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Utopic Dreaming on the Borderlands: An Anzaldúan Reading of Yuri Herrera's Signs Preceding the End of the World

Authors: Cordelia E. Barrera;

Utopic Dreaming on the Borderlands: An Anzaldúan Reading of Yuri Herrera's Signs Preceding the End of the World

Abstract

Abstract The work of Gloria Anzaldúa has not typically been read in concert with utopian studies. Much of her writing, however, offers a rich resource for utopian critique. This is a significant omission given that much of Latin@ speculative fiction has been deemed inherently utopic. Latin@futurism is a field of inquiry by which to focus on the utopian as a broader category of visionary, speculative forms. Anzaldúa draws on techniques of defamiliarization to usher a change of consciousness in the reader, exemplified by her theories of conocimiento, el cenote, and nepantla. This article discusses Anzaldúa's theory of el cenote as a powerful heterotopic space of renewal and transformation in Yuri Herrera's novel Signs Preceding the End of the World. Anzaldúa's theories of conocimiento and nepantla flesh out culminating aspects of borderlands dreaming in the novel that connect to a discourse of apocalypse and its relationship to historical renewal and social justice.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
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