Class Claims of Disparate Treatment

Author:George Rutherglen
Pages:21
 
FREE EXCERPT

Strictly speaking, the distinction between class claims and individuaclaims is one of procedure rather than substance, concerning how individual claims are joined in a single action instead of the theory oliability that the plaintiff pursues in order to establish a violation. Thstandard procedural form for class claims is either a class action bprivate plaintiffs under Federal Rule of Civil Procedure 23 or a pattern-or-practice action by public officials under statutory authority.

Some of these claims have been litigated as a series of individuaclaims of intentional discrimination, following the structure of prooin McDonnell Douglas. Conversely, a few individual cases have beelitigated by presenting statistical evidence of intentional discrimination or disparate impact.[89] Yet substantive theories of liability havtended to correspond to the procedural forms of action: Individuatheories of liability are mostly to be found in individual actions, anclass-wide theories of liability, relying mainly on statistics or the theory of disparate impact, have been found mostly in class actions anpattern-or-practice actions.

The class claims that most closely resemble individual claims arthose of disparate treatment, since both kinds of claims require prooof intentional discrimination. The means of proving intentional discrimination, however, is very different in class claims of disparattreatment. These claims invariably require evidence in the form oclass-wide statistics, often supplemented by evidence of individuainstances of disparate treatment. Using statistics to prove disparattreatment is similar to using them to prove disparate impact,[90] but thextent of a group's underrepresentation in the employer's workforcmust usually be greater to support an inference of disparate treatmenthan it must be to support an inference of disparate impact.

The variety of statistical evidence poses more immediate choicefor legal doctrine. Judges and juries cannot be left entirely on theiown in evaluating statistical evidence, yet they also must not bhemmed in by simplistic quantitative analysis of statistical evidence.

Some lower court decisions, unfortunately, have confused judiciaanalysis of statistical evidence with formulation of categorical rules olaw. The latter is not appropriate for the former. The Supreme Courhas clearly recognized this point and has refused to offer any definitivmethod of analyzing statistical evidence. In cautioning that statisticaevidence comes in many forms and is always rebuttable, the Court hasaid that the force of such evidence "depends on all of the surroundinfacts and circumstances."[91] The methods the Supreme Court has endorsed are suggestive and instructive, not exhaustive; they should nobe taken to exclude the use of alternative methods of evaluating statistical evidence upon a proper showing. The Supreme Court has offered two models of analysis, and the lower federal courts have endorsed several variations on these models.

The first, and simpler, of the two models of statistical analysis waendorsed by the Supreme Court in International Brotherhood of Teamsters v. United States.[92]

This model of statistical inference-or "the inexorable zero" as it was referred to by the court of appeals-concernextreme disparities in the treatment of workers from different groups.

Teamsters was a "pattern-or-practice" case, so called because the government alleged that the Teamsters Union and various trucking companies had engaged in a systematic practice of denying better payinjobs to blacks and Hispanics. These were "over-the-road" jobs involving driving between major cities, for which the defendants employefew, if any, members of minority groups. Almost all the blacks anHispanics were employed instead as "city drivers" and "servicemen,"

working within a single metropolitan area. Although the opiniocompared the proportion of minority employees in these different positions, the decisive comparison was between the proportion of minority...

To continue reading

FREE SIGN UP