Manuscripts available on request.


Belief Revision

Consensus Does Not Justify Contraction (with Isaac Levi)

Unanimous Consensus against AGM?
[Preprint]{Journal}

Decision Theory

Conditional Choice with a Vacuous Second Tier
[Preprint] [Journal]

Social Choice Theory for Deliberative Democrats


Probability

A Modest Orgulity Argument (with Michael Nielsen)

Another Approach to Consensus and Maximally Informed Opinions with Increasing Evidence (with Michael Nielsen)

Distention: Global Polarization in the Context of Imprecise Probabilities (with Michael Nielsen)

Generalized Superconditioning (with Michael Nielsen)

Learning and Pooling, Pooling and Learning (with Ignacio Ojea Quintana)
[Preprint] [Journal]

Modesty: Opinionation or Regularity? (with Michael Nielsen)

Persistent Disagreement and Polarization in a Bayesian Setting (with Michael Nielsen)

Probabilistic Opinion Pooling with Imprecise Probabilities (with Ignacio Ojea Quintana) 
[Preprint] [Journal]

Dissertation

Mathematical aggregation frameworks are general and precise settings in which to study ways of forming a consensus or group point of view from a set of potentially diverse points of view. Yet the standard frameworks have significant limitations. A number of results show that certain sets of desirable aggregation properties cannot be simultaneously satisfied. Drawing on work in the theory of imprecise probabilities, I propose philosophically-motivated generalizations of the standard aggregation frameworks (for probability, preference, full belief) that I prove can satisfy the desired properties. I then look at some applications and consequences of these proposals in decision theory, epistemology, and the social sciences. 
[Short Abstract] [Extended Abstract]