"There's a 70% chance of rain tomorrow," says the weather app on your phone. "There’s a 30% chance my flight will be delayed," posts a colleague on Slack. Scientific theories also include chances: “There’s a 50% chance of observing an electron with spin up,” or (less fundamental) “This is a fair die — the probability of it landing on 2 is one in six.” We constantly talk about chances and probabilities, treating them as features of the world that we can discover and disagree about. And it seems you can be objectively wrong about the chances. The probability of a fair die landing on 2 REALLY is one in six, it seems, even if everybody in the world thought otherwise. But what exactly are these things called “chances”? Readers on LessWrong are very familiar with the idea that many probabilities are best thought of as subjective degrees of belief. This idea comes from a few core people, including Bruno de Finetti. For de Finetti, probability was in the map, not the territory. But perhaps this doesn’t capture how we talk about chance. For example, our degrees of belief need not equal the chances, if we are uncertain about the chances. But then what are these chances themselves? If we are uncertain about the bias of a coin, or the true underlying distribution in some environment, then we can use our uncertainty over those chances to generate our subjective probabilities over what we’ll observe.[1] But then we have these other probabilities — chances, distributions, propensities, etc. — to which we are assigning probabilities. What are these things? Here we’ll show how we can keep everything useful about chance-based reasoning while dropping some problematic metaphysical assumptions. The key insight comes from work by, once again, de Finetti. De Finetti’s approach has been fleshed out in detail by Brian Skyrms. We’ll take a broadly Skyrmsian perspective here, in particular as given in his book Pragmatics and Empiricism. The core upshot is that we don't need to believe i