Dr. Palmer Morrel-Samuels is a
Research Psychologist with extensive training and experience in
Statistical Analysis and
Assessment Design. He has done a considerable amount of research and applied work on communication, testified to the U.S. congress on employee motivation and its linkage to objective performance metrics, published several articles on survey design in Harvard Business Review, among others, and wrote several patents to assist in the administration and analysis of workplace assessments. Dr. Morrel-Samuels currently teaches graduate courses on survey design and research methodology at the University of Michigan.
Litigation Services: Dr. Morrel-Samuels' education, practical experience, and distinguished authorship have made him a valuable resource for providing expert services in legal cases where workplace surveys or assessments are at issue, including:
- Statistical analysis of very large datasets, measuring the impact of corporate culture on performance and race discrimination.
- Analysis of a survey's validity, reliability, objectivity, fairness, accuracy, confidentiality, freedom from response bias, and conformance to The Uniform Guidelines pertaining to all workplace assessments.
- Statistical analyses of performance-related and survey-related data.
- Desiging and conducting employee and workplace surveys, including Electronic surveys.
- Disparate Impact & Disparate Treatment litigation.
- Careful job analysis using court-approved methodology in FLSA litigation.
- Performance appraisals, job evaluations, skill assessments.
- Program evaluations, especially when used in hiring, firing, or other job actions.
Expert Witness Experience, includes: Assisted the NAACP in its amicus brief for the Ricci discrimination case. Was the sole statistician in a successful $100M breach of contract case (Tower Automotive v. UNOVA) that required analyzing 4 million rows of data. Testified for the ICC’s International Court of Arbitration in The Hague. Has successfully withstood Daubert challenges - most recently from the City of Indianapolis in a large discrimination case
Clarifying the Distinction between Reverse Discrimination and Overcorrection; Two Informative Examples
We distinguish between reverse discrimination and over-correction, arguing that the former should be used only to describe cases where well-qualified non-minority applicants are unjustifiably denied positions in organizations run by and/or staffed by minorities. Similarly, we argue over-correction should be used to describe well-qualified non-minority applicants who are unjustifiably denied positions in organizations run by non-minorities.
