Submit work that examines how Hacking’s historical and pragmatic approach to philosophy has reshaped inquiries into psychiatry.

This paper contends with the notion that the methods of machine learning (ML) are unique among the tools of science in enabling a form of theory-free inductive inference. I challenge these assertions of epistemic distinctness, attributing the prevalence of these views to an untenable conception of scientific objectivity: what I term a theory-free ideal, in homage to its normative counterpart. ML, as a formal method of induction, must rely on conceptual or theoretical resources to get inference off the ground. By means of two case studies, I argue that this theory-free ideal has a deleterious effect on the epistemic standing of ML-involving science.

Mary Hesse’s work on the role of analogical reasoning in science has set the disciplinary standard. Her classic Models and Analogies in Science (1966) spearheaded the emergence of the philosophy...

Inferring to the Best Explanation from Uncertain Evidence

Scientific Progress, Astrobiology and the Pursuit of Knowledge