JOURNAL ARTICLE

Electoral Malpractice as Treasonable Felony: A Constitutional Reappraisal under Nigerian Law.

  • Published In: African Journal of Democracy & Election Research (AJDER), 2025, v. 5, n. 2. P. 69 1 of 3

  • Database: Africa Studies Source 2 of 3

  • Authored By: Okeke, Odinakachukwu Emmanuel; Anushiem, Uchenna Maryjane 3 of 3

Abstract

The article critically examines electoral malpractice in Nigeria, arguing that severe forms of electoral fraud—such as systemic rigging, voter suppression, falsification of results, and electoral violence—should be constitutionally reclassified as treasonable felonies under Nigerian law. It highlights the disconnect between Nigeria's colonial-era legal definitions of treason, which focus on violent overthrow, and the 1999 Constitution's affirmation that sovereignty resides in the people, exercised primarily through elections. Drawing on Nigerian statutes, case law, and comparative insights from jurisdictions including Kenya, Ghana, South Africa, India, and the United States, the study contends that deliberate subversion of electoral integrity constitutes a fundamental assault on constitutional democracy and legitimacy. The article concludes by recommending doctrinal shifts, legislative amendments, and institutional reforms to treat egregious electoral offences as constitutional crimes warranting the gravest penalties, thereby reinforcing democratic accountability and the rule of law in Nigeria.

Additional Information

  • Source:African Journal of Democracy & Election Research (AJDER). 2025/12, Vol. 5, Issue 2, p69
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2025
  • ISSN:2752-6011
  • DOI:10.31920/2752-602X/2025/v5n2a4
  • Accession Number:192190732
  • Copyright Statement:Copyright of African Journal of Democracy & Election Research (AJDER) is the property of Adonis & Abbey Publishers Ltd. 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.