In a recent paper McCain (2012) argues that weak predictivism creates an important challenge for external world scepticism. McCain regards weak predictivism as uncontroversial and assumes the thesis within his argument. There is a sense in which the predictivist literature supports his conviction that weak predictivism is uncontroversial. This absence of controversy, however, is a product of significant plasticity within the thesis, which renders McCain’s argument worryingly vague. For McCain’s argument to work he either needs a stronger version of weak (...) predictivism than has been defended within the literature, or must commit to a more precise formulation of the thesis and argue that weak predictivism, so understood, creates the challenge to scepticism that he hopes to achieve. The difficulty with the former is that weak predictivism is not uncontroversial in the respect that McCain’s argument would require. I consider the prospects of saving McCain’s argument by committing to a particular version of weak predictivism, but find them unpromising for several reasons. (shrink)
The judgment that a given event is epistemically improbable is necessary but insufficient for us to conclude that the event is surprising. Paul Horwich has argued that surprising events are, in addition, more probable given alternative background assumptions that are not themselves extremely improbable. I argue that Horwich’s definition fails to capture important features of surprises and offer an alternative definition that accords better with intuition. An important application of Horwich’s analysis has arisen in discussions of fine-tuning arguments. In the (...) second part of the paper I consider the implications for this argument of employing my definition of surprise. I argue that advocates of fine-tuning arguments are not justified in attaching significance to the fact that we are surprised by examples of fine-tuning. (shrink)
This document collects discussion and commentary on issues raised in the workshop by its participants. Contributors are: Greg Frost-Arnold, David Harker, P. D. Magnus, John Manchak, John D. Norton , J. Brian Pitts, Kyle Stanford, Dana Tulodziecki.
Scientific theories are developed in response to a certain set of phenomena and subsequently evaluated, at least partially, in terms of the quality of fit between those same theories and appropriately distinctive phenomena. To differentiate between these two stages it is popular to describe the former as involving the accommodation of data and the latter as involving the prediction of data. Predictivism is the view that, ceteris paribus, correctly predicting data confers greater confirmation than successfully accommodating data. In this paper, (...) I take issue with a variety of predictivist theses, argue that their role for issues of confirmation is extremely limited, and attempt to account for the appeal that predictivism has enjoyed. Introduction Temporal Predictivism Heuristic Predictivism Weak Predictivism 4.1 Inference to better theories 4.2 Inference to better methods Arguments for Strong Heuristic Predictivism 5.1 Best explanations argument 5.2 Conditional support 5.3 Unique explanations Increased Explanatory Unification 6.1 Explaining what other theories can't 6.2 Contrived hypotheses 6.2 Strength and simplicity Conclusions CiteULike Connotea Del.icio.us What's this? (shrink)
A not unpopular thesis, when it comes to the confirmation of scientific theories, is that data which were used in the construction of a theory afford poorer support for that theory than data that played no role. Some compelling thought experiments have been offered in favour of this view, not as proof but rather to add some intuitive plausibility. In this paper I consider such thought experiments and argue that they do not support the thesis; the perceived importance of prediction (...) over accommodation, at least in these cases, is illusory. Introduction Background assumptions Strong thesis Weak thesis Conclusions. (shrink)