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Synthese Library

An Epistemic Foundation for Scientific Realism

Defending Realism Without Inference to the Best Explanation

Authors: Wright, John

  • Develops a new way of justifying the claims made by science about phenomenon not directly observable by humans
  • Argues that it is possible to rationally justify belief in unobservable entities without relying on inference to the best explanation
  • Applies the concept to key cases, including atoms and the size and shape of those parts of the universe lying beyond that which we can observe
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eBook $79.99
price for USA in USD (gross)
  • ISBN 978-3-030-02218-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.99
price for USA in USD
  • ISBN 978-3-030-02217-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This monograph develops a new way of justifying the claims made by science about phenomenon not directly observable by humans, such as atoms and black holes. It details a way of making inferences to the existence and properties of unobservable entities and states of affairs that can be given a probabilistic justification. The inferences used to establish realist claims are not a form of, and neither do they rely on, inference to the best explanation.

Scientific Realism maintains that scientific theories and hypotheses refer to real entities, forces, and relations, even if one cannot examine them. But, there are those who doubt these claims. The author develops a novel way of defending Scientific Realism against a range of influential attacks. He argues that in some cases, at least, we can make probabilistically justifiable inferences from observed data to claims about unobservable, theoretical entities. He shows how this enables us to place some scientific realist claims on a firmer epistemological footing than has previously been the case. This also makes it possible to give a unified set of replies to the most common objections to Scientific Realism.

The final chapters apply the developed conceptual apparatus to key cases from the history of science and from recent science. One example concerns realism with respect to atoms. Another looks at inferences from recent astronomical data to conclusions about the size and shape of those parts of the universe lying beyond that which we can observe.

About the authors

John Wright is Senior Lecturer in Philosophy at the University of Newcastle, Australia. He has published books in philosophy of science, metaphysics and ethics and economics as well as numerous articles in peer-reviewed journals.

Table of contents (8 chapters)

  • Introduction: Realism and Reason

    Wright, John

    Pages 1-6

  • The Skeptical Arguments Against Realism I: Inductive Skepticism

    Wright, John

    Pages 7-36

  • The Skeptical Arguments – 2

    Wright, John

    Pages 37-77

  • Realism and Inference to the Best Explanation

    Wright, John

    Pages 79-115

  • On the Inference to Unobservables

    Wright, John

    Pages 117-143

Buy this book

eBook $79.99
price for USA in USD (gross)
  • ISBN 978-3-030-02218-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.99
price for USA in USD
  • ISBN 978-3-030-02217-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
An Epistemic Foundation for Scientific Realism
Book Subtitle
Defending Realism Without Inference to the Best Explanation
Authors
Series Title
Synthese Library
Series Volume
402
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-02218-1
DOI
10.1007/978-3-030-02218-1
Hardcover ISBN
978-3-030-02217-4
Edition Number
1
Number of Pages
VIII, 220
Number of Illustrations
16 b/w illustrations
Topics