Probability Designs: Literature and Predictive Processing


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Description

In Probability Designs, Karin Kukkonen proposes a new perspective on the complex role of predictions and probabilities in the dynamics of literary narrative. Predictive processing, an emerging account of cognition in neuroscience, psychology, and philosophy, provides the theoretical backdrop for an investigation of how literary texts shape readers' expectations and experience. Through deft analysis of the literary canon in a variety of cultures and languages, she constructs a comprehensive model of probability in a novel's plots, immersive appeal, and potential for reflection. Linking predictive processing to the idea that culture and cognition always develop in tandem, Kukkonen then sketches a place for literature and literary form in this exchange - a mode of exploratory thinking that takes language and writing to the next level.

Chance encounters, last-minute rescues, and coincidences launch Kukkonen's investigation of the literary manipulation of predictions. Through an enlightening blend of cognitive sciences and literary theory, Probability Designs enriches scholarly debates in literary studies and sheds light on how vital literature is for human thought.

Author: Karin Kukkonen
Publisher: Oxford University Press, USA
Published: 01/16/2020
Pages: 240
Binding Type: Hardcover
Weight: 1.20lbs
Size: 9.80h x 6.40w x 1.10d
ISBN13: 9780190050955
ISBN10: 0190050950
BISAC Categories:
- Language Arts & Disciplines | Linguistics | Psycholinguistics | General
- Literary Criticism | Comparative Literature

About the Author

Karin Kukkonen is Professor in Comparative Literature at the University of Oslo. Her work investigates how the novel emerged as a genre designed for particular cognitive and emotional engagements and how the poetics of earlier periods and cognitive poetics today can speak to each other. At the University of Oslo, Kukkonen heads the interdisciplinary research and teaching initiative "Literature, Cognition and Emotions" (2019-2023).