Abstract

Recent literature in the scientific realism debate has been concerned with a particular species of statistical fallacy concerning base-rates, and the worry that no matter how predictively successful our contemporary scientific theories may be, this will tell us absolutely nothing about the likelihood of their truth if our overall sample space contains enough empirically adequate theories that are nevertheless false. In response, both realists and anti-realists have switched their focus from general arguments concerning the reliability and historical track-records of our scientific methodology, to a series of specific arguments and case-studies concerning our reasons to believe individual scientific theories to be true. Such a development however sits in tension with the usual understanding of the scientific realism debate as offering a second-order assessment of our first-order scientific practices, and threatens to undermine the possibility of a distinctive philosophical debate over the approximate truth of our scientific theories. I illustrate this concern with three recent attempts to offer a more localised understanding of the scientific realism debate—due to Stathis Psillos, Juha Saatsi, and Kyle Stanford—and argue that none of these alternatives offer a satisfactory response to the problem.