JOURNAL ARTICLE
Opening the Social Sciences: Questioning Eurocentrism and Implementing Contextualized Open Science.
Published In: Global Perspectives, 2024, v. 5, n. 1. P. 1 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Beigel, Fernanda; Persia, Daniel 3 of 3
Abstract
In this paper, we analyze two global projects, twenty-five years apart—the report of the Gulbenkian Commission, published for the first time in Spanish in 1996, and the open science project, known more widely since the approval of the UNESCO Recommendation on Open Science of 2021—from the perspective of Latin America. In the first section, we revisit the program proposed by Immanuel Wallerstein in the Gulbenkian Report to "open the social sciences" and its main pillars. We then relate this project to the idea of citizen science, the FAIR and CARE principles, and the need to advance participatory science practices with informational justice. Afterwards, we analyze the Latin American path for open science and collaborative infrastructure that has been developing since the 1950s. We analyze the intellectual, institutional, and political conditions that allow our region to carve its own path for open science—and the extent to which the social sciences participate in that process and are affected or promoted by it. Finally, we discuss the critical role of the region's evaluation systems in producing a transformation that reaches the magnitude of open science, without subalternizing the communities that participate in the co-production of open knowledges. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Global Perspectives. 2024/04, Vol. 5, Issue 1, p1
- Document Type:Article
- Subject Area:Biography
- Publication Date:2024
- ISSN:2575-7350
- DOI:10.1525/gp.2023.91203
- Accession Number:184677350
- Copyright Statement:Copyright of Global Perspectives is the property of University of California Press 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.