JOURNAL ARTICLE
Strategic Judicial Empowerment.
Published In: American Journal of Comparative Law, 2024, v. 72, n. 1. P. 170 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Tew, Yvonne 3 of 3
Abstract
This article examines the phenomenon of strategic judicial self-empowerment, focusing on how apex courts in Pakistan, Malawi, Malaysia, and the United Kingdom deploy various legal and institutional strategies to enhance their authority vis-à-vis other branches of government in politically challenging contexts. It identifies five key strategies: maxi-minimalism (broad reasoning with narrow rulings to avoid backlash), mini-maximalism (formalistic reasoning masking expansive impact), coalition-building with other institutions, rhetorical framing to engage popular support, and unanimous decisions to present a unified judicial front. The article further analyzes conditions prompting courts to assert power, such as threats to judicial independence, political crises, public support, and influential judicial leadership, illustrating these dynamics through landmark cases including Malawi's annulment of a presidential election, Malaysia's assertion of judicial review over constitutional amendments, Pakistan's development of a doctrine limiting constitutional amendments, and the U.K. Supreme Court's rulings during Brexit. It concludes that while judicial self-empowerment carries risks of political backlash, judicious use of strategic statecraft can strengthen courts' institutional roles within diverse constitutional orders.
Additional Information
- Source:American Journal of Comparative Law. 2024/03, Vol. 72, Issue 1, p170
- Document Type:Article
- Subject Area:Law
- Publication Date:2024
- ISSN:0002-919X
- DOI:10.1093/ajcl/avad040
- Accession Number:179665184
- Copyright Statement:Copyright of American Journal of Comparative Law 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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