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Prof. Dr. Thomas Bartelborth

Emeritus

Institute of Philosophy
Geisteswissenschaftliches Zentrum
Beethovenstraße 15
04107 Leipzig

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Abstract

I have been professor for philosophy of science at Leipzig University since 1994. Initially at the Institute for Logic and Philosophy of Science and since 2007 within the Institute for Philosophy as part of the Master program in Logic. Before that, I received my diploma in mathematics in Bielefeld in 1985 and then worked in the field of philosophy at the LMU in Munich (with Wolfgang Stegmüller) and the FU in Berlin (with Ulisses Moulines). My research mainly relates to topics in epistemology and philosophy of science. This includes questions about the choice of the best theory in the empirical sciences, justifications for scientific claims, Bayesianism, scientific explanations and questions about (scientific) rationality as well as about coherence theories of justification and last but not least about causality and causal inference. These topics are also discussed in my courses.

Professional career

  • 06/1987 - 09/1989
    Research Assistant at the Ludwig Maximilians University in Munich at the Institute for Statistics, Logic and Philosophy of Science with Prof. Dr. Dr. W. Stegmüller
  • 10/1989 - 04/1993
    Research Assistant at the Free University of Berlin with Prof. Dr. C.U. Moulines
  • 05/1993 - 09/1994
    Research Assistant at the Ludwig Maximilians University in Munich at the Institute for Philosophy, Logic and Philosophy of Science
  • since 11/1994
    Professor for Philosophy of Science at the University of Leipzig

Education

  • 10/1977 - 03/1985
    study of mathematics, physics and philosophy at the University of Bielefeld
  • 03/1985 - 11/1987
    PhD in philosophy (Title: A Logical Reconstruction of Classical Electrodynamics)
  • 10/1994
    Habilitation in philosophy at the Free University of Berlin with the thesis: Wissenschaftliche Erklärungen und menschliche Erkenntnis. Eine diachronische Kohärenztheorie der epistemischen Rechtfertigung

The aim of my research is to explore and compare different methods for the choice of theories in the empirical sciences. A coherence theory of epistemic justification serves as the framework for the study. It shows exactly what further background knowledge determines our choice of theories and what significance probabilistic variables such as the likelihoods of theories or Bayesian plausibility degrees are assigned to. The concept of coherence itself is developed as a version of explanatory coherence and has to prove itself in examples from the history of science. In addition to the inductive support of theories, the explanatory coherence also takes into account their information content and is therefore one of the few approaches that can already implement the most important aspects of a multidimensional choice of theories. In this context, the classical statistics and Bayesian approaches are epistemologically evaluated and developed further. This includes the explication of conceptions of causality, (objective) probability, natural laws and related basic concepts, since they concern essential aspects of good theories. In addition, the question arises as to the peculiarities of social science explanations compared to explanations in the natural sciences.

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The main focus of my teaching is in the areas of philosophy of science and epistemology, which includes the presentation of epistemological approaches to questions of knowledge and epistemic justification, the epistemic conception of explanatory coherence, and there are further courses on modern theories of scientific explanation and on causality and causal inference as well as on epistemic and objective interpretations of probability, which play an important role in many areas of this complex of questions. In addition, there are courses on explaining and understanding in the social sciences and on the philosophy of mathematics.

  • Courses in the winter semester 2020/21

    1. Seminar: Scientific Realism

    2. Seminar: Philosophy of Social Science

    3. Lecture: Formal approaches in epistemology

    4. Seminar: Causal Inference