The usual way probability theory is used is that you posit an algebra of events. Each such event has a probability (that is, it is "measurable"). The assumption that the set of events that have a probability is an algebra means that if A and B are both events then "A and B" is also an event (the intersection also has a probability). What happens if you do not make that assumption? In this paper (by Rabanus Derr and Bob Williamson) we provide an answer: you recover the theory of imprecise probability! This builds an intriguing bridge between measure theory and notions from social science such as intersectionality. One conclusion is that measurability should not be construed as a mere technical annoyance; rather, it is a crucial part of how you choose to model the world.