Partisan Messages, Unconditional Strategies and Coordination in American Elections I use evolutionary models to study how partisan messages and cuing contribute to—or perhaps substitute for—strategic coordination by voters in American presidential elections. Cuing means imitating another voter’s strategy: a cue tells a voter what to do, not what to think. Using National Election Studies data fr...

There are limited evaluations of the impact of knowledge translation (KT) activities aimed at addressing practice and policy gaps. We report on the impact of an interactive, end-of-grant KT event. Although action items were developed and key stakeholder support attained, minimal follow-through had occurred three months after the KT event. Several organizational obstacles to transitioning knowle...

We present the first differentially private algorithms for reinforcement learning, which apply to the task of evaluating a fixed policy. We establish two approaches for achieving differential privacy, provide a theoretical analysis of the privacy and utility of the two algorithms, and show promising results on simple empirical examples.

In this paper we present a political-agency model in which voters exhibit a cognitive deficiency known as hindsight bias: after the uncertainty about an event is resolved, they consider the realized outcome more foreseeable than it actually was. For their reelection decision, voters evaluate the politician’s ability based on the history of observed actions and outcomes. High ability is defined ...

This paper provides an overview of different approaches to policy evaluation. We focus on how different types of uncertainty should be accounted for in the policy evaluation process. Appropriate incorporation of uncertainty in policy evaluation leads to what we call sturdy decisions. We describe classical Bayesian decision theory and decision theory under ambiguity. We provide examples ranging ...

Health in All Policies (HiAP) has gained attention as a potential tool to address complex health and societal challenges at global, regional, national and subnational levels. In a recent article, Lawless et al propose an evaluation framework developed in the context of the South Australia HiAP initiative. Strategies, mediators, activities and impacts identified in the framework could potentiall...

Off-policy evaluation (OPE) aims to accurately evaluate the performance of counterfactual policies using only offline logged data. Although many estimators have been developed, there is no single estimator that dominates others, because estimators' accuracy can vary greatly depending on a given OPE task such as policy, number actions, and noise level. Thus, data-driven selection problem becomin...