Can We Be Wrong? The Problem of Textual Evidence in a Time of Data

by Andrew Piper

Book Details

Format Paperback / Softback

Book Series Elements in Digital Literary Studies

ISBN-10 1108926207

ISBN-13 9781108926201

Publisher Cambridge University Press

Imprint Cambridge University Press

Country of Manufacture US

Country of Publication GB

Publication Date Nov 19th, 2020

Print length 75 Pages

Weight 142 grams

Dimensions 15.00 x 22.70 x 0.90 cms

Product Classification: Literary theory Literary studies: from c 1900 -Database programming

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This Element combines a machine learning-based approach to detect the prevalence and nature of generalization across tens of thousands of sentences from different disciplines alongside a robust discussion of potential solutions to the problem of the generalizability of textual evidence.

This Element tackles the problem of generalization with respect to text-based evidence in the field of literary studies. When working with texts, how can we move, reliably and credibly, from individual observations to more general beliefs about the world? The onset of computational methods has highlighted major shortcomings of traditional approaches to texts when it comes to working with small samples of evidence. This Element combines a machine learning-based approach to detect the prevalence and nature of generalization across tens of thousands of sentences from different disciplines alongside a robust discussion of potential solutions to the problem of the generalizability of textual evidence. It exemplifies the way mixed methods can be used in complementary fashion to develop nuanced, evidence-based arguments about complex disciplinary issues in a data-driven research environment.

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