JOURNAL ARTICLE

GILGĀMEŠ BEYOND CUNEIFORM. ANCIENT LITERARY TRANSMISSION AND THE ROLE OF EMPIRE RECONSIDERED.

  • Published In: Journal of Ancient Civilizations / Gudai Wenming, 2026, v. 41, n. 1. P. 1 1 of 3

  • Database: Historical Abstracts with Full Text 2 of 3

  • Authored By: Edmonds, Alexander Johannes 3 of 3

Abstract

The Mesopotamian literary figure Gilgāmeš has long been known to have survived outside of cuneiform literature, but the extent and manner of his reception has been a source of controversy. Using "top-down" methodologies which generally presuppose intercultural literary transmission as a result of imperial processes such as ancient "globalisation," one line of thought has argued for the widespread influence of works associated with Gilgāmeš outside of the cuneiform literary corpus. Noting issues of insufficient falsifiability in such approaches, a novel, "bottom-up" methodology is instead articulated in this study, constructing detailed "literary microhistories" of the individual extracuneiform attestations of Gilgāmeš-like figures, and conservatively positing their relationships both to the Akkadian literary corpus and to each other. This not only supplies a new basis for literary historical research into the extra-cuneiform dissemination of the character Gilgāmeš, but also posits overlooked routes of literary transmission within first-millennium BC empires. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Ancient Civilizations / Gudai Wenming. 2026/01, Vol. 41, Issue 1, p1
  • Document Type:Article
  • Subject Area:Political Science
  • Publication Date:2026
  • ISSN:2097-2296
  • DOI:10.16758/j.cnki.1004-9371.2026.02.017
  • Accession Number:193639465
  • Copyright Statement:Copyright of Journal of Ancient Civilizations / Gudai Wenming is the property of Northeast Normal University, Institute for the History of Ancient Civilizations (IHAC) 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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