JOURNAL ARTICLE

Two Concepts of Federalism in Myanmar: How the 2021 Military Coup Reshaped Political Discourse and Opposition Institutions.

  • Published In: Publius: The Journal of Federalism, 2023, v. 53, n. 2. P. 278 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Myat, Aung Kaung; David, Roman; Holliday, Ian 3 of 3

Abstract

This article examines the impact of Myanmar's 2021 military coup on the country's political dynamics, focusing on a shift from a majoritarian model dominated by the Bamar ethnic majority toward a more inclusive consensus model of federal democracy. It contrasts the pre-coup National League for Democracy (NLD) government's "democratic federalism," which emphasized majority rule and centralized control, with post-coup opposition institutions such as the National Unity Government (NUG) and National Unity Consultative Council (NUCC), which embody "federal democracy" characterized by broader ethnic inclusion and power-sharing. Analysis of opposition institutional composition and Burmese-language Facebook discourse reveals increased ethnic diversity and popular support for federal democracy after the coup, suggesting a bottom-up transformation in political culture toward consensus politics. The coup thus represents a critical juncture that disrupted longstanding Bamar dominance and opened possibilities for more dispersed, federal political arrangements in Myanmar's future.

Additional Information

  • Source:Publius: The Journal of Federalism. 2023/04, Vol. 53, Issue 2, p278
  • Document Type:Article
  • Subject Area:Politics and Government
  • Publication Date:2023
  • ISSN:0048-5950
  • DOI:10.1093/publius/pjac041
  • Accession Number:163024105
  • Copyright Statement:Copyright of Publius: The Journal of Federalism is the property of Oxford University Press / USA 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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