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Chapter 5 - To Predict or to Describe?

from Part I - Toward a Smarter Data Science

Published online by Cambridge University Press:  21 September 2023

Jo Guldi
Affiliation:
Southern Methodist University, Texas
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Summary

This chapter revisits the fantastical conceit that we can make significant predictions about a society. Engaging recent critiques of predictive logic by Jill Lepore, it touches upon the misuses of partially accurate predictive machines – the marketing research technology that has become part of the fabric of political and social life in our time – often with disastrous consequences. The chapter revisits the fantastic project of Peter Turchin, to map out predictive laws of human society, analyzing him against objections against modeling the evolution of human interactions as law-like, from Karl Popper to William Sewell. It engages the theoretical work of Reinhart Koselleck, who argues that prediction or prophecy is untenable, and that we only have prognosis. It looks at the conditions under which Koselleck imagines “prognosis” to be tenable, including the example of grievance theory, which refrains from predicting how or when a group might respond to historical oppression, and only describes the dynamics and acknowledges when there are “grounds” for revolt. The chapter makes room for readers who have turned to this book out of an interest in modeling or prediction to enter a more robust engagement with history, which is presented here as the source of a rigorous engagement with problems of change over time.

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Chapter
Information
The Dangerous Art of Text Mining
A Methodology for Digital History
, pp. 135 - 158
Publisher: Cambridge University Press
Print publication year: 2023

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  • To Predict or to Describe?
  • Jo Guldi, Southern Methodist University, Texas
  • Book: The Dangerous Art of Text Mining
  • Online publication: 21 September 2023
  • Chapter DOI: https://doi.org/10.1017/9781009263016.008
Available formats
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  • To Predict or to Describe?
  • Jo Guldi, Southern Methodist University, Texas
  • Book: The Dangerous Art of Text Mining
  • Online publication: 21 September 2023
  • Chapter DOI: https://doi.org/10.1017/9781009263016.008
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • To Predict or to Describe?
  • Jo Guldi, Southern Methodist University, Texas
  • Book: The Dangerous Art of Text Mining
  • Online publication: 21 September 2023
  • Chapter DOI: https://doi.org/10.1017/9781009263016.008
Available formats
×