JOURNAL ARTICLE
An Econcentric Turn in the Transitional Restorative Justice Process in Colombia.
Published In: International Journal of Transitional Justice, 2023, v. 17, n. 1. P. 107 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Ordóñez-Vargas, Laura; Gonzalez, L C Peralta; Prieto-Rios, Enrique 3 of 3
Abstract
This article examines Colombia's transitional restorative justice process amid its 60-year internal conflict, focusing on an emerging "ecocentric turn"—an epistemological shift from anthropocentrism (human-centered) toward ecocentrism (nature-centered), with biocentrism as an intermediary hybrid position recognizing both human and non-human rights. It analyzes this shift at two levels: the institutional framework of the Special Jurisdiction for Peace (JEP), which has begun recognizing ethnic territories as collective victims and subjects of rights, and the grassroots experience of the campesino community in Palestina, Huila, which advances a biocentric restorative proposal integrating productive land use with environmental care. The article highlights tensions and challenges in balancing human and environmental reparations, noting that while the JEP's recognition of ethnic territories marks progress, it risks excluding non-ethnic groups like campesinos and may reduce nature to a resource in restorative projects. The campesino initiative exemplifies a biocentric approach that broadens multiculturalism and promotes mutual care between communities and nature, suggesting pathways for more inclusive and ecologically sensitive transitional justice in Colombia.
Additional Information
- Source:International Journal of Transitional Justice. 2023/03, Vol. 17, Issue 1, p107
- Document Type:Article
- Subject Area:Science
- Publication Date:2023
- ISSN:1752-7716
- DOI:10.1093/ijtj/ijad003
- Accession Number:163872212
- Copyright Statement:Copyright of International Journal of Transitional Justice 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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