Online research in philosophy

Elliott Sober argues that the statistical slogan “Absence of evidence is not evidence of absence” cannot be taken literally: it must be interpreted charitably as claiming that the absence of evidence is (typically) not very much evidence of absence. I offer an alternative interpretation, on which the slogan claims that absence of evidence is (typically) not objective evidence of absence. I sketch a definition of objective evidence, founded in the notion of an epistemically objective likelihood, and I show that in Sober’s paradigm case, the slogan can, on this understanding, be sustained.

This paper addresses two examples due to Peter Achinstein purporting to show that the positive relevance view of evidence is too strong, that is, that evidence need not raise the probability of what it is evidence for. The first example can work only if it makes a false assumption. The second example fails because what Achinstein claims is evidence is redundant with information we already have. Without these examples Achinstein is left without motivation for his account of evidence, which uses the concept of explanation in addition to that of probability.

Sherrilyn Roush’s Tracking Truth (2005) is an impressive, precisioncrafted work. Although it sets out to rehabilitate the epistemological theory of Robert Nozick’s Philosophical Explanations (1981), its departures from Nozick’s line are extensive and original enough that it should be regarded as a distinct form of epistemological externalism. Roush’s mission is to develop an externalism that averts the problems and counterexamples encountered not only by Nozick’s theory but by other varieties of externalism as well. Roush advances both a theory of knowledge and a theory of evidence; I focus entirely on knowledge. I shall pinpoint a few respects in which Roush’s theory is not wholly successful. In particular, it works less well than process- (or method-) oriented externalisms like process reliabilism. Nozick’s initial tracking account of knowledge was formulated as follows.

Recently in this journal Sherrilyn Roush (2004) defends positive relevance as a necessary (albeit not a sufficient) condition for evidence by rejecting two of the counterexamples from my earlier (2001) work. In this reply I argue that Roush's critique is not successful.

Sherrilyn Roush defends a new theory of knowledge and evidence, based on the idea of "tracking" the truth, as the best approach to a wide range of questions about knowledge-related phenomena. The theory explains, for example, why scepticism is frustrating, why knowledge is power, and why better evidence makes you more likely to have knowledge. Tracking Truth provides a unification of the concepts of knowledge and evidence, and argues against traditional epistemological realist and anti-realist positions about scientific theories and for a piecemeal approach based on a criterion of evidence, a position Roush calls "real anti-realism." Epistemologists and philosophers of science will recognize this as a significant original contribution.

This paper critically analyzes Sherrilyn Roush’s (Tracking truth: knowledge, evidence and science, 2005) definition of evidence and especially her powerful defence that in the ideal, a claim should be probable to be evidence for anything. We suggest that Roush treats not one sense of ‘evidence’ but three: relevance, leveraging and grounds for knowledge; and that different parts of her argument fare differently with respect to different senses. For relevance, we argue that probable evidence is sufficient but not necessary for Roush’s own two criteria of evidence to be met. With respect to grounds for knowledge, we agree that high probability evidence is indeed ideal for the central reason Roush gives: When believing a hypothesis on the basis of e it is desirable that e be probable. But we maintain that her further argument that Bayesians need probable evidence to warrant the method they recommend for belief revision rests on a mistaken interpretation of Bayesian conditionalization. Moreover, we argue that attempts to reconcile Roush’s arguments with Bayesianism fail. For leveraging, which we agree is a matter of great importance, the requirement that evidence be probable suffices for leveraging to the probability of the hypothesis if either one of Roush’s two criteria for evidence are met. Insisting on both then seems excessive. To finish, we show how evidence, as Roush defines it, can fail to track the hypothesis. This can remedied by adding a requirement that evidence be probable, suggesting another rationale for taking probable evidence as ideal—but only for a grounds-for-knowledge sense of evidence.

Sherrilyn Roush's Tracking Truth provides a sustained and ambitious development of the basic idea that knowledge is true belief that tracks the truth. In this essay, I provide a quick synopsis of Roush's book and offer a substantive discussion of her analysis of scientific evidence. Roush argues that, for e to serve as evidence for h, it should be easier to determine the truth value of e than it is to determine the truth value of h, an ideal she refers to as 'leverage'. She defends a detailed method by which the value of p(h/e) is computed without 'direct' information about p(h) but only using evidence about the value of p(e), from which the value of p(h) is derived. She presents an example of how to use her leverage method, which I argue involves a certain critical mistake. I show how the leveraging method can be used in a way that is sound--I conclude with a few remarks about the importance of distinguishing clearly between prior and posterior probabilities.