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  1. Philosophy of Science in Germany, 1992–2012: Survey-Based Overview and Quantitative Analysis.Matthias Unterhuber, Alexander Gebharter & Gerhard Schurz - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):71-160.
    An overview of the German philosophy of science community is given for the years 1992–2012, based on a survey in which 159 philosophers of science in Germany participated. To this end, the institutional background of the German philosophy of science community is examined in terms of journals, centers, and associations. Furthermore, a qualitative description and a quantitative analysis of our survey results are presented. Quantitative estimates are given for: (a) academic positions, (b) research foci, (c) philosophers’ of science most important (...)
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  • Einstein’s Boxes: Incompleteness of Quantum Mechanics Without a Separation Principle.Carsten Held - 2015 - Foundations of Physics 45 (9):1002-1018.
    Einstein made several attempts to argue for the incompleteness of quantum mechanics, not all of them using a separation principle. One unpublished example, the box parable, has received increased attention in the recent literature. Though the example is tailor-made for applying a separation principle and Einstein indeed applies one, he begins his discussion without it. An analysis of this first part of the parable naturally leads to an argument for incompleteness not involving a separation principle. I discuss the argument and (...)
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  • Mean and Variance in Quantum Theory.John E. Gray & Andrew Vogt - 2015 - Foundations of Physics 45 (8):883-888.
    Calculation of the mean of an observable in quantum mechanics is typically assumed to require that the state vector be in the domain of the corresponding self-adjoint operator or for a mixed state that the operator times the density matrix be in the trace class. We remind the reader that these assumptions are unnecessary. We state what is actually needed to calculate the mean of an observable as well as its variance.
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