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Can We Be Wrong? The Problem of Textual Evidence in a Time of Data - Elements in Digital Literary Studies Piper, Andrew (McGill University, Montreal)
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Can We Be Wrong? The Problem of Textual Evidence in a Time of Data - Elements in Digital Literary Studies
Piper, Andrew (McGill University, Montreal)
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.
75 pages, Worked examples or Exercises; 13 Line drawings, black and white
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | November 19, 2020 |
| ISBN13 | 9781108926201 |
| Publishers | Cambridge University Press |
| Pages | 86 |
| Dimensions | 227 × 150 × 9 mm · 142 g |
| Language | English |