JOURNAL ARTICLE

Porous Penality and the Myth of Liberal Punishment: Lessons from South Africa.

  • Published In: British Journal of Criminology, 2024, v. 64, n. 1. P. 107 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Super, Gail 3 of 3

Abstract

This article examines the intrinsic relationship between law, violence, and punishment, drawing on Walter Benjamin's "Critique of Violence" to argue that state-imposed punishment is inherently violent and logically contradictory. Using South Africa as a case study, it highlights how the state's legal authority to punish often overlaps with extralegal penal violence, disproportionately targeting the racialized poor across multiple jurisdictions, including prisons, police and prosecutorial systems, and civilian vigilante actions. The concept of "penal violence" is employed to encompass both lawful and unlawful violence aimed at enforcing law or punishing perceived transgressions, revealing porous boundaries between legal and extralegal violence. The article critiques the South African Constitutional Court's 1995 Makwanyane decision, which abolished the death penalty but legitimized harsh imprisonment, and details systemic violence within prisons, police brutality, prosecutorial discretion, and tolerated civilian vigilantism, all of which sustain racialized inequalities. It concludes that the supposed distinction between lawful and unlawful violence is a fragile legal fiction, especially in contexts marked by historical racial oppression and socio-economic marginalization.

Additional Information

  • Source:British Journal of Criminology. 2024/01, Vol. 64, Issue 1, p107
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2024
  • ISSN:0007-0955
  • DOI:10.1093/bjc/azad017
  • Accession Number:174273379
  • Copyright Statement:Copyright of British Journal of Criminology 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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