Data Practices: Making Up A European People

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What is 'Europe' and who are 'Europeans'? Data Practices approaches this contemporary political and theoretical question by treating it as a practical problem of counting. Only through the myriad data practices that make up methods such as censuses can EU member states know their national populations, and this in turn is utilized by the EU to understand the population of Europe. But this volume approaches data practices not simply as reflecting populations but as performative in two senses: they simultaneously enact—that is, “make up"—a European population and, by so doing—intentionally or otherwise—also contribute to making up a European people. The book develops a conception of data practices to analyze and interpret findings from collaborative ethnographic multisite fieldwork conducted by an interdisciplinary team of social science researchers as part of a five-year project, Peopling Europe: How Data Make a People. The book focuses on data practices that involve establishing and assigning people to categories and how this matters in enacting Europe as a population and people. Five core chapters explore key categories of people—usual residents, refugees, homeless people, migrants, and ethnic minorities—and how they come into being through specific data practices such as defining, estimating, recalibrating and inferring. Two additional chapters address two key subject positions that data practices produce and require: the data subject and the statistician subject.

Author(s): Evelyn Ruppert, Stephan Scheel
Edition: 1
Publisher: Goldsmiths Press | Versa Press
Year: 2021

Language: English
Commentary: TruePDF
Pages: 368
Tags: European Union countries: Population; Population; European Union Countries

Cover
Half-title
Title page
Copyright page
Table of contents
Acknowledgments
Biographies
1 Introduction: The Politics of Making Up a European People
2 Data Practices
3 Usual Residents: Defining and Deriving
4 Refugees and Homeless People: Coordinating and Narrating
5 Migrants: Omitting and Recalibrating
6 Foreigners: Inferring and Assigning
7 Data Subjects: Calibrating and Sieving
8 Statistician Subjects: Differentiating and Defending
9 Conclusion: The Politics of Data Practices
Notes
Glossary
Index