Transcript Slide 1
Two Faces of Causality: A Small Case Study of the Admission of Scientific Evidence to Show Causality in a Bias and a Toxic Tort Case in the 4th Circuit Christina Kirk Pikas LBSC 735: Legal Issues in Information Management December 11, 2002 Overview Review of the efforts made to form the admissibility of scientific evidence Discussion of causality and the scientific and the statistical methods used to prove Case studies of two cases: Product liability Pay discrimination Admission of Expert Evidence 19th century Frye (1923) Federal Rules of Evidence (1975) Daubert Trilogy Daubert (1993) Joiner (1997) Kumho (1999) Causality Definition: “The principle of causal relationship; the relation between cause and effect” (Black’s Law Dictionary) Cause: “To bring about or effect” (Black’s Law Dictionary) Correlation, association, or statistically significant relationship is not enough Primary issue in Toxic torts Product liability Discrimination General vs. Specific Causality General (examples: toxicology, epidemiology) anecdotal evidence observational studies controlled experiments Specific Treating Doctor Series of specific details such as •Temporal relationship •Strength and specificity of association •Dose-response relationship •Consistent with other knowledge •Biological plausibility •Consideration of alternate hypotheses •Cessation of exposure Case 1: Nettles v. Proctor & Gamble Ms. Nettles used Vicks Sinex Nasal Spray and later became blind A neuro-opthalmologist was produced to give evidence on her case No studies existed linking the main ingredient to her condition Only temporal connection was found As per Joiner – court did was neither arbitrary or capricious, decision was affirmed Case 2: Smith, et al v. Virginia Commonwealth University VCU employed a committee to determine if there was a discrepancy in pay between male and female tenure and tenure-track professors The committee used a multiple regression analysis and determined that there was a $1,300 difference. Another committee was started to review CVs and give deserving female employees appropriate raises. Case 2: continued Plaintiffs Allege Not fair because raises based only on gender Inflated pool – more males had been administrators and therefore had higher pay Analysis not valid because did not take into account major factors relating to pay, namely performance Trial Court Proxies were sufficient, regression study valid, pay handed out fairly, to correct inequity Summary Judgment awarded to VCU Case 2: Continued Appeals Court Regression did not take into account performance factors, not invalid, but probative value in question If material issues exist, should not have been a Summary Judgment, reversed. Analysis If the lower court had employed Daubert factors, the summary judgment was correct The initial study was invalid – it poorly fit the real situation under study Conclusion Complexity of new cases, commingling of evidence, junk science make the gatekeeper role very important Judges see expert evidence 90 days before trial Many courses, books, and studies exists to help train judges Judges can appoint neutral experts to help interpret the evidence More Conclusions Scientific methods and statistics are being used for purposes for which they were not designed Statistics don’t prove anything – give relative probability Toxicology and epidemiology – give relative risk Statistical significance and practical significance are not the same Finally Daubert provides a useful framework if flexibly employed Resulting summary judgments save time and money It’s still easy to lie with statistics