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Beyond lawfare: An analysis of law's temporality through Russian‐doll urbanization from Turkey.

  • Published In: PoLAR: Political & Legal Anthropology Review, 2023, v. 46, n. 2. P. 241 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Civelek, Cansu 3 of 3

Abstract

This article opens a discussion about how temporalities in spatial and legal spheres are interlinked and shape both policymaking and governance mechanisms and resistance practices. Taking a case study from Eskişehir, Turkey, the research examines several urban renewal attempts of a municipality on the same urban lands over two decades that used different laws and policy tools in each case while all of which were annulled by court suits. From a perspective of legal anthropology, the analysis shows the limits of lawfare discussions that remain incapable of explaining cases that cannot be categorized with domination and resistance. Instead of focusing on detecting who wins or loses, the article claims that such complex cases could be understood better by scrutinizing temporal dynamics: how do legal, spatial, and social temporalities intertwine and impact policymaking? More specifically, how does the law's temporality (re)shape urbanization? Even further, what political work do temporalities generate? The article offers Russian‐doll urbanization as an analogy and ethnographic metaphor to examine several layers and endlessness of renewal initiatives within the broader process of urbanization. Studying the revelation of each layer unravels entangled temporalities of law and socio‐spatial dynamics and their consequences in policymaking and resistance. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:PoLAR: Political & Legal Anthropology Review. 2023/11, Vol. 46, Issue 2, p241
  • Document Type:Article
  • Subject Area:Sociology
  • Publication Date:2023
  • ISSN:1081-6976
  • DOI:10.1111/plar.12543
  • Accession Number:174030439
  • Copyright Statement:Copyright of PoLAR: Political & Legal Anthropology Review is the property of Wiley-Blackwell 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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