JOURNAL ARTICLE

Mexican Federal Law for the Protection of Cultural Heritage of Indigenous and Afro-Mexican Peoples and Communities.

  • Published In: GRUR International: Journal of European & International IP Law, 2023, v. 72, n. 4. P. 364 1 of 3

  • Database: Legal Source 2 of 3

  • Authored By: Santamaria Hernández, Esteban 3 of 3

Abstract

This article analyzes the Mexican Federal Law for the Protection of Cultural Heritage of Indigenous and Afro-Mexican Peoples and Communities (the Mexican sui generis law), enacted in 2022 to safeguard traditional knowledge (TK), traditional cultural expressions (TCEs), and, to a limited extent, genetic resources (GE). The law aims to recognize and guarantee collective intellectual property rights of indigenous and Afro-Mexican peoples, including mechanisms against unauthorized use and misappropriation, while establishing a collaborative system between federal authorities and communities. The analysis highlights that although the law incorporates many recommended elements from international literature on sui generis protection, it lacks clear definitions of key concepts such as intellectual property, excludes genetic resources from its full scope, and did not involve ad hoc indigenous consultations during its legislative process. The article concludes that while the law represents a significant national effort responding to indigenous demands, its effectiveness will depend on further detailed implementation, institutional capacity, and ongoing engagement with indigenous communities.

Additional Information

  • Source:GRUR International: Journal of European & International IP Law. 2023/04, Vol. 72, Issue 4, p364
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:26328550
  • DOI:10.1093/grurint/ikac146
  • Accession Number:162875285
  • Copyright Statement:Copyright of GRUR International: Journal of European & International IP 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.