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What Can Narrative Theory Learn from Illness Narratives?

Authors: Shlomith, Rimmon-Kenan;

What Can Narrative Theory Learn from Illness Narratives?

Abstract

This essay assumes the possibility of establishing a fruitful mutual relationship between narratology and autobiographical illness narratives. Within this relationship, it focuses on several ways in which the latter illuminate, and sometimes problematize, central notions in narratology and narrative theory. The main issues explored are 1) the complex interaction between the collapse of the body and that of the narrative, and its implications for the interplay between order and contingency; 2) the resistance of a disintegrating body to both verbalization and narration, as well as its paradoxical articulation in language and narrative; 3) the potential undermining of the author-reader "contract" by a blunt narration of disturbing physical details; and 4) the ethical and psychological risks involved in texts where flesh-and-blood readers are also (fictional?) characters, and the pain, misunderstandings, and erasures such implicated readers may experience in the reception.

Related Organizations
Keywords

Anecdotes as Topic, Narration, Humans, Models, Theoretical, United States

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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!
14
Top 10%
Top 10%
Average
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