I analyse an empirically informed argument in philosophy of science to show that it faces several varieties of risk commonly discussed as inductive risk. I argue that this is so even though the type of reasoning used in this argument differs from the reasoning in some of the arguments usually discussed in connection with inductive risk. To capture the variety of risks involved, I use the more general notion of epistemic risk proposed by Justin Biddle and Quill Kukla. I show (...) how the argument in question faces several of the epistemic risks already described in connection with empirical reasoning. Importantly, I also argue that the subtype of inductive reasoning used in the argument merits a separate discussion. To analyse it, I recommend using the model of colligation, or reasoning through offering synthesising expressions. I then argue that it is desirable to recognise the risk in colligating inductive reasoning as a distinct type of epistemic risk that is relevant for understanding risk in other fields as well. Thus, I suggest that philosophy of science is one of the fields subject to non-trivial epistemic risk; I characterise several of these risks on the example of a specific argument; and I describe epistemic risk that accompanies colligation – colligating inductive risk. (shrink)

Previously, I (Boesch 2017) described a notion called “representational licensing”—the set of activities of scientific practice by which scientists establish the intended representational use of a vehicle. In this essay, I expand and develop this concept of representational licensing. I begin by showing how the concept is of value for both pragmatic and substantive approaches to scientific representation. Then, through the examination of a case study of the Mississippi River Basin Model, I point out and explain some of the activities (...) of representational licensing that help to establish the representational nature of this model. Throughout the exploration of the case study, I pause to identify some important lessons which apply more generally about the nature of representational licensing in science. (shrink)