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Christina Kirk Pikas LBSC 735: Legal Issues in Information Management December 11, 2002

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.

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Christina Kirk Pikas LBSC 735: Legal Issues in Information Management December 11, 2002

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  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

  2. 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

  3. Admission of Expert Evidence • 19th century • Frye (1923) • Federal Rules of Evidence (1975) • Daubert Trilogy • Daubert (1993) • Joiner (1997) • Kumho (1999)

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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

  12. Finally • Daubert provides a useful framework if flexibly employed • Resulting summary judgments save time and money • It’s still easy to lie with statistics

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