JOURNAL ARTICLE

The Perils of Gender Self-Determination: Global Shifts in Sex Reclassification Law and Policy.

  • Published In: American Journal of Comparative Law, 2023, v. 71, n. 3. P. 707 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Katri, Ido 3 of 3

Abstract

The article examines the global evolution of legal recognition and protection of transgender populations through laws and policies enabling gender self-determination, defined as the right to self-identify one’s gender without medical or external corroboration. It provides a comparative analysis of sex reclassification frameworks worldwide, ranging from complete bans and medical prerequisites (such as sterilization or bodily modification) to corroboration schemes and self-identification models, highlighting a shift from external bodily criteria to internal gender identity as the basis for legal recognition. While self-identification laws enhance autonomy and access to identification documents, the article argues they remain structurally limited by the foundational legal system of sex classification assigned at birth, which continues to enforce binary gender norms and systemic inequalities. The article concludes that addressing gender inequality and trans rights requires critically rethinking the legal category of sex itself, moving beyond current frameworks that separate gender identity from sex and proposing alternative normative approaches that challenge the centrality of birth-assigned sex classifications.

Additional Information

  • Source:American Journal of Comparative Law. 2023/09, Vol. 71, Issue 3, p707
  • Document Type:Article
  • Subject Area:Women's Studies and Feminism
  • Publication Date:2023
  • ISSN:0002-919X
  • DOI:10.1093/ajcl/avae002
  • Accession Number:176355821
  • Copyright Statement:Copyright of American Journal of Comparative 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.)

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