), such as religious confession and therapeutic and psychoanalytic approaches to identity and authenticity.

Following Foucault, Vormbusch considers power “as a productive network which runs through the whole social body, much more than as a negative instance whose function is repression” (Foucault, 1980, pp. 118). He stresses that self-measurement does not only lead to an
intensification of surveillance, coercion and self-discipline. It also opens
up new spaces for self-discovery and self-modulation. It is this tension
between autonomy and subordination that he is interested in further
exploring. Vormbusch shows that self-quantifiers are not necessarily using
new technologies and data uncritically. He portrays them as capable and
reflexive actors (Boltanski & Thévenot, 2006 [1991]) who are actively
inventing and manipulating technology to explore who they are and could
become. To be sure, such use of technology is not without problems and
conflicts. Vormbusch shows how quantifying your self is as much about
coping with new forms of cultural incertitude and precariousness as well as
keeping oneself “fit” and adept to today’s neoliberal “flexible capitalism”
(Boltanski & Chiapello, 2007).

There is a striking proximity between the social utopias of the self-quantifiers and the Chinese Dream of forging the body into a new object of knowing and governing via digital tracking, although both are situated at opposing ends of the spectrum of neoliberal governing. In the former case, we are dealing with a network of supposedly autonomous individuals who are seemingly free to choose what to measure and how to adjust their behaviour accordingly; in the latter case, we are dealing with a highly centralized apparatus of authoritarian control. Yet, both resort to benchmarking as a key instrument of neoliberal, market-oriented governance (Bruno & Didier, 2013).

The dream of the self-quantifiers is to make visible the self, to make
it comparable and manageable, which requires classification, scales of
evaluation, the decontextualization of observations and the application
of the same methodologies for all. How can one be sure not to lose
essential information about the self? The self-quantifiers Vormbusch inter-
viewed oscillate between confidence in numbers and worries, even despair,
about the numbers’ ability to grasp their (distinctive) selves. The metrics
introduce an irreducible distance between forms of objectified external
judgement and quests to learn more about ones’ (unique) self. Such
distance is also problematized in the contribution by Ota De Leonardis
(Chapter 5).

De Leonardis examines measurements of inequality and their implica-
tion in dreams of “indifferent power”. She shows how attempts aimed
at quantifying poverty and inequality were accompanied by a semantic
shift in which the meaning of inequality as a (historical) bond of
domination and subjection was being obscured. Inequality as defined by
quantification, she argues, “tends to designate a distributive difference, a
gap, a disparity: a distance, and no longer a tie". It has no longer a rela-
tional meaning that refers to power relations between unequal people,
where a bond is recognized between the "high" and "low" that creates
for both sides obligations and claims. She focuses in her analysis on
the dispositif of the *threshold*, in particular poverty thresholds, and their
effects on redefining welfare policies in Europe (above all Italy).

She highlights that “threshold” is not only a quantitative measure but
also a spatial metaphor which shapes social spaces with divisions and sepa-
rations. It is aimed at “governing at a distance” as Miller and Rose (1990)
would say. De Leonardis distinguishes between space and territory (or
place), a distinction also developed by Supiot (2008). Space refers to
abstract geometries (distance, direction, size, shape, volume) detached
from any material, living, cultural and historical contents. De Leonardis
interrogates how a “spatialized” configuration of notions of inequality,
helped by measurement and the definition of quantitative poverty thresh-
olds, represents the negation of any relationship between privileged and
deprived people, and especially one of domination. As she writes, when
inequality is captured in a quantitative format, a poverty threshold,
the “vertical configuration, which anchored inequality to burning issues
of power, politics, and institutions, is being obfuscated”. Questions of
inequality are reduced to “a comparison between linear positions and
intended merely as a matter of plus or minus, more or less, yes or no,
according to a binary code”. De Leonardis emphasizes that quantitative
poverty thresholds render inequality relative, and no longer relational (see
here also Townsend’s definition of relative poverty from 1979, quoted
in De Leonardis). Inequality loses its “absolute” that is, its societal
and political, dimension, as Sen (1983) would put it. Such “flattening
effects” of quantification come also to light in other contributions to this
volume. Quantification is thus far more than an instrument to envisage
and realize a new, “better” world. Quantification technologies, such as
poverty measurements or social credit scores, reconstitute the very object
they are asked to help create (“the ideal city” or “the ideal citizen”). As
Espeland and Stevens (1998, p. 323) write, quantification “reconstructs
relations of authority, creates new political entities, and establishes new
interpretive frameworks”.

Part II of this volume, to which we now turn, takes a closer look at the
implication of quantification in “politics of evidence”—attempts aimed at
undergirding policies with an “undebatable truth” produced via numbers.
The creation of such truth is not only difficult and laborious. What counts
as an undisputable fact, and the ways how such facts are produced, have changed over time, and therewith also the very meaning of facticity itself.

## THE POLITICS OF EVIDENCE

Numbers have come to be integral to how democracy is justified and operationalized (Rose, 1991). To paraphrase Rose (1991, p. 684), to govern legitimately does no longer mean to govern at the mercy of opinion and prejudice, but to govern in the light of quantifiable facts (see also Porter, 1995). Although “evidence-based policy making” has a long history that spans several centuries, it gained renewed popularity—particularly in the Anglo-Saxon world—with the rise and spread of New Public Management. Evidence-based policy making is based on the assumption that public policy decisions should be grounded in rigorously established “objective evidence” (facts), rather than “common sense” or ideology. To become fact, knowledge should be detached from both the context of observation in which it was generated and contemporary theoretical controversies (that are relegated to the rank of ideologies) (Salais, 2016).

Daston (1992) has coined such objectivity as “aperspectival”. Numbers are often seen as a crucial element in realizing an aspiration to “escape from perspective” (Daston, 1992) and to obtain a univocal, impersonal interpretation of the phenomena around which political decisions come to be framed (Samiolo, 2012). The objectivity of numbers, in turn, following Porter (1992), is rooted in standardization, a process whereby decisions are “linked to replicable calculative methodologies which are seen to transcend individual subjectivity and deemed universally applicable” (Samiolo, 2012, p. 383). Yet, how the objectivity of numbers is generated, stabilized or disrupted, is culturally contingent and context-specific (Fourcade, 2011; Samiolo, 2012).

Alain Desrosières’ works (see e.g. Desrosières, 1998 [1993], 2008) as well as studies by the economics of convention (see e.g. Diaz-Bone, 2016; Salais 2016; Thévenot, 2001) have shown that the production of objective quantitative evidence relies on conventions of measurement, categories and classifications that are rooted in specific socio-historical processes and projects of nation-building. These conventions, categories and nomenclatures are historically and geographically contingent, as for instance studies of changes in the measurement and categorization of employment and unemployment or the professional occupations have
demonstrated (Boltanski, 1987 [1982]; Desrosières & Thévenot, 1988; Salais et al., 1986).

The Baconian dream of eliminating variation due to the specificity of context and different theoretical foundations of debates—when transposed to the social—is impossible to achieve. Evidence-based quantification in itself is an utopia one might say. The contributions collected in this part of the volume trace different aims and modes of intervention that have come to be attached to quantification-based politics of evidence over time and in different settings. Following the economics of convention, they highlight, amongst other things, that it is important to accept a plurality of positions and perspectives as valid in the search for evidence. Amartya Sen referred in this context to “positional objectivity” (that he distinguished from subjectivity) arguing that “the idea of objectivity requires explicit acceptance and extensive use of variability of observations with the position of the observer” (Sen, 1990, p. 114).

A key element of evidence-based politics are state statistics. In this volume, Thomas Amossé (Chapter 6) traces the history of France's public statistical infrastructure aimed at knowing its population. The chapter distinguishes between three different models of quantification that came to sustain the relationship between the French State and its statistical citizens since 1950. Although these models appeared successively, they co-exist today. These are the “representative household survey” (which emerged in the 1950s), the “biographical investigation” (which was developed in the early 1980s) and “the matched panel” (which emerged at the end of the 1990s). According to Amossé, “these models articulate, each in a specific way, social science theories, statistical methodologies, and public action conceptions”, and they correspond to three different types of “statistical being” (homo statisticus)—subject, person and individual—modelled on Supiot’s exploration of the development of the legal subject (Supiot, 2007 [2005]).

Imported from the US in the 1950s, the representative household survey sought to provide a snapshot of society. The surveys were aimed at representing the entire population and became one of the most important sources of social and demographic statistics. Their main variables (such as age, gender, income and socio-professional categories) were primarily of an administrative nature and assumed to be unanimously and uniformly understood. Amossé shows that, today, such surveys have not disappeared, but they have become supplanted with other statistical tools. Biographical investigations, born out of social scientific reflection and
critique in the 1980s, gave less primacy to standardized, institutional categories and questions of statistical representativeness. They focused on the tracking of a respondent's individual trajectory (birth, move, promotion). Grounded in interpretive sociology, they were based on the assumption that the individual bears multiple identities which must be explored. Both models (household surveys and biographical investigations) respected the respondents as owners of a practical experience deemed valuable for the formulation and implementation of public policies. In contrast, the third form of statistical infrastructure (the matched panel) that Amossé explores is of a very different nature.

It responds to a micro-causalist agenda, where the statistical infrastructure is not focused on individuals as persons or members of the collective entities to which they belong (e.g. a household). Rather, the “statistical beings” making up matched panels can be seen as “dividuals” (Appadurai, 2016; Moor & Lury, 2018) resulting from an assembling of matched data, multiple data marks and imprints. As Amossé writes, matched panels are based on “libraries of information which, for each respondent, store a great number of fragmentary and heterogeneous pieces of a puzzle, which are put back together once they have been re-aggregated to represent the targeted individuals”. In this form of statistical infrastructure, the metrological objective is preeminent. The collected variables rarely, or only secondarily, refer to practical experience or institutional categories. Statistical data are “purified” and abstracted from context and convention.

The theme of abstraction is also of importance in the politics of evidence examined by Laurent Thévenot (Chapter 7). Thévenot examines sustainable palm oil certification as a new mode of global governing that operates away from states. Voluntary governing schemes, such as that of the Roundtable for Sustainable Palm Oil (RSPO), have gained legitimacy through the implementation of multi-stakeholder governance. Thévenot interrogates what such governance arrangements entail. He argues that “governing by standards” has shifted the political debate about power, legitimacy and the common good to questions of measurable certifiable characteristics of products and services that are to be chosen by “autonomous opting individuals”. What kind of alternative to the rule of law do certification standards offer? How do actors, including local smallholders in developing economies, cope with the standards’ reliance on measurable objectives? What does this format of governance, and the liberal grammar underpinning it, do to voices of concern? These are some of the central questions Thévenot explores.
Building on his earlier research on the politics of statistics (Thévenot, 1990), economics of convention (Eymard-Duvernay et al., 2006), investments in form (Thévenot, 1984), orders of worth (Boltanski & Thévenot, 2006 [1991]) and the plurality of regimes of engagement (Thévenot, 2006, 2015), Thévenot studies governing by standards “in action”. This demands close-up fieldwork, including following the most vulnerable actors, from their daily life in remote rural areas to their participation in the “open spaces” of the public roundtables that are a key element of the certification process.

As Thévenot writes, each year the general assembly of the “Roundtable on Sustainable Palm Oil” (RSPO) meets in a “convention” which votes for resolutions and changes to the standard (of sustainable palm oil). Thévenot describes the arrangements and procedures designed to allow for wide participation in deliberations over the standard. These procedures urge participants to formulate their voice in a particular manner—as “engagement in a plan” and “in a format of individual choice between optional plans”. Discussions are organized in an open space akin to a marketplace, where participants shop for information and ideas. Scrutinizing the liberal grammar of the “open space technology”, Thévenot shows how it transforms (and limits) participants’ (in this case a smallholder and representative from a local community) ability to engage in critique. The “open space technology” does not fit “grammars of practice which support pluralist constructions of commonality and difference”. Thévenot shows that to be truly heard and understood requires the training of rhetoric abilities, the learning and use of the right language, and concepts specific to the object.

The registration of a complaint with the RSPO (here a complaint that the rules of the certification standard were not being properly implemented by the corporation) demands its “right formatting” in accordance with RSPO’s standards. “Local familiar” and “customary formats” of evidence have to be translated into evidence legible by the organization (in this case the RSPO)—quantifiable and auditable markers, which in turn limit the very possibility to articulate dissent. For such transformation deprives the most vulnerable (local smallholders, communities and NGOs) of their primary resource: practical knowledge.

Such “dogmas of universal competition” (Supiot, 2009) and standardized “best practice” are also present in the case of implementation of development aid in Mali, which Ousmane Ousmarou Sidibé studies in this volume (Chapter 8). When writing his contribution, Sidibé was a
senior civil servant of the Malian government. Hence, he speaks not only as a researcher, but also as a participant.

In a quest to make development aid more efficient and effective—to reduce waste and transaction costs and enhance accountability—govern- mental and non-governmental organizations involved in the provision and use of development signed on 2 March 2005 the Paris Declaration on Aid Effectiveness which, amongst other things, commits donors and recipients of aid to “management by results”, a shift from “project aid” to “budget support”, increased coordination and mutual accountability. Performance indicators have become a cornerstone in the implementation of the declaration.

Sidibé explores how “management by indicators” contributed to the undermining of public policies in Mali focusing on the cases of education and public health. Amongst other things, he highlights that a national indicator, by its very nature, does not reflect the conditions and results of a public policy in distinct geographic areas. In Mali, there are large dispar- ities between regions. Such regional differences are not captured by the national indicators that average local results. Likewise, the public health indicator stating the percentage of the population that lives within five kilometres of a functional healthcare centre (56% in 2013) does not say much about the actual accessibility of healthcare. Accessibility to health- care is shaped by many more factors than geographical distance, such as availability of appropriate medications, staffing levels, and staff’s exper- tise. Another problem of performance-based management to which Sidibé draws attention consists in the difficulty to reach consensus on targets. As Sidibé states, “the aims of public policy are multiple, and sometimes contradictory, so reaching consensus can be extremely laborious”.

How can under such circumstances a new social contract be devised, which sets reciprocal obligations for families, communities, local author- ities, civil society and the national government, Sidibé asks. According to him, “performance indicators have become a formidable tool in the hands of a few international experts, who insidiously impose far-reaching public policy choices on states, in the absence of any real debate among citizens”. Paradoxically, the states with the least institutional capacity to handle the weighty apparatus of “management by indicators”, are often those on whom donors impose the most stringent terms of conditionality, because these states lack the capacity to negotiate. This does not mean that management by indicators should be abandoned altogether. But Sidibé warns against its blind, mechanical application. As he concludes:
"An indicator should be just that, literally furnishing an indication of the quality of governance, but not in itself a full appraisal of quality. From this point of view, indicators can send a warning on the state of public policy, and foster discussion, without issuing a judgement with no appeal, and are much less a guilty sentence".

Also Corine Eyraud examines a case of “management by indicators” (Chapter 9). She turns our attention to the development of govern-
mental performance indicators for French universities. As a participant
observer, she followed the numbers from their birth through their
detailed construction to their concrete uses. The development of these
indicators began in France in 2001 with the “*Loi organique relative aux
lois de finance*” (LOLF) that took effect in 2006. This law sought to
bring New Public Management (NPM) ideas to France. One of its main
objectives was to make the government and the public services account-
able to parliament for the results of their actions. The law further sought
to give more power to parliament over budgetary policies and choices.
Lastly, it sought to reform the allocation of resources to administrations
and public services. Yet, from the three projected uses of “management
by indicators” only the third one was actually realized.

Eyraud shows that MPs did not pay much attention to numerically
based performance reports in budgetary debates. First, the LOLF did
not link performance to budgetary funding. Second, the MPs did not
find the indicators particularly meaningful in relation to public policy
making. They did not participate in their construction and found the
indicators too technical and too detached from their concerns. Yet, a
few years later, the performance indicators (e.g. number of publishing
academics, number of PhD degrees delivered, undergraduate success
rate, number of master degrees delivered, the rated research quality of a
research centre) became an essential element in a new system of university
resource allocation, called “Sympa”. From 2009 onwards, a university’s
performance became financially rewarded, while non-performance was
financially punished. This new way of funding introduced competition
amongst universities and lead to various forms of “reactivity” (Espeland
& Sauder, 2007), including gaming and the redirection of financial and
human resources from teaching towards research. Yet, at the same time,
Eyraud also describes how this system became contested, especially by
academics, and eventually abandoned under Hollande’s government in
2012.
Eyraud highlights that the various policy reforms and implied quantification instruments did not form a very integrated assemblage. The changes that the performance measures were supposed to help bring about were at the same time significant and very limited. Similar to Sidibé, also Eyraud does not seek to argue against quantification per se. But, she cautions, citing Supiot (2012), that one should not confuse measurement with assessment. Furthermore, the setting of indicators should not become “a way of surreptitiously encapsulating values and hierarchies”. Rather, she pleads for the opening up of quantification, the setting and use of performance indicators, to public debate and scrutiny, which brings us to the third and final part of this volume, Part III, devoted to exploring the changing relation between numbers and democracy.

## VOICING FOR DEMOCRACY

In democratic political systems, the law guarantees citizens the freedom of opinion and expression, including the right to demonstration and protest (see here also Articles 19, 20 and 21 of the 1948 Universal Declaration of Human Rights of the United Nations). How does the rise and spread of “governance by numbers” (Miller, 2001; Supiot, 2015) affect individual and collective capacities to exercise voice? Quantification may be motivated by a democratizing ambition, the desire to hold to account, and to counteract despotism and arbitrariness (Alonso & Starr, 1989; Cohen, 1982; Kurunmäki et al., 2016; Porter, 1995). Yet, numbers also change how we perceive things, how decisions are framed and how concerns become articulated. Numbers promise a “de-politicization” of politics. But as Rose (1991, p. 676) remarks, “numbers do not merely inscribe a pre-existing reality. They constitute it”. And with that new conduits of power are brought into being (see also Miller & Rose, 1990). “Numbers delineate fictive spaces for the operation of government” (Rose, 1991, p. 676). In so doing, they generate new forms of visibility and invisibility. They create new actors and new relations which might thwart political engagement and participation.

Contributions assembled in this part interrogate possibilities for the incorporation of voice in numbers. To paraphrase Morgan (2010), they examine the ways in which quantification can (or cannot) express citizens’ experience about political, economic, and social arrangements that affect them. They also scrutinize the relationship between quantification and public debate (Mennicken & Espeland, 2019, pp. 232–233),
and investigate the role that numbers play in generating and framing public discussions and deliberations, for example about public goods and services, such as public security, fiscal policies or employment. Finally, they query prospects for a pluralization of quantification (ibid.). They examine how numbers can come to be unsettled, challenged and changed through the development of alternative measures, “counter-quantifications”, as the literature on “statactivism” has highlighted (Bruno et al., 2014).

Andrei Guter-Sandu and Andrea Mennicken (Chapter 10) use the case of prison privatization in England and Wales to scrutinize what it means to “economize the social” through numbers. Guter-Sandu and Mennicken show how ratings and rankings of organizational entities, such as hospitals, universities or prisons, are often closely linked to aspirations aimed at facilitating competition and the establishment of (quasi) markets in the public services. Further, they highlight that particularly over the past fifteen years or so, we have witnessed an increase in quantified social impact assessments seeking to make the value of public sector work knowable in financial terms not only for evaluation purposes but also to attract (private) investment. Guter-Sandu and Mennicken analyse this multiplicity of quantification and its implication in different processes of economizing distinguishing between activities aimed at curtailing, marketizing and financializing.

Tracing the history of quantification and performance measurement in the HM Prison Service of England and Wales, they attend, first, to the introduction of prison performance metrics in the 1990s which, amongst other things, was stimulated by prison privatization and concerns with the accountability of prison governors. They examine then the evolution of these metrics, including their translation into aggregated prison ratings from the early 2000s onwards. Underlying the introduction of the prison ratings, the authors argue, was a belief in the power of market incentives and the aspiration to govern through competition. But the chapter also shows that we need to be careful not to equate quantification with economization. It describes how measures seeking to capture the quality of prison life from a prisoner's perspective were introduced to “moralize” the prison ratings (Liebling, 2004). Of course, we need to be cautious when labelling this as democratization. Nonetheless, the performance measures served as an important platform for debate about prison values and reform, not least because of the public attention and criticism they attracted.
Yet, these “moralized” measures were, in turn, destabilized in the wake of the government’s austerity policies. Concerns with the measurement and management of costs came to the fore which overruled the Prison Service’s “balanced” performance measurement system. Ironically, contracted-out private prisons were largely spared from these cuts, due to the inflexible nature of the 15- or 25-year contracts under which they were operating. Thus, they were largely shielded from economization in the form of budgetary savings requests. This does not mean that private prisons are not economized, but different mechanisms of economization (and quantification) are at work here, which the authors disentangle examining experimentations with Social Impact Bonds (SIBs). These mechanisms of economizing relate first and foremost to processes of financialization and a logic of (financial) “capitalization” (Muniesa, 2016; Muniesa et al., 2017) where prisons and prisoners come to be viewed as (financial) assets, as vehicles for the generation of future returns. Guter-Sandu and Mennicken conclude by cautioning us to be mindful of the multiple ways in which quantification and financial concerns come to be interlinked—reinforced, mitigated or undermined.

Subsequent chapters (see in particular Chapters 11 and 12) explore in what ways and under what conditions quantification can be turned against programmes of marketization, financialization and austerity. They examine instances when quantification is subjected to scrutiny, debate and critique; when forms of disruption are sought that go beyond “gaming the numbers”; when numbers become (re)attached to dreams and schemes of doing things differently.

Boris Samuel’s analysis (Chapter 11) focuses on the struggle against high living costs in Guadeloupe in 2009. He investigates a case of “stat-activism” (Bruno et al., 2014), where calculation and figures came to be used as a “weapon” by a social and civic movement, led by local trade unions, to fight what they identified as “pwofitasyon”. “Pwofitasyon” [in French: profitation] is a Creole term that denotes the capturing of undue profit resulting from the existence of excessive sales prices, particularly in relation to basic consumer goods, such as food. Samuel shows how the movement, called LKP [l’alliance contre la profitation], engaged in the calculation and collection of data to revaluate purchasing power and challenge the setting and regulation of prices by the administrative authorities. Samuel assesses to what extent “the statactivistic momentum” of the LKP and other non-state actors was capable of shifting generally accepted price measurement methods and, more generally, debates on price.
His analysis shows that the struggles with numbers lead to unequal outcomes, in which technical but also relational resources determined the balance of power between the actors. The alternative calculations (counter-quantifications) put forward by the LKP were effective in generating a public debate on “pwofitasyon”, yet, at the same time the measurements came to be deemed as “too simplistic” to be considered legitimate by the public authorities. Instead, a statistically more sophisticated analysis of price differences between Guadeloupe and mainland France undertaken by the INSEE (France’s Institute of Statistics and Economic Studies) became an important reference point in the negotiations. But here the reported price differences rested on averages, and the reported average gap of approximately 15% made it impossible to expose the abusive pricing of individual goods, for example chocolate powder or yoghurt, where price differences could be as large as 100% and more.

The common and rigorous statistical methods used by the INSEE were thus not socially acceptable and led to further controversy and social unrest. Yet, the report formed the basis for the development of a new strategy of communication on price differentials. This strategy represented prices no longer on the basis of average values, but focused on the representation of particular extreme values which, in the end, came to be considered a fairer representation of the inequitable situation lived by many Guadeloupians. This strategy was supported by a report of the Competition Authority which identified several violations of competition law in the large-scale retail and import sectors. This report, Samuel writes, “turned each price, as experienced by the consumers in their everyday life, into an indication of abuse and injustice, deserving to be discussed and publicly denounced”.

Samuel’s study helps gain a deeper understanding of the multiplicity of price level measurement and the shifting legitimacies associated with it. It also shows that the increased complexity and sophistication of statistical techniques may reduce possibilities for public scrutiny and the utilization of quantification as an emancipatory device. Further, Samuel’s analysis raises important questions about what should count as “right and fair” statistical proof in a democratic debate, and in what way statistical data are, or should be, able to capture lived experience, a topic which also Robert Salais’ contribution addresses (Chapter 12), to which we turn next.
Salais investigates the development and transformation of a social and statistical category, namely that of unemployment, in three major European countries (France, Germany, Great Britain) and at European level (Salais, 2007). In his analysis, Salais differentiates between statistics and governance-driven quantification. He shows that both rely on quantification, but differ with regards to the political status of social and cognitive conventions. As he writes: "The purpose of statistics is to build *general knowledge* 'extracted' from the plurality and variety of *social conventions* people use in daily life to understand their world [...]. The purpose of governance-driven quantification is to find ways to *rationally transform social conventions* toward some pre-given political objective, judged by the centre as optimal". According to Salais (but see also Desrosières, 1998 [1993]), in statistics, the establishment of facts logically precedes the design and implementation of public policies. In governance-driven quantification, the "fabrication" of facts is internal to public policies and driven by the search of maximizing these policies' quantitative performance. Put differently, the ultimate outcome (or aim) of "governance by numbers" is to modify the conventions upon which people rely as landmarks to identify what can be their legitimate claims.

Rather than being rooted in collective deliberation, the informational basis of governance-driven quantification is predetermined and imposed by “the Centre”; it incorporates norms without discussion and directs the decisional process towards prefixed political outcomes. These norms are mostly incorporated into technicalities (e.g. definitions of operational categories). All this creates a move towards what Salais terms an “a-democratic regime” of quantification. According to Salais, “a-democracy” is a political regime that maintains the formal procedures of democracy, but impedes any effective participation of citizens and other actors who could speak on their behalf (see here also Crouch’s definition of post-democracy, 2004).

Salais shows how European employment policies came to be based on such governance-driven quantification and “a-democracy”. European authorities substituted the search of Keynesian full employment for the maximizing of the rate of employment as their main target. In this new regime, employment took on a very different meaning, encompassing any job, regardless of wage, working conditions, duration, or type of labour contract. Salais goes on to explore ways by which this turn could be counter-acted and social justice expectations be brought back into quantification processes so that another understanding of the collective issue
to deal with can be developed. For him, producing and interpreting data should thus be seen as a collective undertaking. Informants (e.g. people who are asked to respond to a survey on employment) should be considered as active interpreters bringing with them valuable practical experience and knowledge that should be used in defining the issue at hand (e.g. helping to arrive at a collectively shared understanding of what should or should not count as employment).

Quantification, in this context, has to become legitimate in terms of both fairness and correctness of the data it helps produce. Drawing on Amartya Sen's concept of “the informational basis of judgement in justice” (IBJJ) (Sen, 1990; but see also Salais, 2019), Salais argues that a major aim of quantification should be the generation of an informational basis which has not only been produced with the help of rigorous methodologies, but satisfies also accepted requirements of justice. This informational basis is thus no longer merely objectified “aperspectival” evidence reflecting reality; it is also elaborated by (lay) people through the prism of their own feelings on what is or is not justice and injustice, taking into account relevant features of their “factual territory”. Such an understanding of quantification opens up the possibility of a plurality of “data-makings” for the same situation. It also does not oppose qualitative and quantitative methodologies and, more importantly, has as its foundation effective freedom.

Also the chapter by Emmanuel Didier (Chapter 13) problematizes the divide between qualitative and quantitative methodologies. Examining the history of what is now called “qualitative sociology” in the US, Didier asks how we can account for the political production of the border of qualitative enclaves which exclude quantities. The founding fathers of sociology never chose between quantification and non-quantification. So, how did the conceptual pair “qualitative vs. quantitative” come to settle within sociology?

Didier pays attention to both the epistemic and political forces that participated in the production of the border between the qualitative and quantitative in sociology. His analysis begins with a discussion of Herbert Blumer's *Symbolic Interactionism*, who located the social primarily in situations of interaction. Deeply influenced by American pragmatism, he examined how a member's action is guided and formed by a process of interpretation. Blumer was against surveys (as e.g. conducted by Paul Lazarsfeld at the time), but he was not against quantification per se. Next to symbolic interactionism, ethnomethodology, originally developed by
Garfinkel in the mid-1950s, elaborated another criticism of statistics. As Didier writes, ethnomethodology is aimed at developing “a generalized social system built solely from the analysis of experience structures”. But also ethnomethodological criticisms of quantification did not oppose all and every quantification. Indeed, Garfinkel was probably the first to take a sociological interest in examining the production of statistics, as early as 1956, arguing that the process through which quantitative rates are produced should be conceived as a socially organized activity.

Later, qualitative sociologists, such as Becker and Horowitz, labelled as “the radicals” by Didier, became more defensive when trying to fight the wave of quantitative scholarship that washed over their discipline. Glaser and Strauss’s publication of *The Discovery of Grounded Theory* consolidated the divide between the categories of “qualitative” and “quantitative” further. Today, Didier shows, qualitative sociology has become a category where two sets of “good examples” of published papers he examined are in opposition. On the one hand, there are those which belong to a “Lazarsfeldian” cluster where qualitative and quantitative are in a hierarchy and the former is serving the latter. On the other hand, there are papers pertaining to an “interpretative” definition of the qualitative which seeks to set itself apart from “quantitativist” uses of qualitative information. Didier concludes by cautioning us not to forget that such a divide had been produced over time, and that many of the classical qualitative sociologists had criticized a certain method of quantification (surveys and opinion polls), not the general use of quantities. It is neither possible (nor desirable) to completely wipe out quantities from an epistemic system. Rather, we ought to scrutinize their production.

In this respect, both ethnomethodology and symbolic interactionism bear strong proximities with the economics of convention, an approach which was developed in France in the 1980s, amongst other things, by statisticians who at the time were working for the INSEE (France's National Institute of Statistics and Economic Studies) (see also the special issue of *La Revue économique*, March 1989 [edited by Dupuy et al., 1989]). Now the approach has taken hold more widely in sociology, socioeconomic and history (Desrosières, 2011; Diaz-Bone, 2018 [2015]; Salais et al., 2019). The developers of the economics of conventions approach tried to converge American pragmatist sociology with their own lived experience as state statisticians. This unique positioning enabled them to move beyond “positivism” and “structuralism”, beyond
a sterile division between qualitative and quantitative approaches, which
also Didier argues against.

In this context, it is also worthwhile to recall Alain Desrosières’
notion of the “convention of equivalence”, which has largely escaped
North-American sociology, including more recent (qualitative) studies
of quantification. Conventions of equivalence (commensurate scales as
Espeland & Stevens, 1998, would put it) allow the rise to generality, from
the singular (by essence qualitative) to the general (based on numbers).
They ensure continuity from the qualitative to the quantitative, instead
of separation, opposition or domination. Such a perspective considerably
enlarges the scope and ambition for the study of social life, including
practices of quantification.

Many of the contributions assembled in this volume draw on the
economics of convention in their study of quantification. Others, as we
have highlighted earlier, examine governing by numbers with reference to
Foucault, in particular Foucault's works on governmentality. This volume
seeks to engage these two strands of research in a critical dialogue.
Where does the economics of convention approach meet Foucault? And
what does such a joining up bring to the furthering of debates about
quantification and the politics of numbers?

QUANTIFICATION: WHERE THE ECONOMICS
OF CONVENTION APPROACH MEETS FOUCAULT

Neither the economics of convention (EC) nor Foucauldian studies of quantification represent coherent and unitary research programmes. As Diaz-Bone (2019, p. 311) recalls, “EC was projected not as a coherent paradigm, but as a scientific movement, organized around some core concepts and methodological positions. EC has developed the concept of conventions as logics of coordination”. Also Foucauldian studies of quantification do not form a “school”. To borrow Colin Gordon’s (1991) apt way of characterizing governmentality research three decades ago, studies in this area amount to a “zone of research”, rather than a “fully formed product” (Mennicken & Miller, 2012, p. 18).

Both the EC and Foucauldian studies of quantification are concerned
with relations between “quantified objectivity”, as Thévenot writes in this
volume (Chapter 7), “and modes of governing that make the world calcu-
lable”. Both seek to examine the various ways in which the administering
or governing of lives in a wide range of settings has been made think-
able and practicable through quantification. Peter Miller, who laid the
foundations for governmentality studies of quantification with Nikolas
Rose in the early 1990s in the UK (Miller & Rose, 1990; Rose &
Miller, 1992; but see also Hopwood, 1992), highlighted that accounting
numbers have a distinctive capacity for “acting on the actions of others”,
one that goes far beyond the abstract injunctions of economic theory
(Miller, 1992; but see also Mennicken & Miller, 2012 for a review of
Foucauldian studies in accounting). Also Alain Desrosières, who initi-
ated a sociologically reflexive turn in the study of statistics in France
and was involved in the development of the economics of convention
approach, was interested in examining questions related to the governing
by numbers. He associated different modes of government with different
modes of quantification, distinguishing, amongst other things, between
five forms of state and associated (different) modes of quantification, the
neoliberal state being one amongst others (Desrosières, 2003) (but see
also Diaz-Bone & Didier, 2016, pp. 14–15).

Nonetheless, for long, both approaches did not take much note of each
other. Curiously enough, in France, the founders of the economics of
convention were aware of Foucault’s work on nomenclatures (Foucault,
1966), but they did not take cognizance of Foucault’s works on govern-
mentality (Diaz-Bone & Didier, 2016, pp. 14–15). One reason for this
might be the fact that these works became only widely available in French
in 2004 (see Foucault, 2004), whereas Foucault’s lecture on govern-
mentality delivered at the Collège de France was translated into English
as early as 1979 by Colin Gordon (Foucault, 1979), a British philoso-
pher who had attended Foucault’s lectures at the time. Some years later,
Gordon co-edited *The Foucault Effect* with Graham Burchell and Peter
Miller (G. Burchell et al., 1991), which contained further English trans-
lations of Foucault’s works and became a cornerstone in Anglo-Saxon
governmentality studies.

For the EC, statistics and other forms of calculative practice have to
be related to the foundational conventions of data production (measure-
ment) and data interpretation, modes of justification and orders of worth,
to be fully understood (see Thévenot in this volume, Chapter 7, but see
also Diaz-Bone, 2019). In contrast, Foucauldian analyses of quantifica-
tion draw attention to the inherently political character of calculation.
They highlight that accounting and other numbers, through their ability
to produce certain forms of visibility and transparency, both create
and constrain subjectivity (Miller, 1992; Miller & O'Leary, 1987). This creates distinctive possibilities for intervention while potentially displacing others (see also Mennicken & Miller, 2012, p. 7). Yet, despite differences in theoretical heritage, in our view, and as the contributions to this volume demonstrate, the EC and Foucauldian approaches converge in at least three important respects.

First, both are concerned with the study of practices of quantification. Instead of concentrating on the interests of politicians, scientists or bureaucrats, both seek to investigate and unpack different stages in “the statistical [or accounting, added] production chain” as Thévenot puts it in this volume, from data collection, classification, codification, to the processing of information and its effects on the “making up” (Hacking, 2002) of people and entities. As Diaz-Bone (2019, p. 309) writes, “both have an anti-substantialist ontology: properties, qualities and valuations of people, objects and actions are results of practices”. Such a focus on practices of quantification helps to develop a more nuanced understanding of the different capacities and roles that numbers have come to assume in political life. It helps generate insight into the inner workings of accountability regimes, their changing nature, and the emergence of new regulatory spaces and practices.

Second, both approaches are interested in examining the variable ways in which the capacities and attributes of subjects are constituted, shaped and changed, through quantification. Both do not “posit a universal form for the human subject” (Mennicken & Miller, 2014, p. 15). See here, for instance, Vormbusch’s study of the emergence of new taxonomies of the self in this volume (Chapter 4) or Thévenot’s unfolding of different regimes of engagement with standardization and quantification (Chapter 7).

Third, as Thévenot highlights (Chapter 7), both seek to move beyond “the state” and “the neoliberal” as an all-encompassing notion (see here also the contributions by Mespoulet, Lam, De Leonardis, Guter-Sandu and Mennicken, and Salais in this volume). Both are interested in developing what Raffinsøe et al. (2016) have termed a “dispositional analytic” of quantification (see also Diaz-Bone, 2019). Both draw attention to the implication of quantification in what Foucault termed “dispositif” or “apparatus”, “a thoroughly heterogeneous ensemble consisting of discourses, institutions, architectural forms, regulatory decisions, law, administrative measures, scientific statements, philosophical, moral and
philanthropic proportions – in short: the said as much as the unsaid” (Foucault, 1977, p. 299, quoted in Raffnsøe et al., 2016, p. 278).

In so doing, both approaches share a relational and processual understanding of power and the state. Power is not a property—something that can be possessed. For what defines a relationship of power, according to Foucault, “is that it is a mode of action that does not act directly on others. Instead, it acts upon their actions, whether an existing action or one that may arise in the future. And, the ‘other’ over whom power is exercised remains resolutely a person who acts, who is faced with a whole field of possible actions and reactions” (Foucault, 2001 [1982], pp. 341–342, cited in Mennicken & Miller 2014, p. 15).

However, one concept that is absent from Foucauldian studies of quantification which is central to the EC is the notion of “convention”. As Thévenot points out in this volume, in the economics of convention, activities of “in-forming, trans-forming and formatting through invested conventional forms are central operations, because they sustain coordination power under uncertainty” (see also Boltanski & Thévenot, 2006 [1991]; Thévenot, 1984). Comparing France and USA, Storper & Salais (1997) focus on the plurality of conventions of the state on what people agree on the reciprocal roles and actions of citizens and state institutions with regards to defining, quantifying and contributing to common goods (see also Salais, 2015; Salais & Storper, 1993). The economics of convention approach is interested in the pluralism of (different) modes of evaluation (and quantification) constituted by conventions, orders of worth, modes of coordination, worlds of production and regimes of engagement (Boltanski & Thévenot, 2006 [1991]; Eymard-Duvernay, 1986, 1989; Salais, 2006; Salais et al., 1986; Salais & Storper, 1993; Storper & Salais, 1997; Thévenot, 2001, 2007).

Here, authors seek to break down policies and politics into a variety of modes of coordination (e.g. market, industrial, civic) or worlds of production (e.g. interpersonal, market, industrial, immaterial) (see the chapters by Thévenot, Salais and Vormbusch). This allows the EC to account more systematically for differing voices and evaluative orientations, conflict and contestation. It also makes it possible to draw more explicitly attention to the agency of participants and “their capacities of critique”, as Vormbusch points out (see Chapter 4). Put differently, the EC makes us query to what extent people “have a grip” (Bessy & Chateauraynaud, 2014 [1995]) on the specificity of the situation, are able to challenge and change its definition, and the way in which numbers work.
Yet, in both approaches, human freedom is always present. How can we then conceive the dynamics of socio-historical processes? How can we draw renewed attention to the diverse arts of government, resistance and freedom—to the conflicts and compromises that are the engine of history? Foucault deeply acknowledged the contradictory and dialectic (Grant, 2010) nature of historical processes and was always concerned “with the multiple and dispersed surfaces of emergence of disparate and often humble practices” (Miller & Napier, 1993, p. 633). Nonetheless, as Raffnsøe et al. (2019, p. 162) highlight, a preoccupation of scholarship with the image of “discipline as subjugation” led some to reinstate the very dualism between power and freedom that Foucault’s notion of power sought to overcome (see also Foucault, 2010, 2011) (for a critique see Jameson, 1984).

The economics of convention approach seeks to overcome such dualism by explicitly recognizing that coordination in real situations is structured by a plurality of conventions (Diaz-Bone, 2018). In so doing, it makes recourse to actors’ competencies to master and recognize the plurality of conventions; to their ability to use different grammars for interpreting the situation of coordination they face. Yet, under what conditions and circumstances can such competence be assumed and assured? This, in our view, is something that warrants further exploration, also in relation to the production and use of numbers in economic and political life.

We ought to acknowledge that “real situations” are often characterized by inequality and asymmetrical power relations. Inequalities exist, for example, with regards to access to public life; the knowledge and expertise participants possess; economic resources; control over conditions of work (and life more generally); recognition and respect for cultural differences; age; gender; class; race; and much else besides. Such inequalities shape the capacity to exercise voice, including the capacity to exercise voice in the production and use of numbers. Amartya Sen has developed the idea that society should promote equality in the space of *capabilities* (see e.g. Sen, 1992). We propose that both Foucauldian studies of quantification and the economics of convention would benefit from making use of Sen’s concept of *capability* (see also De Leonardis et al., 2012).

Sen acknowledges that persons are not similarly situated in their capability to convert resources brought by the situation to freedom of choice. Sen’s notion of capability captures both competency and effective freedom to act—the ability to choose the life one wants to live
from amongst a wide variety of valued functionings to which one has
effective access (Sen, 1992, 1993). According to Sen, capabilities are
not only a function of fixed personal traits and divisible resources, but
also social relations, organizational and institutional environments, and
the practical configuration of situations, in short, what Foucault termed
“dispositif” (see also Salais’ chapter in this volume and Salais, 2011).
Struggling against inequalities in capabilities to understand numbers and
their production should be at the heart of concerns with effective democ-
racy, even more so today, where numbers have taken an unprecedented
rise in the governing of our lives.

In conclusion, we think it is time for a renewal of the study of the
politics of numbers. The two strands of scholarship brought together in
this volume move quantification scholarship beyond the tired dichotomies
between autonomy and discipline, compliance and resistance, power and
freedom by moving our attention to the processes of quantifying and
calculating, and the possibilities for action these open up or foreclose.
In so doing, they do not only provide in-depth empirical insight into
the multi-varied nature of governing by numbers and its consequences
in different sites. They also help more generally to rethink the study of
the politics of numbers, acknowledging plurality, contingency and “the
differential structuring of freedom, performative and indirect agency”
(Raffnsøe et al., 2019, p. 155).

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Quantification as Utopia
# Creating a Socialist Society and Quantification in the USSR

Martine Mespoulet

When the Bolshevik government came to power in October 1917, it based the legitimacy of its action on the scientific nature of its decisions, figures being one of the core elements thereof. Its leaders asserted the ambition of building a state in which science would form the basis for political decisions, for the well-being of everyone and fundamentally for the fulfilment of the communist plan to create a new society and new human being. From this perspective, statistics—an information and decision support tool—was also an instrument of power designed to prove the soundness of state action. Statistics would help symbolically construct the Soviet social and economic world. That notwithstanding, can one discern specific forms of production of figures in such a state, that is to say, as Alain Desrosières has conceptualized, a particular relationship between concepts, methods, technical instruments, statistical institutions and representations of the social and economic world, that could be construed as characterizing the nature of such a state (Desrosières, 1985)?

<footnote>M. Mespoulet (✉)
University of Nantes, Nantes, France
e-mail: martine.mespoulet@univ-nantes.fr</footnote>
In particular, did certain tools take on a specific form in the USSR,
in a context of construction of a socialist society underpinned by central-
ized and planned management of the economy? If that is the case, how
were they adapted to new political representations of society, the economy
and the role of science in such a state? This newly developed form of
producing figures serving a new type of state and a new political plan
included the creation of a new central government statistics department
and an effort to formulate a new theory of statistics and design new
methods and new tools. Various attempts to that effect gave rise to
debates and tensions between leaders and statisticians, and between the
statisticians themselves. After trying to characterize some of them, we will
endeavour to underscore the specific nature of state statistics in the Soviet
Union.

INVENTING A NEW FORM OF STATISTICS
FOR A NEW MODEL OF SOCIETY

A New State Statistics Administration

The Bolshevik state’s new Central Statistics Administration, the TsSU
(Tsentral’noe Statisticheskoe Upravlenie), was set up on 25 July 1918.
One can consider that it was the product of two plans tending towards
change, but plans in which the role of statistics was defined differently.
For the Bolshevik leaders, the production of figures had to play a key
information role for developing the plan and for managing the economy
and society. But for the TsSU’s statisticians, most of whom were formerly
employed by the statistical offices of the zemstva, local self-governed
authorities of the Tsarist state provinces founded in 1864, the challenge
consisted above all in creating the statistical institutions and tools of a
modern state, in line with the recommendations of the international statis-
tics congresses of the nineteenth century (Mespoulet, 2001; Mespoulet &
Blum, 2003; on statistical internationalism in the late nineteenth century,
see Brian, 1989).

So notwithstanding the political message conveyed by the Bolshevik
government, the TsSU was organized on the model of the statistical agen-
cies of late 19th-century European states, structured around a series of
departments reflecting the main divisions of statistics of the time, and
moreover constructed on the institutional and methodological bases of
regional statistics as practised by the zemstva. The texts regulating its
foundation and missions adhered to the spirit of the debates and resolutions of the international statistics congresses of the nineteenth century, as asserted by its director, Pavel I. Popov, speaking at the national congress of Russian statisticians held between 8 and 16 June 1918 (Popov, 1918). Encouraged by the experience of the statisticians in the regional offices of the *zemstva*, the Bolshevik state statistics administration was also resolutely organized in line with statistical internationalism, its scientific positions and organizational principles (on this point, see Brian, 1989).

This continuity with the pre-revolutionary period, relying also on continuity of the staff, was simply the visible part of other forms of inheritance in the representation of statistical work, methods and observational tools, and in the maintenance of certain administrative practices behind the apparent institutional changes (see Mespoulet, 2001, chapters 5 and 7). This strong continuity of individuals and practices coexisting with a disruptive political message was at the root of a great deal of tension between statisticians and political leaders from the early 1920s (see Blum & Mespoulet, 2003).

For the Bolsheviks, planned management, centralization and accounting had to be the bedrock of the organization of production in the future socialist state, and the statistics administration had to serve this political plan. While in line with the new plan model formulated by Lenin and the Bolsheviks prior to 1917, it should be noted that this conception of a centralized and planned economy was strengthened by the experiences of the First World War (see Holquist, 2002) and the civil war between 1918 and 1921 (Sapir, 1997), which provided a breeding ground for formulating and experimenting with a state-controlled economy (Stanziani, 1998), in particular to resolve supply chain issues.

In such a context, it is hardly surprising that the statisticians in charge of setting up the TsSU subscribed to this goal, in particular those who had played a part in the management of public and economic affairs during the war, in the Tsarist Ministry of Agriculture, or within the framework of the All Russian Union of towns and of the *zemstva*, or in the Provisional Government. However, such an endorsement of the Bolshevik plan did not preclude tensions and clashes between leaders and statisticians about the very definition of the role, methods and tools of state statistics. What form of quantification should be adopted to construct a socialist
economic and social model tending towards communism? The first challenge consisted in how to define the connection between accounting and statistics.

## *A Complicated Demarcation Between Accounting and Statistics*

The expression “socialist accounting” was used by Lenin as early as 1917 to describe the form of quantification aimed at providing figures to construct a socialist economy and society. In his speech to the Petrograd Soviet, Lenin said: “Socialism is accounting. If you want to record each piece of iron and fabric in the books of account, then that is socialism” (Lenin, 1955, vol. 26). Before the Revolution, he had already stressed the key role of accounting in his book entitled *The State and Revolution*: “Accounting and control, these are the chief things necessary for the organizing and correct functioning of the first phase of Communist society” (Lenin, 1955, vol. 21).

Initially, and for reasons of efficiency, the production of figures was to be controlled by their immediate practical applicability, that is their usefulness in guiding actions and decisions. This conception tended to strengthen the comparison of statistics with accounting, regarding it as a set of tools rather than a science. This demarcation of the role of statistics clearly comes across in the letter Lenin sent to the TsSU's director on 16 August 1921: “For practical work, we need to have figures, and the TsSU should have them before anyone else. But we will defer the verification of the accuracy of the figures, the estimated percentage errors, etc., to a later period” (Lenin, quoted in Iastremskii & Khotimskii, 1936, pp. 14–15).

Lenin does not provide a precise distinction between accounting and statistics. Rather, he differentiates between statistics as a “bourgeois science” inherited from the nineteenth century, and a newly emerging field of (socialist) statistical practice, accounting, which he sees as a practice of factual recording and counting, which does not involve any analysis or interpretation of reality, contrary to what, in his view, (bourgeois) statisticians did when producing their data. For Lenin, it was accounting which was needed for the construction of a communist economy and society. In his eyes, this construction project was an urgent undertaking and the “academic” efforts of (bourgeois) statisticians a waste of valuable time, standing in the way of proceeding with it as quickly as possible.
Economic and political urgency justified paying less attention to the use of statistical theory to verify the accuracy of figures, which led statisticians to restrain their scientific ambitions. The scope of statistics had to relate above all to the need to plan economic activity, which demanded a state statistics administration totally dedicated to this task:

> The central administration of statistics must not be an “academic” and “independent” body, which it currently is, for 9/10<sup>ths</sup> following old bourgeois habits, but one for constructing socialism, for verifying and controlling the accounts of what the socialist state needs to know now, today. (Lenin, 1955, vol. 28)

These Lenin quotes are not provided merely for form's sake. For it was in the name of his own vision of the role of statistical surveys in the management of Soviet economy and society that he regularly intervened in the TsSU's affairs until his death in January 1924 (see Kotz & Seneta, 1990). Then, at the 13th Congress of the Party in May 1924, Stalin in turn linked statistics back to accounting, while remaining very vague about the nature of the connection between them:

> No construction work, no work for the state and no planning is imaginable without correct accounting. But accounting is inconceivable without statistics. Accounting without statistics will not make a single step forward.¹

The link between statistics and accounting was clearly reaffirmed in the early 1930s and symbolized by the TsSU being taken over by the State Planning Commission Gosplan in 1930. In the reference manual of statistics published that year under the direction of B. I. Iastremski and V. I. Khotimski (1931),² the authors reiterated the tasks Lenin had assigned to the TsSU in the introduction: statistics had to be associated with accounting, even in the study of social phenomena. In such a conception, the attention paid to the tools was essential. To better understand the decisions made for their development and use, we need to recall the definition of the scientific nature of statistics given in the 1930s, a key period in the formation of the Soviet system under Stalin.

In fact, just like scientists or professional specialists in other fields, the statisticians had to justify the status of statistics as a science in the early 1920s (on the status of science in the USSR, see Graham, 1993; Krementsov, 1997). They strove to develop an analytical framework for
social and economic phenomena adapted to the plan to construct a
socialist economy and society, setting themselves apart from the writings
of European statisticians, described as “bourgeois” by the Soviet political
leaders.

In this task of revision and reinterpretation, the Soviet statisticians were
faced with a profound contradiction. Though rooted in an intellectual
tradition inherited from the nineteenth century, which regarded statis-
tics as a science on a par with chemistry or mathematics, during various
conflicts they were forced to justify the socialist nature of their work and
its conformity with the political plan to construct a new state, and its
economy and its society. But for these statisticians, who associated figures
with objectivity and scientific truth, all science sought to establish was
a truth that could not be imposed by political leaders (on the notion
of objectivity, see Porter, 1995). The TsSU's statisticians were subjected
to various forms of political pressure that they nonetheless had to come
to terms with, at times under duress, and that drove them to work out
a theory in conformity with the Bolshevik political message about the
construction of a socialist economy and society. How much of their theo-
retical constructs were based on compromise? In the initial stages, they
embarked on a task of theoretical deconstruction.

A Task of Theoretical Deconstruction

In reality, it was rather a hollow definition of Soviet state statistics that was
produced, as opposed to the statistics qualified as “bourgeois” to describe
the theories developed in the nineteenth century. The manual published
by B. S. Iastremskii and V. I. Khotimskii in the early 1930s begins with a
denunciation of the latter:

Like any science, statistics is a science of class. The whole system of
statistics in capitalist countries is constructed to serve the interests of the
ruling classes. Bourgeois statistics does not just serve to significantly reduce
income tax of different capitalist groups, it also hides the actual amounts
of military spending. Furthermore, bourgeois statistics gives a false picture
of the situation of the capitalist economy by embellishing it and attesting
to the absence of antagonisms. (Iastremskii & Khotimskii, 1931, p. 6)

The production of statistics in capitalist countries is presented as an
undertaking of falsification serving a non-egalitarian state. Accordingly,
its fundamentals cannot be used in a state that plans to achieve equality between all human beings. On that basis, the authors of the manual are led to refute certain theoretical contributions of the pre-revolutionary period by associating them with the fundamentals of statistics as used by the bourgeoisie of capitalist countries:

> Bourgeois statistics as practised is based on the bourgeois theory of statistics, which is organically connected to the whole system of bourgeois political economy and philosophy. The authors and theorists of the bourgeois science of statistics (Süssmilch, Quetelet, Lexis, Bortkiewicz, Pearson, Mittchell, Bowley, Moore, Chuprov, the fascists Pareto and Gini, and others) give arguments, with the aid of statistical constructs, extolling the "unshakeable" and "eternal" nature of the capitalist system. (Iastremskii & Khotimskii, 1931, p. 6)

The authors discredit the statistical reasoning developed in the nineteenth century (on statistics in the nineteenth century, see Porter, 1986), accusing it of encouraging the status quo and of curbing economic and social progress by basing natural and unchanging laws on the “regular stability of statistical figures”:

> In the first half of the 18th century, pastor Süssmilch spoke of “the divine order” that manifested itself in the regular stability of statistical figures. In the 19th century, Quetelet, who admittedly said so without referring to God, spoke of a natural order that found expression through statistical figures, of an “average man” having a specific number of crimes, good deeds, etc. (Iastremskii & Khotimskii, 1931, p. 6)

This accusation (nineteenth-century statistics being a curb on progress) led to the plan to construct a system of “socialist accounting” serving a political programme of figures being used by the people:

> Lenin on many occasions said that accounting would become the business of the masses only after the overthrow of capitalism. But such accounting is impossible without statistics, which is also essential for the good of the masses. "In capitalist society, statistics was the exclusive reserve of 'people of the state' or narrow-minded specialists; we have to bring it to the masses, popularize it so that workers can gradually learn to understand themselves and see how and how much they have to work, how and how much they can rest..." (Lenin, 1955, vol. 21). The essential nature of disseminating
socialist accounting among the people requires maximum simplification of its technique. (Iastremskii & Khotimskii, 1931, p. 13)

The production of figures in a socialist state thus becomes a tool for the people, one that the people must appropriate, which requires the contents of statistics to be reduced primarily to technical mechanisms, assumed to be accessible to the greatest number. However, the link between accounting and statistics is not broken, even though it is not clarified. Such a conception gave rise to numerous discussions between political leaders and statisticians and among the statisticians themselves.

## DEBATES AND TENSIONS SURROUNDING STATISTICAL THEORY

Scientific debates were mingled with internal political rivalries (see Maksimova, 1996). These discussions were all the more heated when statisticians trained in Marxism in the new Soviet higher education institutions, such as the Plekhanov Institute for the National Economy³ or the Institute of Red Professors,⁴ started being recruited by the TsSU. The rifts between statisticians keen to maintain theoretical mathematical statistics and those who preferred more descriptive statistics based on surveys were reinterpreted during their controversies. The interpretation of the mean and of the law of large numbers, as well as the use of probabilities in statistics, were in particular the subject of heated debate.

### *Tension Surrounding the Mean and the Law of Large Numbers*

As already mentioned earlier, the interpretation of the mean by Quetelet was accused of leading to moral fatalism, which negated the freedom of individual will, and facilitated a form of social fatalism whereby society depended on superior laws that one could not combat (on Quetelet and the mean, see Desrosières, 1988; Porter, 1986, ch. 2 and 4; Thévenot, 1994). The fact is that these conceptions were in contradiction with the Bolsheviks' Promethean transformation plan.

The law of large numbers, which was one of the essential factors legitimizing statistics as a science serving the measurement of social facts, was condemned for the same reasons from the early 1920s. The Marxist theorists emphasized the fact that observed trends were not inevitable,
and that such a concept led to putting the state’s action into perspec-
tive. In their view, this statistical law contradicted the principle of political
action, as it portrayed social processes as fatalistic and the effects of polit-
ical action on society as illusory. Moreover, it helped to justify the idea of
stability of capitalism and thus its unchanging dimension.

On the other hand, for the TsSU statisticians, statistics could not exist
without the law of large numbers. Consequently, they strove to present
a use of the said law that did not challenge its theoretical foundation
while at the same time taking into account the attacks on it. In 1936,
Vladimir N. Starovskii, head of the Central Statistics Administration,⁵
proposed a wording full of stylistic acrobatics in a work published that
year (Starovskii, 1936). True to Marxist thinking, he did not question
the existence of laws that transcend individuals when having to deal with
large populations, but he challenged the ineluctable nature of phenomena
that appeared to him to be suggested behind the statistical regularities and
the lack of references to history. He presented as essential the reference
to the historicity of these laws, which he presented as specific to a given
social and political system. That being the case, the state could transform
the said laws and replace them with others. Human and political action
was no longer at risk of being powerless. But a socialist use of the law of
large numbers and the mean still had to be defined.

In fact, as they failed to establish the theoretical foundations of a
form of statistics that could be described as socialist, the statisticians in
charge of this task of reinterpretation endeavoured first of all to clarify
what statistics should not be. Their reasoning consisted in calling into
question the purportedly erroneous interpretations inherited from the
pre-revolutionary past rather than in elaborating a new set of concepts
adapted to a socialist economy and society. On the substance, it was
therefore more a political debate on the use of the tools than disagree-
ments on their theoretical foundations. Beyond the views and reasoning
of convenience, the statisticians were forced to think about the interpre-
tation of the tools they used and the creation or use of other tools better
suited to the context of the moment. The tension around the concept of
randomness and the use of probabilities is one such example.

*Tensions Around the Shift to the Random Model*

In 1917, Russia had already acquired extensive experience in the field
of sample surveys. The first tests of surveys on a "part of the whole"
probably took place in the 1870s. The period from 1885 to 1917 was marked by numerous efforts to perfect sampling methods, and by serious thinking by the Russian statisticians in this respect (Mespoulet, 2002). From 1895, they had the same discussions between themselves as their colleagues in other European countries about the shift from an exhaustive count to a partial survey, then about the shift from a sample constructed in a reasoned manner, based on the use of type, to a random sample based on calculated probabilities (on the history of sampling methods and sampling surveys, see Desrosières, 2002; Gigerenzer et al., 1989; Stigler, 1986). At the European level, the two questions of representativeness and confidence raised by a survey of “a part of the whole” were at the heart of a debate that started with Kiær’s first communication at the Congress of the International Institute of Statistics (IIS) in 1895 and ended in 1925 at the IIS Congress in Rome, where both sampling methods—reasoned selection, also called purposive selection, and random selection—were accepted after heated discussions about their respective merits (on the debates during the period 1895–1925, see Desrosières, 1998 [1993], ch. 7; Kruskal & Mosteller, 1980).

The exuberant production of statistics in the USSR in the early 1920s created particularly favourable conditions for the rapid spread of sample surveys in the country (Mespoulet, 2002). Intensive use of such surveys from 1919 onwards stimulated thinking about sampling methods. After 1925, such thinking indeed developed much more as a logical extension to the questions raised by the already long-standing practice of Russian statisticians in this field than in relation to the questions discussed at the Congress of Rome, even though a summary on this subject was drawn up by the TsSU.

However, the shift to the random model took particular forms from the 1930s, in a country where the political leaders propounded a representation of society in which the collective prevailed over the individual, and in which an average collective behaviour was preferred to individual—and therefore diverse and dispersed—forms of expression. Moreover, the Bolsheviks’ purposeful plan to construct a new state and their Promethean representation of human action on the environment gave a new dimension to the debates about the adoption of random sampling: what place could chance have in a planned world, in which there was precisely no place for uncertainty, and in which the unpredictable nature of individual behaviour and the variability of individual cases could not be factored in?
Planning concerns influenced the thinking about statistical representation and uncertainty, and consequently the forms of recourse to the calculation of probabilities. The treatment of statistical dispersion and of the mean, on the one hand, and the construction of sampling methods for sample surveys, on the other hand, depended on the status of the individual in society. The way of considering the question of confidence in the method for constructing samples influenced the forms of the shift to random sampling in the USSR.

Random selection, the product of the law of randomness, could only be considered within the bounds of a prior breakdown of reality controlled by human reason, in accordance with the Marxist concept of the primacy of human action over the economy and society. Chance could only operate if confined within a framework demarcated by human reasoning and compliant with political choices and directives. From that stemmed the basic Soviet statistical sampling method, developed in the 1930s, subsequently modified in the early 1950s. Whether under the name "random stratified sample" (raionirovannyi sluchainyi otbor) or "typical stratification" (tipicheskoe raionirovanie), the method for creating a sample based on a combination between the demarcation of "typical groups", firstly, and random selection, secondly, addressed the need to perform a prior breakdown of social reality into classified categories deemed relevant for analysing class structure or different types of agricultural or industrial production structures. This way of combining use of type and a specific interpretation of randomness characterized Soviet statistics from the 1930s to the early 1990s.

Mechanical selection was preferred to probabilistic random selection in the strict sense. The former was considered to provide more accurate results than random sampling, in the strictly random sense of the term, inasmuch as it guaranteed regular distribution of the sample's units over the entire set. In actual fact what was called mechanical selection was a systematic selection (1/5 or 1/10 for example) without replacement. This preference for mechanical selection was also a constant of Soviet statistics until 1991.

This form of constructing samples combines the two symbolic characteristics of the preference for typical stratified sampling: attachment to territory as the basis for division into typical groups, which dates back to the association between territory and type of the nineteenth century, and the principle of an a priori breakdown of observed reality into classifications. Random selection could only occur subsequently. From the 1930s,
the classifications developed served to form “typical groups” based on an economic breakdown of reality into branches of production. In the process, they resulted in excluding a part of the population of the samples used in budget surveys for instance, casting out to an unknown world all those who were not counted in the productive sphere, pensioners among others. They thus departed from the principle of representativeness in relation to the population as a whole. This way of focusing statistics on groups or entities that mattered economically, socially and politically in the eyes of the leaders can be explained by the priority given to targets. This appears no less in contradiction with the desire to know everything, which is often ascribed to the Soviet leaders. In this case, the search for information appears to have been selective, satisfying political choices rather than statistical laws.

At the end of the 1960s, A. Boiarskii clearly addressed the problems raised by this sampling method:

> A sample formed on the basis of production is obviously a sample of individuals who work, and in that case the rest of the population is only included in the field of view inasmuch as it has a connection with those who work. However much we then adjust and correct the results, this sample will never replace a sample of another kind of population. With this sampling process, observation is still based on the habitual recourse to administrations and companies. But from data concerning all companies one cannot obtain an appropriate reflection of the life of all the population, all socialist society in its entirety. (Boiarskii, 1968, p. 16)

> This tension between a realistic conception of statistics, which produces figures “reflecting” reality and was defended by the statisticians, and a representation of the figures, treated as one of the instruments for constructing a socialist reality and preferred by the political leaders, is regarded as one of the main components of Soviet statistics. In such a situation, the statisticians had to make efforts to adapt to the requirements of the moment; this took various forms according to the period and the circumstances. A. Boiarskii’s remark implies moreover that the adjustments and corrections of results may in certain cases have resulted from this effort aimed at better matching the data with reality, despite the choices of methods or techniques that resulted in ignoring or masking certain aspects or dimensions thereof.
## WHAT FORM OF STATISTICS FOR CONSTRUCTING A NEW ORDER?

The Soviet state was founded on a system of representations of management of the country predominated by the image of a stable universe, in which a planned economy was based on an organizational method designed to lead to an increase in general living standards and to an egalitarian society. Figures occupied a central position, being a tool for information and action, a tool for evaluating results and an instrument for proving the rightfulness of the measures taken. Central to such a system of administration of the economy and society, quantification was a basis for legitimizing the state and power. Accounting seemed to be the new language that the Soviet Union needed to construct a system of quantification serving the construction of socialism in the economy and society. But that also needed new categories of classification to be constructed to characterize the composition of society and to redefine the criteria on which confidence in the data produced by state statistics was based.

### *The Relationship Between Statistics and Accounting*

In 1932 Valerian V. Osinskii, then head of the Central Directorate of Accounting for the National Economy (TsUNKhU),⁶ defined the role of statistics in relation to accounting:

> During the transition towards socialism, accounting must encompass all spheres of economic and social life, and must penetrate all its links, even the smallest.

> [...] As the remains of capitalism were being swept from the economy and the consciousness of people, statistics was increasingly superseded by national accounting itself. The former TsSU did not become the TsUNKhU by accident. This change in name did not happen by accident, it characterizes the transformed orientation of activity of the system as a whole. (Osinskii, 1932)

V. V. Osinskii regarded statistics as a relic of capitalism. Henceforth serving the plan, statistics had to be transformed into accounting to draw up the national accounts. This unified form of accounting, from initial recognition to centralized processing, had to ensure uniform auditing and processing both of demographic and social phenomena and of economic activity, and guarantee continuity between companies' accounts and the
national accounts. This idea of a unified accounting system was not exclu-
sive to the USSR. It is found with variants, after the Second World War,
in European countries that set up their own system of national accounting
(see Studenski, 1958; Vanoli, 2002). In the USSR, it was intensified by
bureaucratic management at different levels, from the basic department of
a company to the central planning bureau of the Gosplan (Kornai, 1996,
pp. 141–164).

Was accounting destined to replace statistics? The answer to this ques-
tion remained ambivalent until the end of the 1930s, reflecting the
difficulty in inventing a new quantification language centred primarily on
accounting devices without resorting to statistical theory as a resource.
So Stalin's formulation, at the 16th Party Congress in 1930, of the idea
that "there can be no accounting without statistics" then gave rise to
much prevarication and many changes in attitude in the definition of the
connection between statistics and planning through accounting.

One such example is provided by the fate of the theory of the decline
of statistics formulated by Osinskii in 1932 and subsequently denounced
at his trial in 1937. The idea that statistics had to be transformed into
accounting to serve the preparation of the national accounts was put to
the test. This prompts one to put into perspective the formulations made
during the 1930s about the conception of the scientific role of statistics,
as the use of ideas for political ends was standard practice at the time.
However, even if the role of statistics was once again officially recognized
at the end of the 1930s, it was not at all well-defined. In reality, it was
only in 1948 that statistics was fully restored as a field in its own right,
when the TsSU regained institutional independence from the Gosplan, the
figures of which it was tasked to audit. Its rehabilitation was completed
in 1960 when Starovskii, then director of the TsSU, gave himself up to
a form of self-criticism on the occasion of the publication of his work on
the history of statistics in the USSR:

In economic literature, all sorts of leftist ‘theories’ were formulated, for
instance the ‘theory’ of the decline of money under socialism or the ‘the-
ory’ of the decline of statistics under socialism (the transformation of
statistics into accounting, which appeared for the first time in the articles of
academic V.V. Osinskii) [...]. The author of this article, in his works, in the
period 1932-1935, also asserted this ‘theory’. Life has clearly demonstrated
the pointless and erroneous nature of these ‘theories’, which distracted
the attention of scientific managers from current questions surrounding
statistical theory. (Starovskii, 1960, p. 16)
Nevertheless, the asserted integration of statistics into accounting had far-reaching consequences on the forms of the use of statistics and the tools used. Firstly, the period 1930–1955 was marked by the virtual disappearance of social statistics. The scientific and universalist ambition of nineteenth century statisticians, defended by the early heads of the TsSU, was supplanted by an immediate use of figures for accounting purposes to provide the *Gosplan* with the data needed to work out and evaluate five-year plans. The social figures produced between 1930 and 1955 were mainly demographic in nature. Statisticians became a kind of “right hand” providing the economistic planners with statistics needed for elaborating the plan, for instance for building blocks of flats, schools or leisure facilities.

On the other hand, a whole new area of statistics developed, based on economic forecasting and the construction of indexes. The statisticians elaborated new approaches directed at constructing a national accounting system, the reflections of which are already evident in the manuals published in the 1930s (see in particular Iastremskii & Khotimskii, 1936). The chapters dealing with “relative magnitudes” and indexes occupied a more important place in them, helping steer practices towards a purely accounting use of statistical techniques.

When the Methodological Council of the Central Directorate of Accounting examined the training programme on corporate accounting techniques and statistical theory in 1934, it stressed the need to limit statistical theory to what it described as the purpose of statistics: categorization, the calculations of averages, indexes and the sampling method.⁷ The construction of indexes, for instance, was based on ratios aimed to compare two quantities, for example industrial production to agricultural production. The indexes were built for planning purposes and for the evaluation of the plan objectives. However, not by any means unbiased, categorization brought into play considerations that were much more than merely technical, namely social and political issues, in particular when it was a matter of constructing other tools, such as classifications of population censuses.

## Categorization of the Population and Censuses

The work of constructing occupational classifications used for censuses combined the desire of the statisticians to reflect reality as closely as possible and the classification models officially accepted by the Party.
The tension between a “realistic” conception of statistics, which produces figures ‘reflecting’ reality defended by the statisticians, and an understanding that treated statistics as one of the instruments for constructing a socialist reality, which was preferred by the political leaders, can be regarded as a key feature of Soviet statistics.

Each census involved a confrontation between the desired construction of a socialist reality and forms of resistance to transformation of society or the economy, and it was important for the results to provide a snapshot of the volume and structure of the population. The census, which had to confirm the successful construction of a socialist society, was the central link in the statistical tools for constructing reality. From the mid-1920s, its production was subjected to increasingly frequent attempts at intrusion by the Party at various different data collection, processing and publication stages.

While as in any country the elaboration of classification categories for the individuals and phenomena under study was the subject of negotiation between various administrations or institutions, it raised particular issues in the USSR, where the administration of society was based on a classification of the population into categories defined by the Party. The TsSU's statisticians had to find the adaptations needed to match the bill of materials with, among other things, the structure of the social classes adopted by the Party or the official list of nationalities (on the classification of nationalities in the censuses, see Cadiot, 2007; Hirsch, 1997). This work of adjustment, which varied according to period, the political views and priorities of the moment, was a source of tensions between statisticians and political leaders and calls to order from the latter to the former. The example of the definition of occupational categories in the 1920s and 1930s clarifies certain forms of adjustment. In the 1926 census, the category “occupation” replaced “profession”, which had been used by choice in the 1920 census, but which created difficulties for constituting the main social groups defined in the theoretical Marxist social analysis model (Mespoulet, 2008). Subsequently, behind a simplified classification into major social groups, called “classes” at certain periods, there remained a very detailed classification of “occupations” that reflected social diversity.

The purges of statisticians following the 1937 census halted the TsSU statisticians' efforts to reflect such diversity through censuses (on the Great Purges in the Soviet state statistical administration, see Blum & Mespoulet, 2003). From the 1939 census onwards, a stable image of
social structure dominated through a classification of social groups that remained broadly unchanged until 1989. This virtual stability of the classification, which can be an advantage for comparisons over time, nonetheless resulted in obscuring some of the diversity of the social situations of individuals from the 1960s onwards. Generally speaking, the model of stable social aggregates, based on major groups, overlooked changes affecting small groups of individuals, regarding them as residual or marginal phenomena. In the process, it left blind spots with regard to the actual state of Soviet society and failed to spotlight its underlying transformations that broke out after the perestroika.

What room was left for the social in this model where the collective prevailed over the individual? In reality, social phenomena were studied mainly when they could be reduced to economic management. Furthermore, reflecting on how social matters were taken into consideration raises another question, namely the confidence one has in the data on society collected by the statisticians and in what the respondents say.

*Confidence in the Data and the Status of the Statistician*

As already mentioned, the question of how much confidence we can have in statistics explains the reservations one can have about using a random selection in the sample surveys method practiced in the USSR. This question is also expressed in a number of ways in connection with the collected data and the processing of individuals' responses to the surveys. How much confidence can one have in what respondents say, and thus in the data based on their responses? Beyond that, this point also raised the question of confidence in the work carried out by the statistician.

From the end of the nineteenth century, surveys were considered a social situation in their own right, in which the effects of interaction between interviewer and respondent played their part (Mespoulet, 2008). However, whereas this thinking had helped to consolidate the role of the professional statistician in conducting field surveys up to the early 1920, in particular in questioning individuals, it went in quite another direction from the early 1930s. The effects induced by the leeway respondents had in responding made them suspect in the eyes of the authorities, and the Party started intervening in the organization of data collection operations, more particularly by controlling recruitment and the work of local census takers.
In areas other than state statistics, in the early 1960s, the local Soviets and trade unions appointed “civic controllers and engineers” to audit certain stages of statistics work at a local level (see Anisimov, 1968; Sbeglov, 1967). In the late 1970s, an article in *Vestnik statistiki*, the TsSU’s journal, pointed out: “The state’s statistics bodies, with the active help of the Party, Soviet organizations and trade unions, do their work by recruiting civic activists on a large scale to audit the accounts, administrative registers and the authenticity of the data in the registers” (Vestnik statistiki, 1978, p. 67). This auditing of statistics by the citizens, in reality by social activists, presupposes a careful choice of those hired to do the work, who were also known as “civic inspectors of state statistics”: “They were selected and confirmed nationwide by branch, according to worker qualification, and also according to the possibility of combining an inspector’s *obshchestvennaiia rabota* with his main job” (Vestnik statistiki, 1978, p. 67). Who were these inspectors, also called *obshchestvenniki*, civic activists?

In principle, the most experienced specialists in the various branches of the national economy were recommended as civic inspectors of state statistics, and the nature of each district is also taken into account. These inspectors are accountants, economists, engineers in factories, administrations, organizations and kolkhozes (collective farms), workers in the plan and financial bodies. Applications are put forward with the agreement of the managers of the companies and organizations where the applicants work. They are examined with the leaders of the Party and the trade unions in the workplace, and only after that are they confirmed by the local executive committee of the district or town, the soviets of the people’s deputies. (Vestnik statistiki, 1978, p. 67)

What precise tasks were expected of these inspectors? First and foremost, their function entitled them to demand that the managers of factories, work sites, government departments, organizations and kolkhozes disclose their accounting records and work registers for inspection purposes. This consisted in auditing accounts and figures in factories and other workplaces, by examining the original documents. On that basis and with the aid of the managers of these establishments, the inspectors could take measures in situ aimed at eliminating the defects brought to light, and also ask for the collectives of workers subject to this inspection process to be convened in order to discuss the results thereof.
In 1978, there were nearly 30,000 inspectors covering most of the districts of the Soviet republics, half of whom were in the Federal Republic of Russia (Vestnik statistiki, 1978, p. 68). Most of them had a secondary school or higher level of educational attainment, and many of them were members of the Party or candidates for Party membership.

Whether it be a control of the data provided by factories or administration registers, by censuses or budget surveys, this inclusion of data collection operations in the sphere of civic activities demonstrates a special way of treating interaction between interviewers and respondents in an authoritarian state such as the USSR. The question of the degree of confidence one can have in the information provided by the respondents, a subject of discussion for Russian statisticians from the 1880s onwards, remained an important factor in Soviet statistics, but the way it was resolved took on a different form. Before 1917, Russian statisticians shared the idea that it was up to the interviewer himself to behave in such a way as to gain the trust of the respondents and thereby elicit more accurate and comprehensive responses from them. After 1917, the Party had a quite different view of the way of handling trust in relations with respondents.

In the censuses of 1919 and 1920, against a backdrop of grain requisition campaigns, the Bolsheviks suspected the peasants of holding back information, especially about their harvests and stocks of grain production. So they were considered guilty in principle. This suspicion of the leaders vis-à-vis the peasants was a constant in the 1920s and 1930s. So, an assessment of the confidence one would have in the information provided by the respondents was not left solely to the statisticians, suspected in principle of possibly colluding with the respondents. The degree of confidence one could have in the collected information therefore had to be handled differently, both by the Party and its social organizations. The control of the statistics would be done by new forms of social and political control. The census preparation and collection operations in the various districts were controlled by Party bodies and social organizations until 1989.

The intrusion of the Party and the social organizations in the conduct of field survey operations, both for censuses and for surveys of family budgets, socialized this moment of statistical work while at the same time divesting part of the statistician's professional competence.

In that light, Lenin's statements regarding the need to "popularize" statistics, in the sense of making it accessible to the people, take on a
particular relevance. The ambition of the Soviet regime was to create a
"new human being". At the centre of this project, all aspects of social
life were deemed susceptible to control by the mass organizations repre-
senting the people. Who better than the collectors of the people's data
to control the statements of citizens subject to survey? The verification
of the reliability of the gathered information compared with reality took
the form of social control. Such inclusion of certain statistical opera-
tions in the sphere of civic activity restricted the statistician even more
to a primarily technical role, cutting him off from the very source of the
information he had to process.

*What Statistical Tools for a New Order?*

Up to the 1950s, the management tool aspect of statistics was regarded as
the main one in the apparatus of state statistics and was closely linked to
planning. However, surveys of family budgets, which were precisely at the
point where statistics and planning intersected, offer a good example of a
technical mechanism that in certain cases could also be used as a tool for
acquiring knowledge about society, which Boiarskii, then Director of the
TsSU Research Institute, himself acknowledged in 1968 when, following
new directives from the 1967 Party Congress aimed at developing the
social sciences, the TsSU had to "intensify the statistical study of social
phenomena" (Boiarskii, 1968). For Boiarskii, surveys of family budgets
were the preferred tool for assessing what he included in the subjects of
study of social statistics: problems at work, wages, consumption, services,
housing, everyday life. Apart from that, health, the composition and
movements of the population and the family structure were in his view
in the realm of demography, which also encompassed social statistics. In
fact, the demarcation of the latter was dictated by an imperative: all these
questions had to be studied as "a reflection of the economy's effects on
all other phenomena of social life" (Boiarskii, 1968, p. 14).

In reality, from the 1950s, and even more so from the 1960s, many of
the tools and mechanisms used in Soviet social statistics resembled those
used in capitalist countries (Elisseeva, 2003). The difference was not so
much in the type of tools used but rather in the way they were used,
which Boiarskii himself pointed out, for instance in connection with the
methods of sample surveys conducted by Soviet sociologists in the late
1960s:
We cannot compare our surveys with those of bourgeois sociologists without due consideration, on the basis of specific criteria. The main difference lies in the fact that their programme (both of observation and of processing) is constructed in such a way that by expressing itself in a manner full of imagery one can't see the wood for the trees. Their specific nature does not stem from the fact that one proceeds by conducting sample surveys or by conducting a survey, but rather from the fact that the whole construction of these surveys is not designed to bring to light what matters most: the role of relations of production that, all things considered, in reality determine all these processes. (Boiarskii, 1968, p. 17)

Much more so than the tools as such, and the statistical theory underpinning them, the difference resided in the approach and the model for interpreting the reality in the framework of which they were used:

> Our sample surveys are constructed on quite different bases and principles – the principle of the historical materialism of sociology, in our Soviet, Marxist conception of the word. It is precisely in that, and not in the technical question, that resides the dividing line between the surveys of sociologists in socialist countries and those of bourgeois sociologists. The very forms of the work may be similar. (Boiarskii, 1968, p. 17)

National accounts, demographic censuses, budget surveys, all these tools were used for a similar purpose in different European countries after the Second World War, whether to measure production levels or living standards or to analyse trade circuits for the purpose of macroeconomic regulation and increasing material well-being in a country. In the case of the USSR, victory against the United States to claim the title of superpower also depended on success in the economic competition. The Soviet socialist system thus had to demonstrate its superiority in the same economic and social fields as the capitalist countries, which meant that they tended to adopt the same tools, while re-interpreting their uses.

## CONCLUSION

Quantification can be analysed as a way of legitimizing a fragile and young power, if one considers the USSR of the 1920s and 1930s, but it can be said that this was still true in the 1950s and 1960s, in the period of confrontation with the capitalist states. Adam Tooze has shown how statistics have been used to boost the legitimacy of the German state