Population Geometries of Europe: The Topologies of Data Cubes and Grids

Tools

Grommé, Francisca and Ruppert, Evelyn. 2020. Population Geometries of Europe: The Topologies of Data Cubes and Grids. Science, Technology, & Human Values, 45(2), pp. 235-261. ISSN 0162-2439 [Article]

Preview

Text
Gromme and Ruppert STHV forthcoming AAM.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.
Download (542kB) | Preview

Preview

Text
0162243919835302.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.
Download (433kB) | Preview

Official URL: https://doi.org/10.1177/0162243919835302

Abstract or Description

The political integration of the European Union (EU) is fragile for many reasons not least the reassertion of nationalism. That said, if we examine specific practices and infrastructures a more complicated story emerges. We juxtapose the political fragility of the EU with the formation of data infrastructures in official statistics that take part in post-national enactments of Europe’s populations and territories. We develop this argument through an analysis of transformations in how European populations are enacted through new technological infrastructures that seek to integrate national census data in ‘cubes’ of cross-tabulated social topics and spatial ‘grids’ of maps. In doing so these infrastructures give meaning to what ‘is’ Europe in ways that are both old and new. Through standardisation and harmonisation of social and geographical spaces, ‘old’ geometries of organising and mapping populations are deployed along with ‘new’ topological arrangements that mix and fold categories of population. Furthermore, we consider how grids and cubes are generative of methodological topologies by closing the distances or differences between methods and making their data equivalent. By paying attention to these practices and infrastructures we examine how they enable reconfiguring what is known and imagined as ‘Europe’ and how it is governed.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1177/0162243919835302