Abstract

The debate between scientific realism and anti-realism remains at a stalemate, with reconciliation seeming hopeless. Yet, there is work to be done in navigating this impasse: to seek a common ground, even if only to isolate deeper points of disagreement. This common ground I propose is founded on the idea that everyone loves some truths, and benefits both sides of the debate. More specifically, many anti-realists, such as instrumentalists, have yet to seriously engage with Sober's call to justify their preferred version of Ockham's razor through a positive epistemology; meanwhile, realists face a similar challenge, lacking a non-circular explanation of how their version of Ockham's razor connects to truth. The common ground I propose helps address these issues for both parties, drawing insights from fields that study scientific inference: statistics and machine learning. The common ground I propose also helps isolate a distinctively epistemic root of the irreconcilability of the realism debate.