Eric Barnes’ The Paradox of Predictivism is concerned primarily with two facts: predictivism (the fact that novel predictions play an important part in scientificconfirmation) and pluralism (the fact that scientific development is not just a matter of isolated individuals judging the truth, but at least partly a matter of trusting legitimate experts). In the middle part of the book, he peers through these two lenses at the tired realist scarecrow of the no-miracles argument. He attempts to reanimate this (...) weatherworn realist argument, contra suggestions by people like me that it should be abandoned. In this paper, I want to get clear on Barnes’ contribution to the debate. He focuses on what he calls the miraculous endorsement argument, which explains not the success of a specific theory but instead the history of successes for an entire research program. The history of successes is explained by reliable and improving methods, which are the flipside of approximately true background theories. Yet, as Barnes notes, the whole story must begin with methods that are at least minimally reliable. Barnes demands that the realist explain the origin of the minimally reliable take-off point, and he suggests a way that the realist might do so. I contend that his explanation still relies on contingent developments and so fails to completely explain the development of take-off theories. However, this line of argument digs into familiar details of the no-miracles argument and overlooks what’s new in Barnes’ approach. By calling attention to pluralism, he reminds us that we need an account of scientific expertise. This is important, I suggest, because expertise is not indefinite. We do not trust specific experts for everything, but only for things within the bounds of their expertise. Drawing these boundaries relies on our own background theories and is only likely to be reliable if our background theories are approximately true. I argue, then, that pluralism gives us reason to be realists (about some things). (shrink)

We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. Some say (...) that pre-analysis plans are epistemically meritorious while others deny this, and in practice pre-analysis plans are often violated. We resolve this debate with a modest defence of pre-analysis plans. Further, we argue that pre-analysis plans can be epistemically relevant even if the plan is not strictly followed—and suggest that allowing for flexible pre-analysis plans may be the best available policy option. (shrink)

There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential contexts , (...) we can see that neither weak nor strong predictivism captures all of the reasons for valuing prediction available. A third path is presented, Pluralist Instrumental Predictivism; PIP for short. (shrink)

Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role of orthodox (...) economic theory. Second, a conditional predictivism: if we are not committed to orthodox economic theory, then we should demand prediction rather than accommodation – against most current practice. (shrink)