JOURNAL ARTICLE

MIRROR OF LITERATURE: THE HISTORIAN AS A CHARACTER IN A NOVEL.

  • Published In: Historyka: Studia Metodologiczne, 2025, v. 55. P. 189 1 of 3

  • Database: Central & Eastern European Academic Source 2 of 3

  • Authored By: ŠVEDAS, AURIMAS 3 of 3

Abstract

This article analyses three novels of exceptional content and form, written at the end of the 20th century by Graham Swift, Penelope Lively, and William H. Gass, where the main characters are historians. The historians' portraits that emerge in the novels Waterland, Moon Tiger and The Tunnel are complicated, melodramatic personalities, rebellious figures bearing a complex fate who try to come to terms with the outcomes of their traumas. They live through the crisis resulting from their traumas and the change of time regimes, reflect on the meaning of the historian's work, the value of history to people and society, and try to find an answer to the question of whether the ability to tell stories will help them deal with the scars history leaves behind as it breaks people's destinies. How should historians read and interpret these novels? Can the imagery of a scholar examining the past or lecturing on history created in the pages of a novel tell us something new about how today's society understands the work done by a historian? How can such portraits of a historian (historians) help us in our analysis of society's self-awareness, its experience of time, and historical sensibility? This article seeks answers to the questions raised above. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Historyka: Studia Metodologiczne. 2025/01, Vol. 55, p189
  • Document Type:Article
  • Subject Area:Biography
  • Publication Date:2025
  • ISSN:0073-277X
  • DOI:10.24425/hsm.2025.156567
  • Accession Number:190429155
  • Copyright Statement:Copyright of Historyka: Studia Metodologiczne is the property of Polish Academy of Sciences 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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