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 theoryLiterary studies: from c 1900 -Database programming
AI Summary
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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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