Catherine Stinson (Ryerson University) gives a talk at the MCMP Colloquium (21 May, 2014) titled "Computational Model as Generic Mechanisms". Abstract: The role of computational models in science is a bit of a puzzle. They seem to be very unlike experiments in terms of their access to empirical facts about their target systems, yet scientists make liberal use of computational models to experiment and make discoveries. I connect this problem to one concerning mechanistic explanation. There a puzzle arises as to how schematic or abstract mechanisms can be explanatory, which they often seem to be, if one is committed to thinking of explanation as intimately connected to causation. Abstractions aren’t the sorts of things that have causal powers. A solution to both problems is to think of computational models not as abstractions, but as bare instantiations of abstract types, which I’ll call generics. Generics are the sorts of things that have causal powers. Computational models can then be considered experiments on generics, which gives them access to empirical facts about those generics. I argue that many common types of experiment can be better understood as experiments on generics, and suggest a shift in how we think of the inferences made in interpreting and applying experimental results.