David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Philosophy of Science 62 (3):438-458 (1995)
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
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Jonathan Y. Tsou (2012). Intervention, Causal Reasoning, and the Neurobiology of Mental Disorders: Pharmacological Drugs as Experimental Instruments. Studies in History and Philosophy of Science Part C 43 (2):542-551.
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Elisabeth A. Lloyd (2015). Model Robustness as a Confirmatory Virtue: The Case of Climate Science. Studies in History and Philosophy of Science Part A 49:58-68.
Anna Leuschner (2012). Pluralism and Objectivity: Exposing and Breaking a Circle. Studies in History and Philosophy of Science Part A 43 (1):191-198.
Anna Leuschner (2015). Uncertainties, Plurality, and Robustness in Climate Research and Modeling: On the Reliability of Climate Prognoses. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 46 (2):367-381.
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