Russell C. Burnett

Learn More
The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian networks. In(More)
a r t i c l e i n f o Decisions, both moral and mundane, about saving individuals or resources at risk are often influenced not only by numbers saved and lost, but also by proportions of groups saved and lost. Consider choosing between a program that saves 60 of 240 lives at risk and one that saves 50 of 100. The first option maximizes absolute number(More)
We investigated how people design interventions to affect the outcomes of causal systems. We propose that the abstract structural properties of a causal system, in addition to people's content and mechanism knowledge, influence decisions about how to intervene. In Experiment 1, participants preferred to intervene at specific locations (immediate causes,(More)
A well-established finding in research on concepts and categories is that some members are rated as better or more typical examples than others. It is generally thought that typicality reflects centrality, that is, that typical examples are those that are similar to many other members of the category. This interpretation of typicality is based on studies in(More)
We investigate how people use causal knowledge to design interventions to affect the outcomes of causal systems. We propose that in addition to using content or mechanism knowledge to evaluate the effectiveness of interventions, people are also influenced by the abstract structural properties of a causal system. In particular, we investigated two factors(More)
  • 1