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Truth or Consequences? Generative Versus Consequential Justification in Science

Published online by Cambridge University Press:  28 February 2022

Thomas Nickles
Thomas Nickles*
Affiliation:
University of Nevada-Reno
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Extract

For the past century the Central Dogma of confirmation theory has been:

All empirical support (of a theoretical claim) = empirical evidence = empirical data = successful test results = successful predictions or postdictions = true empirical consequences (of the claim plus auxiliary assumptions).

According to the Dogma, all empirical support derives from empirical testing of predicted consequences. I shall attack this pure consequentialism and defend the importance of generative justification in science.

One question which has been widely debated through the years is whether “postdicting” or explaining already known phenomena provides as much epistemic support for an hypothesis as predicting new phenomena or, indeed, whether explanation provides any support at all. I believe that explanation is on a par with prediction, but I want to address a different question here. Both explanation and prediction (as usually construed) involve consequential reasoning.

Type
Part XII. Confirmation
Information
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association , Volume 1988 , Issue 2: Volume Two: Symposia and Invited Papers 1988 , 1988 , pp. 393 - 405
Copyright
Copyright © 1989 by the Philosophy of Science Association

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Footnotes

1

This paper is dedicated to the memory of my colleague, Willard Day, for his helpful comments and his exemplary life. I thank my co-symposiasts for a good discussion and the National Science Foundation for research support.

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