JOURNAL ARTICLE

Intellectual property rights as a tool for bridging gender gap: approaches and prospects under the African Union.

  • Published In: Journal of Intellectual Property Law & Practice, 2025, v. 20, n. 3. P. 155 1 of 3

  • Database: Legal Source 2 of 3

  • Authored By: Mwakaje, Saudin J 3 of 3

Abstract

This article examines the integration of intellectual property rights (IPRs) within the African Union's (AU) women's empowerment initiatives, arguing that current AU frameworks insufficiently incorporate IPRs as tools to bridge the gender gap. It highlights the socio-economic and cultural challenges African women face in accessing and benefiting from the IPR system, despite the recognized role of IPRs in fostering innovation, creativity, and economic empowerment. The article reviews key AU legal instruments and policies—such as the Maputo Protocol, the Solemn Declaration on Gender Equality in Africa, and the African Continental Free Trade Area (AfCFTA) protocols—finding that while these promote gender equality broadly, they lack explicit strategies for leveraging IPRs to empower women. It recommends that the AU adopt a gender-conscious continental IPR agenda, establish support structures for women in IP, reconsider IP legal principles to reflect women's contributions (including co-ownership in matrimonial contexts), and conduct a comprehensive continental IP needs assessment to better integrate IPRs into gender equality efforts.

Additional Information

  • Source:Journal of Intellectual Property Law & Practice. 2025/03, Vol. 20, Issue 3, p155
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:17471532
  • DOI:10.1093/jiplp/jpae093
  • Accession Number:184349190
  • Copyright Statement:Copyright of Journal of Intellectual Property Law & Practice 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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