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Religious Heritage and Nuclear Communication: Principles from Christianity, Hinduism, and Islam.

  • Published In: International Journal of Religion & Spirituality in Society, 2025, v. 15, n. 3. P. 169 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Muzas, Brian 3 of 3

Abstract

This article examines the influence of religious heritage, specifically through the religious traditions of Christianity, Islam, and Hinduism, on nuclear security discourse and policy, with a particular focus on Catholicism and Shi'ite Islam. By employing a just war framework as a comparative baseline, it conducts a cross-religion analysis of ethical approaches to warfare and nuclear weapons. This methodology facilitates "translation" among religious perspectives, illuminating both shared principles and unique insights within each tradition. The study finds that while these traditions share some common principles, they also present unique perspectives that can significantly affect nuclear policy decisions. The article concludes that awareness of religious heritage is crucial for effective communication and negotiation in the nuclear age. Policy recommendations include incorporating religious perspectives in nuclear policy discussions, promoting interfaith dialogue, investing in education on diverse religious views, and leveraging shared principles in international negotiations. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Religion & Spirituality in Society. 2025/09, Vol. 15, Issue 3, p169
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:2154-8633
  • DOI:10.18848/2154-8633/CGP/v15i03/169-193
  • Accession Number:188299668
  • Copyright Statement:Copyright of International Journal of Religion & Spirituality in Society is the property of Common Ground Research Networks 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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