Traditional theories construe approximate truth or truthlikeness as a measure of closeness to facts, singular facts, and idealization as an act of either assuming zero of otherwise very small differences from facts or imagining ideal conditions under which scientific laws are either approximately true or will be so when the conditions are relaxed. I first explain the serious but not insurmountable difficulties for the theories of approximation, and then argue that more serious and perhaps insurmountable difficulties for the theory of (...) idealization force us to sever its close tie to approximation. This leads to an appreciation of lawlikeness as a measure of closeness to laws, which I argue is the real measure of idealization whose main purpose is to carve nature at its joints. (shrink)

Representationalists who hold that phenomenal character can be explained in terms of representational content currently cannot explain counter-examples that involve indeterminate perceptual content, such as in the case of objects seen blurrily by someone with poor eyesight, or objects seen vaguely in misty conditions. But this problem can be resolved via provision of a more sophisticated double content (DC) view, according to which the representational content of perception is structured in two nested levels. I start by outlining the DC view (...) via consideration of four closely related cases of perceptual imprecision. Then, after a demonstration that the DC view can also explain imprecise photographic content, inadequacies in the more standard single content (SC) view are demonstrated. The results are then generalized so as to apply to the content of any kinds of non-conventional representation. The paper continues with evidence that a DC account provides a moderate rather than extreme realist account of perception, and it concludes with an initial analysis of the failure of nomic covariance accounts of information in indeterminacy cases. (shrink)

The Scientific Revolution spawned not just one methodology, but two. We have emphasized Bacon's inductivism at the expense of Galileo's more abstract, sophisticated method of successive approximation, and so have failed to appreciate Galileo's contribution to the ceteris paribus problem in philosophy of science. My purpose here is to help redress this imbalance. I first briefly review the old unsolved problems, and then point out the Baconian basis of ceteris paribus, as this clause is conventionally understood, and its history from (...) Aristotle to twentieth century Positivism. Then I explore Galileo's method of dealing with unwanted impediments, and the more general problem of 'accidents.' I trace his methodology back to Archimedes and forward through the economic theories of Adam Smith (18th century), J. S. Mill (19th) and Milton Friedman (20th). Finally, I point out ways in which I think Galileo's scientific method sheds light on, and provides a partial solution to, the ceteris paribus problem. (shrink)

Causal theories of mental content attempt to explain how thoughts can be about things. They attempt to explain how one can think about, for example, dogs. These theories begin with the idea that there are mental representations and that thoughts are meaningful in virtue of a causal connection between a mental representation and some part of the world that is represented. In other words, the point of departure for these theories is that thoughts of dogs are about dogs because dogs (...) cause the mental representations of dogs. (shrink)