Ben Blumson

It’s a platitude that a picture is realistic to the degree to which it resembles what it represents (in relevant respects). But if properties are abundant and degrees of resemblance are proportions of properties in common, then the degree of resemblance between different particulars is constant (or undefined), which is inconsonant with the platitude. This paper argues this problem should be resolved by revising the analysis of degrees of resemblance in terms of proportion of properties in common, and not by accepting a sparse theory of properties or by denying that degree of realism is degree of resemblance (in relevant respects).

Traditionally, the structure of a language is revealed by constructing an appropriate theory of meaning for that language, which exhibits how – and whether – the meaning of sentences in the language depends upon the meaning of their parts. In this paper, I argue that whether – and how – what pictures represent depends on what their parts represent should likewise by revealed by the construction of appropriate theories of representation for the symbol system of those pictures. This generalisation, I argue, reveals a much cited disanalogy between depiction and description is illusory: the structure of pictures, like language, is compositional.

In this paper I argue that the analysis of natural properties as convex subsets of a metric space in which the distances are degrees of dissimilarity is incompatible with both the definition of degree of dissimilarity as number of natural properties not in common and the definition of degree of dissimilarity as proportion of natural properties not in common, since in combination with either of these definitions it entails that every property is a natural property, which is absurd. I suggest it follows that we should think of the convex class analysis of natural properties as a variety of resemblance nominalism.

This paper considers whether an analogy between distance and dissimilarlity supports the thesis that degree of dissimilarity is distance in a metric space. A straightforward way to justify the thesis would be to define degree of dissimilarity as a function of number of properties in common and not in common. But, infamously, this approach has problems with infinity. An alternative approach would be to prove representation and uniqueness theorems, according to which if comparative dissimilarity meets certain qualitative conditions, then it is representable by distance in a metric space. I will argue that this approach faces equally severe problems with infinity.