JOURNAL ARTICLE
Nuclearized River Basins: Conflict and Cooperation along the Rhine, Danube, and Elbe.
Published In: Historical Social Research, 2024, v. 49, n. 1. P. 92 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Gutting, Alicia; Högselius, Per 3 of 3
Abstract
This article analyses the historical geography of nuclear energy through the spatial lens of river basins. Approximately half of the world's nuclear power plants were built along one or the other river. There, they gave rise to both conflict and cooperation. Drawing on the theoretical notion of water interaction, which takes into account relations of both conflictual and cooperative nature, we distinguish between such relations in three dimensions: space, environment, and infrastructure. The spatial dimension gravitates around social and political processes where proximity and distance are at the heart, often linked to the search for suitable sites for nuclear construction. The environmental dimension refers to conflict and cooperation around the radioactive and thermal pollution of waterways. The infrastructural dimension, finally, highlights how nuclear power plant builders, when they arrived from the 1950s onwards, had to relate to pre-existing infrastructural features of the rivers, which sometimes led to clashes with other actors and sometimes to more cooperative forms of interaction. In empirical terms, we focus on three European river basins that came to play particularly important roles in European nuclear history: those of the Rhine, Danube, and Elbe. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Historical Social Research. 2024/01, Vol. 49, Issue 1, p92
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2024
- ISSN:0172-6404
- DOI:10.12759/hsr.49.2024.05
- Accession Number:175941490
- Copyright Statement:Copyright of Historical Social Research is the property of GESIS - Leibniz-Institute for the Social Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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