Judgment is needed as an additional source of knowledge in measurement. This chapter aims to clarify what kind of judgment is referred to and what it is not. Judgment is defined in the Kantian sense; it presupposes intuition and imagination, and is not a strict deduction of particulars from universals. It requires expertise, that is, real experience with the particulars to which it is applied. But judgments in this sense are subjective. To eliminate this subjectivity, also called “bias,” accounts are developed that ensure that judgments are rational, for example, “unbiased.” A rational judgment, however, is not a Kantian judgment; it is the optimal solution of a model that represents a real-life judgment problem. But a real-life problem can be modeled in various different ways, each with a different rational solution. In the chapter’s appendix it is shown that correct Bayesian deduction can be biased as defined in mathematical statistics.
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