Gerhard Schurz [2001, Journal for General Philosophy of Science, 32, 65-107] has proposed to reconstruct auxiliary hypothesis addition, e.g., postulation of Neptune to immunize Newtonian mechanics, with concepts from non-monotonous inference to avoid the retention of false predictions that are among the consequence-set of the deductive model. However, the non-monotonous reconstruction retains the observational premise that is indeed rejected in the deductive model. Hence, his proposal fails to do justice to Lakatos' core-belt model, therefore fails to meet what Schurz coined (...) "Lakatos' challenge". It is argued that Lakatos's distinction between core and belt of a research program is not mapable onto premise-set and consequence-set and that Schurz's understanding of a ceteris paribus clause as a transfinite list of interfering factors is problematic. I propose a simple reading of Lakatos's use of the term ceteris paribus clause and motivate why the term hypothesis addition, despite not being interpretable literally, came to be entrenched. (shrink)

ABSTRACTProbability judgements entail a conjunction fallacy if a conjunction is estimated to be more probable than one of its conjuncts. In the context of predication of alternative logical hypothesis, Bayesian logic provides a formalisation of pattern probabilities that renders a class of pattern-based CFs rational. BL predicts a complete system of other logical inclusion fallacies. A first test of this prediction is investigated here, using transparent tasks with clear set inclusions, varying in observed frequencies only. Experiment 1 uses data where (...) BL makes dominant predictions; Experiment 2's predictions were less clear, and we additionally investigated judgements about the second-most probable hypotheses. The results corroborated a pattern-probability account and cannot be easily explained by other theories of CFs. IFs were not limited to conjunctions, but rather occurred systematically for several logical connectives. Thus, pattern-based prob... (shrink)

What Do the Data Tell Us? Justification of scientific theories is a three-place relation between data, theories, and background knowledge. Though this should be a commonplace, many methodologies in science neglect it. The article will elucidate the significance and function of our background knowledge in epistemic justification and their consequences for different scientific methodologies. It is argued that there is no simple and at the same time acceptable statistical algorithm that justifies a given theory merely on the basis of certain (...) data. And even if we think to know the probability of a theory, that does not decide whether we should accept it or not. (shrink)

This is a personal, incomplete, and very informal take on the role of logic in general philosophy of science, which is aimed at a broader audience. We defend and advertise the application of logical methods in philosophy of science, starting with the beginnings in the Vienna Circle and ending with some more recent logical developments.