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Supplementary Data for Can We Be Wrong?

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posted on 2020-07-17, 17:32 authored by Andrew PiperAndrew Piper

This data accompanies the book, Can We Be Wrong? The Problem of Textual Evidence in a Time of Data, by Andrew Piper (Cambridge 2020).

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Social Sciences and Humanities Research Council of Canada

Social Sciences and Humanities Research Council

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Digital Humanities computational literary studies Science of Science Machine Learning generalization Digital Humanities Literary Studies not elsewhere classified Knowledge Representation and Machine Learning

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