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

Explore the intriguing intersection of data and textual evidence in Andrew Piper's insightful work, Can We Be Wrong? The Problem of Textual Evidence in a Time of Data. Published by Cambridge University Press in 2020, this thought-provoking book spans 75 pages and delves into the complexities of generalization across diverse disciplines. Piper employs a machine learning-based approach to analyze tens of thousands of sentences, shedding light on the prevalence and nuances of generalization in textual evidence. In addition to presenting data-driven insights, the book offers a robust discussion on potential solutions to the challenges posed by generalizability. This essential read is perfect for scholars, researchers, and anyone interested in the evolving landscape of data analysis and textual interpretation. Don't miss the opportunity to enhance your understanding of this critical topic!