Shakespeare's Queer Analytics (PDF)
Distant Reading and Collaborative Intimacy in 'Love's Martyr'
(Sprache: Englisch)
What led Shakespeare to write his most cryptic poem, 'The Phoenix and Turtle'? Could the Phoenix represent Queen Elizabeth, on the verge of death as Shakespeare wrote? Is the Earl of Essex, recently executed for treason, the Turtledove lover of the Phoenix?...
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What led Shakespeare to write his most cryptic poem, 'The Phoenix and Turtle'? Could the Phoenix represent Queen Elizabeth, on the verge of death as Shakespeare wrote? Is the Earl of Essex, recently executed for treason, the Turtledove lover of the Phoenix? Questions such as these dominate scholarship of both Shakespeare's poem and the book in which it first appeared: Robert Chester's enigmatic collection of verse, Love's Martyr (1601), where Shakespeare's allegory sits next to erotic love lyrics by Ben Jonson, George Chapman and John Marston, as well as work by the much lesser-known Chester.
Don Rodrigues critiques and revises traditional computational attribution studies by integrating the insights of queer theory to a study of Love's Martyr. A book deeply engaged in current debates in computational literary studies, it is particularly attuned to questions of non-normativity, deviation and departures from style when assessing stylistic patterns. Gathering insights from decades of computational and traditional analyses, it presents, most radically, data that supports the once-outlandish theory that Shakespeare may have had a significant hand in editing works signed by Chester. At the same time, this book insists on the fundamentally collaborative nature of production in Love's Martyr.
Developing a compelling account of how collaborative textual production could work among early modern writers, Shakespeare's Queer Analytics is a much-needed methodological intervention in computational attribution studies. It articulates what Rodrigues describes as 'queer analytics': an approach to literary analysis that joins the non-normative close reading of queer theory to the distant attention of computational literary studies - highlighting patterns that traditional readings often overlook or ignore.
Don Rodrigues critiques and revises traditional computational attribution studies by integrating the insights of queer theory to a study of Love's Martyr. A book deeply engaged in current debates in computational literary studies, it is particularly attuned to questions of non-normativity, deviation and departures from style when assessing stylistic patterns. Gathering insights from decades of computational and traditional analyses, it presents, most radically, data that supports the once-outlandish theory that Shakespeare may have had a significant hand in editing works signed by Chester. At the same time, this book insists on the fundamentally collaborative nature of production in Love's Martyr.
Developing a compelling account of how collaborative textual production could work among early modern writers, Shakespeare's Queer Analytics is a much-needed methodological intervention in computational attribution studies. It articulates what Rodrigues describes as 'queer analytics': an approach to literary analysis that joins the non-normative close reading of queer theory to the distant attention of computational literary studies - highlighting patterns that traditional readings often overlook or ignore.
Autoren-Porträt von Don Rodrigues
Don Rodrigues is an Assistant Professor of English at Old Dominion University, USA. He specializes in early modern literature and culture, queer theory, and computational approaches to early modern literature. He has published on Shakespearean authorship and presented widely on computational stylistics, early modern literature and culture, and gender and sexuality. Rodrigues has held fellowships with the Folger Shakespeare Library, Vanderbilt University's Center for Digital Humanities, and Harvard University's metaLAB.
Bibliographische Angaben
- Autor: Don Rodrigues
- 2022, 1. Auflage, 296 Seiten, Englisch
- Verlag: Bloomsbury UK
- ISBN-10: 1350178845
- ISBN-13: 9781350178847
- Erscheinungsdatum: 27.01.2022
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