Joel Pust

Hilary Kornblith (1993) has recently offered a reliabilist defense of the use of the Law of Small Numbers in inductive inference. In this paper I argue that Kornblith's defense of this inferential rule fails for a number of reasons. First, I argue that the sort of inferences that Kornblith seeks to justify are not really inductive inferences based on small samples. Instead, they are knowledge-based deductive inferences. Second, I address Kornblith's attempt to find support in the work of Dorrit Billman and I try to show that close attention to the workings of her computational model reveals that it does not support Kornblith's argument. While the knowledge required to ground the inferences in question is perhaps inductively derived, Billman's work does not support the notion that small samples provide a reliable basis for our generalizing inferences.

Does natural selection explain why individual organisms have the traits that they do? According to "the Negative View," natural selection does not explain why any individual organism has the traits that it does. According to "the Positive View," natural selection at least sometimes does explain why an individual organism has the traits that it does. In this paper, I argue that recent arguments for the Positive View fail in virtue of running afoul of the doctrine of origin essentialism and I demonstrate that other recent defenses of the Negative View depend upon my own for their plausibility.