JOURNAL ARTICLE
Gender Politics in Mythology: A Reading of Aeschylus's Agamemnon.
Published In: International Journal of Literary Humanities, 2025, v. 23, n. 2. P. 217 1 of 3
Database: Humanities Source Ultimate 2 of 3
Authored By: Rahman, Md. Munibur; Yeasmin, Farhana; Jamila, Marium 3 of 3
Abstract
This study centers on examining the power dynamics within the gender politics of ancient Greek society, drawing insights from Aeschylus’s play, Agamemnon. In this qualitative research, utilizing textual analysis of both primary and secondary sources, the authors delve into the play to unravel the diverse layers of meaning, cultural contexts, and stylistic choices embedded in the text. The findings of this study unveiled a pattern of victimization and exploitation of women by male figures within literature and mythology, underscoring the gender politics orchestrated by the prevailing male-dominated society. In Agamemnon, Helen and Cassandra were viewed as objects and prizes, while Clytemnestra and her daughter Iphigenia were marginalized in decisions concerning their personal lives, liberty, and justice. These instances reflect the pervasive influence of male-dominated gender politics across various spheres, including society, history, social structures, state mechanisms, literature, and mythology. This exploration holds momentous universal relevance, as the dynamics explored surpass any specific culture, country, or historical period. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Literary Humanities. 2025/06, Vol. 23, Issue 2, p217
- Document Type:Article
- Subject Area:Literature and Writing
- Publication Date:2025
- ISSN:23277912
- DOI:10.18848/2327-7912/CGP/v23i02/217-234
- Accession Number:190499789
- Copyright Statement:Copyright of International Journal of Literary Humanities is the property of Common Ground Research Networks 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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