Discrimination and Employment Law

Pattern of Practice Cases

  • Framework of Pattern of Practice:

    • Differentiates from individual discrimination under McDonnell Douglas.
    • No need to prove individual discrimination for each class member.
    • Use of statistics to demonstrate a standard operating procedure of discrimination.
    • If the defendant fails to rebut claims with convincing evidence of accuracy or significance, plaintiffs receive a presumption of discriminatory practice.

  • Presumption of Discrimination:

    • Each member does not need to prove individual discrimination.
    • Presumption that all members faced discriminatory practices entitling them to damages.

  • Defendant's Rebuttal:

    • Can counter claims by showing non-qualification of individuals or alternate reasons for employment actions.
    • Must bear the burden of proof in rebuttal.

  • Standing in Pattern of Practice Cases:

    • Plaintiffs do not have to have applied to a job to claim membership in the class.
    • Deterred from applying due to known discriminatory practices qualifies them.

Statistical Evidence in Discrimination

  • Hazelwood Case Example:

    • Highlights importance of comparison populations in statistical evidence.
    • Effect of comparing different demographics (e.g., St. Louis County with vs without the city) on outcomes.

  • Importance of Expert Testimony:

    • Laypersons often lack competence to explain statistics to a jury.
    • Expert testimony may fall under rules of evidence as essential for cases involving statistics.

Bona Fide Occupational Qualifications (BFOQs)

  • Definition and Application:
    • Applies to direct intentional discrimination cases.
    • Employers must prove essence of business requires disqualification of a protected class.
    • BFOQs are limited to religion, sex, national origin (not race or color).

After-Acquired Evidence Doctrine

  • National Banner Case:
    • Employers may limit damages if they learn of disqualifying information after employment action.
    • Does not completely erase liability for discrimination; it only limits remedies available.

Rubber Standing Theory (Cat's Paw Theory)

  • Concept:
    • Plaintiff alleges decision was influenced by a subordinate's discriminatory act, even if upper management did not possess discriminatory intent.
    • Must demonstrate proximate causation between the act and the adverse employment decision.

Disparate Treatment vs. Disparate Impact

  • Differences:

    • Individual disparate treatment litigation is more common.
    • Disparate impact concerns facially neutral policies affecting protected classes disproportionately.
    • Intent does not need to be proven in disparate impact cases.

  • McDonnell Douglas Framework:

    • Required to establish a prima facie case in disparate treatment claims.
    • Balances employer discretion with anti-discrimination statutes.

Disparate Impact Analysis

  • Employment Practices and Statistics:

    • Acknowledges that some discriminatory effects may arise from non-intentional policies.
    • Statistical data must show a substantial disparity to indicate disparate impact (referencing the 80% rule).
    • EEOC considers a selection rate of any group less than 80% of the highest selection rate as potential evidence of impact.

  • Examples and Case Law:

    • Duke Power Case established importance of not just proving intention but recognizing broad barriers to employment.
    • Griggs Case emphasized employers' need to justify practices which cause disparate impacts based on job-relatedness and business necessity.

Legislative Changes: Civil Rights Act of 1991

  • Purpose:

    • Clarified disparate impact claims under Title VII.
    • Established framework for plaintiffs to show cause and impact in employment practices leading to discrimination.

  • Key Amendments:

    • Recognized disparate impact as a viable claim in employment discrimination.
    • Provided avenues for proving job-relatedness and business necessity for employment practices.

Conclusion

  • Practical Application:
    • Understanding the differences between testing cases and other policies is crucial for identifying and addressing potential discrimination.
    • Knowledge of statistical requirements and legislative frameworks aids in formulating strong legal arguments.