JOURNAL ARTICLE
Communist Parties and Threat to Democracy in Nepal: A Historical Analysis, 1949–2023.
Published In: Journal of Asian & African Studies (Sage Publications, Ltd.), 2025, v. 60, n. 7. P. 4733 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Chamlagai, Abi 3 of 3
Abstract
This study examines the role of communist parties in Nepal's political landscape and assesses whether they pose a threat to democracy, given their ideological roots in establishing a dictatorship of the proletariat. Using historical analysis, the research finds that communist parties have contributed more to the establishment and sustenance of democracy in Nepal than to its erosion, having ideologically accepted democracy and actively opposing authoritarian tendencies within their ranks. Despite episodes of democratic breakdown linked to communist factions—such as support for the 1960 royal coup, the 1980 referendum boycott, and the Maoist insurgency—the dominant communist parties have since embraced multiparty democracy and participated in democratic processes, including the 2006 People's Movement that restored democracy. Recent authoritarian actions by leaders within communist parties have been met with internal opposition, indicating ongoing contestation over democratic norms. The study concludes that communist parties currently do not threaten Nepal's democracy but notes that their continued commitment to Marxism-Leninism raises questions about their full democratic credentials.
Additional Information
- Source:Journal of Asian & African Studies (Sage Publications, Ltd.). 2025/11, Vol. 60, Issue 7, p4733
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2025
- ISSN:0021-9096
- DOI:10.1177/00219096241263960
- Accession Number:188807215
- Copyright Statement:Copyright of Journal of Asian & African Studies (Sage Publications, Ltd.) is the property of Sage Publications Inc. 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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