Katrina (Katie) Elliott


I am an assistant professor of philosophy at UCLA, where I teach philosophy of science and metaphysics and work on chance, explanation, and prediction. 

The Department of Philosophy
University of California, Los Angeles
Box 951451, Dodd 321
Los Angeles, CA 90095


Research Summary 

Explaining (One Aspect of) the Principal Principle without (Much) Metaphysics. Philosophy of Science 83, no. 4 (October 2016): 480-499 

Exploring a New Argument for Synchronic Chance.  Philosopher’s Imprint 18

How to Know that Time Travel is Unlikely without Knowing Why.  Pacific Philosophical Quarterly, September 2018

In progress:

Scientific Explanation:  Still a Headache for Humeans (updated draft coming soon…)
Inferece to the Best Theory:  (updated draft coming soon…)
Two Explanatory Questions

When an event occurs by chance, there are at least two distinct questions that arise: (1) why did the event occur? and (2) why was the event’s chance of occurring equal to n? (where “n” is a particular real number along the unit interval). I argue that many influential discussions of indeterministic explanation confuse these two questions by mistaking plausible answers to question (2) for plausible answers to question (1). As a result, the current literature offers very few credible theories about how best to answer question (1); I suggest that, when an event occurs by chance, it is the chance of that outcome that explains its occurrence.

Chance Explanation: 

Chance is a kind of predictive choke point between the present and the future; there is a great deal of evidence that one might presently have about whether a particular event will occur in the future, but the event’s present chance of occurring is at least as good grounds for one’s expectations about whether the event occurs in the future as is (nearly) all of that other evidence. I offer a novel explanation of this aspect of chance’s predictive role. On my view, chance is a predictive chokepoint because chance is also an explanatory chokepoint: the present chances explain future occurrences, while the present conditions, causes, and natural laws help to explain the present chances.

Where are the Chances?:

Not all probability ascriptions that appear in scientific theories describe chances. There is a question about whether probability ascriptions in non-fundamental sciences, such as those found in evolutionary biology and statistical mechanics, describe chances in deterministic worlds and about whether there could be any chances in deterministic worlds. Recent debate over whether chance is compatible with determinism has unearthed two strategies for arguing about whether a probability ascription describes chance—that is, to speak metaphorically, two different strategies for figuring out where the chances are: find the chances by focusing on chance’s explanatory role or find the chances by focusing on chance’s predictive role. These two strategies tend to yield conflicting results about where the chances are, and debate over which strategy is appropriate tends to end in stalemate. After discussing these two strategies, I consider a new view of chance’s explanatory role. I argue that one theoretical advantage of this new view is that allows us to make progress on the question of where the chances are by providing a principled way of determining which probability ascriptions describe chances. From the vantage of this new view, the correct application of both strategies involves figuring out where the chances are by figuring out where the probabilistic scientific explanations are and what those explanations are like.

I am from Kansas.

                                                                I own a dog.