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Theory-laden experimentation

机译：理论丰富的实验

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The thesis of theory-ladenness of observations, in its various guises, is widely considered as either ill-conceived or harmless to the rationality of science. The latter view rests partly on the work of the proponents of New Experimentalism who have argued, among other things, that experimental practices are efficient in guarding against any epistemological threat posed by theory-ladenness. In this paper I show that one can generate a thesis of theory-ladenness for experimental practices from an influential New Experimentalist account. The notion 1 introduce for this purpose is the concept of 'theory-driven data reliability judgments' (TDR), according to which theories which are sought to be tested with a particular set of data guide reliability judgments about those very same data. I provide various prominent historical examples (among others, the confirmation of Einstein's prediction of star light bending in 1919 by Eddington and others) to show that TDRs are used by scientists to resolve data conflicts. I argue that the rationality of the practices which employ TDRs can be saved if the independent support of the theories driving TDRs is construed in a particular way.
机译：带有各种形式的观测理论负载论被广泛认为是对科学合理性的误解或无害。后一种观点部分取决于新实验主义的拥护者的工作，他们主张，除其他外，实验实践可以有效地防范理论负担带来的任何认识论威胁。在本文中，我表明可以从一个有影响力的“新实验主义者”的帐户中为实验实践生成理论负载理论。为此目的引入的概念1是“理论驱动的数据可靠性判断”（TDR）的概念，根据该理论，试图用一组特定的数据集进行测试的理论将指导那些非常相同的数据。我提供了许多著名的历史例子（其中包括爱丁顿（Eddington）和其他人对爱因斯坦1919年对星光弯曲的预测的证实），以表明TDR被科学家用来解决数据冲突。我认为，如果以特殊方式解释驱动TDR的理论的独立支持，则可以节省采用TDR的做法的合理性。

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