Unsupervised Thinking

In part two of our conversation on what counts as an explanation in science, we pickup with special guest David Barack giving his thoughts on the "model–mechanism–mapping" criteria for explanation. This leads us into a lengthy discussion on explanatory versus phenomenological (or "descriptive") models. We ask if there truly is a distinction between these model classes or if a sufficiently good description will end up being explanatory. We illustrate these points with examples such as the Nernst equation, the Hodgkin-Huxley model of the action potential, and multiple uses of Difference of Gaussians in neuroscience. Throughout, we ask such burning questions as: can a model be explanatory if the people who made it thought it wasn't? are diagrams explanations? and, is gravity descriptive or mechanistic?