Fleeing from the Nazi regime, along with many German refugees, Hans Reichenbach came to teach at Istanbul University in 1933, accepting the invitation of the Turkish government and stayed in Istanbul until 1938. While much is known about his work and life in Istanbul, the existing literature relies mostly on his letters and works. In this article I try to shed more light on Reichenbach’s scholarly activities and personal life by also taking into account the Turkish sources and the academic (...) context in which Reichenbach taught and worked. (shrink)
This paper argues against Papineau's claim that causal relations can be reduced to correlations and defends Cartwright's thesis that they can be nevertheless boot-strapped from them, given sufficiently rich causal background knowledge.
We compare Carnap's and Kuhn's views on science. Although there are important differences between them, the similarities are striking. The basis for the latter is a pragmatically oriented semantic conventionalist picture of science, which suggests that the view that post-positivist philosophy of science constitutes a radical revolution which has no interesting affinities with logical positivism must be seriously mistaken.
I argue that Nancy Cartwright's largely methodological arguments for capacities and against Hume's regularity account of causation are only partially successful. They are especially problematic in establishing the primacy of singular causation and the reality of mixed-dual capacities. Therefore, her arguments need to be supported by ontological ones, and I propose the propensity interpretation of causal probabilities as a natural way of doing this.
Humean accounts of law are at the same time accounts of causation. Accordingly, since laws are nothing but contingent cosmic regularities, to be a cause is just to be an instance of such a law. Every particular cause-effect pair, according to these accounts, instantiates some law of nature. I argue that this claim is false. Singular causation without being governed by any law is logically and physically possible. Separating causes from laws enables us to see the distinct role each plays (...) in science, especially in matters related to prediction and explanation. (shrink)
Causal modeling methods such as path analysis, used in the social and natural sciences, are also highly relevant to philosophical problems of probabilistic causation and statistical explanation. We show how these methods can be effectively used (1) to improve and extend Salmon's S-R basis for statistical explanation, and (2) to repair Cartwright's resolution of Simpson's paradox, clarifying the relationship between statistical and causal claims.
Recent philosophical studies of probabilistic causation and statistical explanation have opened up the possibility of unifying philosophical approaches with causal modeling as practiced in the social and biological sciences. This unification rests upon the statistical tools employed, the principle of common cause, the irreducibility of causation to statistics, and the idea of causal process as a suitable framework for understanding causal relationships. These four areas of contact are discussed with emphasis on the relevant aspects of causal modeling.
Although there is universal consensus both in the science education literature and in the science standards documents to the effect that students should learn not only the content of science but also its nature, there is little agreement about what that nature is. This led many science educators to adopt what is sometimes called “the consensus view” about the nature of science (NOS), whose goal is to teach students only those characteristics of science on which there is wide consensus. This (...) is an attractive view, but it has some shortcomings and weaknesses. In this article we present and defend an alternative approach based on the notion of family resemblance. We argue that the family resemblance approach is superior to the consensus view in several ways, which we discuss in some detail. (shrink)
