| Averages from various populations have long been accepted as a means for prediction – life expectancy,
earnings, and others. No statistic, no matter how fine-tuned, can provide an exact predictor of an
individual’s future. This is as true of worklife expectancies as it is of various
measures of annual earnings and growth and discount rates.
The expert must use available statistics about populations and mold
them to meet the specifics of the case. As
noted by Marcia Angell in Science on Trial (1997, p. 115): Courtroom trials are not about populations, they are about individuals. . . . We
have no basis, at least in the current state of knowledge, for making a
judgment about a particular woman. We
therefore must appeal to epidemiological data – that is, studies
of populations.
The United States Supreme Court recognized this uncertainty several years ago, in their decision
in Jones and Laughlin Steel Corporation v.
Howard E. Pfeifer 462 U.S. 523 (1983):By its very nature the calculation of an award for lost earnings must be a
rough approximation. Because the lost stream can never be predicted with complete confidence, any lump
sum represents only a “rough and ready” effort to put the plaintiff in
the position he would have been in had he not been injured.
Economists, actuaries, insurance
companies, and gambling establishments use population averages when making
rational bets on human outcomes. The
basic belief is that in the absence of more specific and precise
information, the best predictors of outcomes are statistical averages or
relative frequencies. Following
this, it is not true that disability data would have to be disaggregated
by type, severity, or duration of disability in order to be reliable or
meaningful. Even if segregated data existed, its use would be limited at best. Persons
with the same diagnosis and the same length of time since injury can have
dramatically different experiences in terms of their experience in the
workplace, especially when education level is factored in.
Consider an example of two men with identical hand injuries
resulting in reduced grip strength and limited range of motion.
This injury would have an enormous impact on a carpenter, who
would likely need to leave his employment.
For an English professor, however, the effect may be minimal.
What the criticism does point to,
however, is the fact that statistics of all sorts must be used responsibly
and applied by persons familiar with issues involved. When assessing
persons with disability, for instance, the user must be familiar with the
effects of impairment on ability to work and earn money as well as the
experiences of persons with disability in the labor market. |
