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Objectivity in Experimental Inquiry: Breaking Data-Technique Circles

Published online by Cambridge University Press:  01 April 2022

Sylvia Culp
Sylvia Culp*
Affiliation:
Department of Philosophy Western Michigan University
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Abstract

I respond to H. M. Collins's claim (1985, 1990, 1993) that experimental inquiry cannot be objective because the only criterium experimentalists have for determining whether a technique is “working” is the production of “correct” (i.e., the expected) data. Collins claims that the “experimenters' regress,” the name he gives to this data-technique circle, cannot be broken using the resources of experiment alone. I argue that the data-technique circle, can be broken even though any interpretation of the raw data produced by techniques is theory-dependent. However, it is possible to break this circle by eliminating dependence on even those theoretical presuppositions that are shared by an entire scientific community through the use of multiple independently theory-dependent techniques to produce robust bodies of data. Moreover, I argue, that it is the production of robust bodies of data that convinces experimentalists of the objectivity of their data interpretations.

Type
Research Article
Information
Philosophy of Science , Volume 62 , Issue 3 , September 1995 , pp. 438 - 458
Copyright
Copyright © Philosophy of Science Association 1995

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Footnotes

†

Send reprint requests to the author, Department of Philosophy, Western Michigan University, Kalamazoo, MI 49008

‡

I would like to thank Philip Kitcher, Gerald Doppelt, Arthur Falk, Quentin Smith, and an anonymous referee for their insightful criticism and helpful suggestions. Earlier versions of this paper were presented at the University of California, San Diego, University of Illinios, Urbana-Champaign, University of California, Irvine, Rice University and Western Michigan University. This work was supported by a New Faculty Research Support Program Grant and by funds from the Faculty Research and Creative Activities Support Fund, Western Michigan University.

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