Carl F. Cranor, University of California,
Riverside
This paper addresses the admissibility of scientific evidence and expert
opinion testimony into toxic tort suits, using case studies to provide a small
window into some of the issues. A case
study is a detailed report by a physician, or other healthcare provider, of
the profile of single individuals. They
tend to document unusual occurrences and may provide early clues about the
development of a disease or the occurrence of rare events.
Case studies can be merely descriptive or they can be much more
analytical, in which case they can constitute potentially good evidence for
causal relations.
One aim of this paper is to investigate the extent to which case studies can be good evidence for causation in toxic tort cases, something courts have routinely rejected.
First, I argue that good case studies, those that satisfy certain criteria, are quite good evidence of causation in the appropriate toxic tort cases. Case studies in which the author has followed certain procedures in reviewing the evidence presented by a particular case tend to be good evidence for causation. The data for this are what scientists and methodologists in the field judge to be good evidence of causation.
Second, I argue that, since good case studies, based upon a singular events or a small number of events, can reveal causal relations, they also provide important insights into the nature of causal judgments and the reasoning supporting them. In fact good case studies rest on a principle of reasoning quite familiar to philosophers and utilized in many fields—inference to the best explanation—that shows not only why good case studies can support causal judgments, but also one that provides the foundation for many other evidentiary inferences in science and the law.
Finally, once the principle of inference to the best explanation is understood, it becomes clear why several other “causal templates” utilized by judges are inadequate. Courts have created problems for themselves or misconceived a number of problems because they have failed to recognize the significance of inference to the best explanation in coming to causal judgments.