I’m thinking of turning to crime

He is a man of good birth and excellent education, endowed by nature with a phenomenal mathematical faculty. At the age of twenty-one he wrote A Treatise on the Binomial…

Disparity is inevitable: a counter argument to filing discrimination lawsuits

Introduction

Know a lawyer who is involved in a discrimination lawsuit? Particularly one in which the plaintiff alleges discrimination because actual disparities are found in company hiring practices? Were you aware that, just by chance, a company can be absolutely innocent of discrimination even though they actually are found to have under-hired a particular group? No? Then read on to find out how.

What are diversity and disparity?

We discussed earlier that there are (at least) two definitions of diversity: one meaning a display of dissimilar and widely varying behaviors, a philosophical position that is untenable and even ridiculous (but strangely widely desired). The second meaning is our topic today.

Diversity of the second type means parity in the following sense. Suppose men and women apply in equal numbers and have identical abilities to perform a certain job. Then suppose that a company institutes a hiring policy that results in 70% women and 30% men. It can be claimed that that company does not properly express diversity, or we might say a disparity in hiring exists. Diversity thus sometimes means obtaining parity.

Disparity is an extraordinarily popular academic topic, incidentally: scores of professors scour data to find disparities and bring them to light. Others—lawyers—notice them and, with EEOC regulations in hand that call such disparities illegal, sue.

And it’s natural, is it not, to get your dudgeon up when you see a statistic like “70% women and 30% men hired”? That has to be the result of discrimination!

Of course, it was in the past routinely true that some companies unfairly discriminated against individuals in matters that had nothing to do with their ability. Race and sex were certainly, and stupidly, among these unnecessarily examined characteristics. Again, it’s true that some companies still exhibit these irrational biases. For example, Hollywood apparently won’t hire anybody over the age of 35 to write screenplays, nor will they employ actors with IQs greater than average.

Sue ’em!

It’s lawsuits that interest us. How unusual is a statistic like “70% women and 30% men hired”? Should a man denied employment at that company sue claiming he was unfairly discriminated against? Would we expect that all companies that do not discriminate would have exactly 50% women and 50% men? This is a topic that starts out easy but gets complicated fast, so let’s take our time. We won’t be able to investigate this topic fully given that it would run to a monograph-length document. But we will be able to sketch an outline of how the problem can be attacked.

Parity depends on several things: the number of categories (men vs. women, black vs. white, black men vs. black women vs. white men vs. white women, etc.; the more subdivisions that are represented, the more categories we have to track), the proportion those categories exist in the applicant population (roughly 51% men, 49% women at job ages in the USA; we only care about the characteristics of those who apply to a job and not their rates in the population), the exact definition of parity, the number of employees the company has, and the number of companies hiring. That last one is the one everybody forgets and is the one that makes disparities inevitable. Let’s see why.

Men vs. Women

Throughout all examples we assume that companies hire blindly, that they have no idea of the category of its applicants, that all applicants and eventual hires are equally skilled; that is, that there is no discrimination in place whatsoever, but also that there is no quota system in place either. All hires are found randomly. Thus, any eventual ratio of observed categories in a company is the result of chance only, and not due to discrimination of any kind (except on ability). This is crucial to remember.

First suppose that there are in our population of applicants 51% men and 49% women.

Now suppose a company hires just one employee. What is the probability that that company will attain parity? Zero. There is (I hope this is obvious) no way the company can hire equal numbers of men and women, even with a quota system in place. Company size, then, strongly determines whether parity is possible.

To see this, suppose the company can hire two employees. What is the probability of parity? Well, what can happen: a man is hired first followed by another man, a man then a woman, a woman then a man, or a woman followed by another woman. The first and last cases represent disparity, so we need to calculate the probability of them occurring by chance. It’s just slightly over 50%.

(Incidentally, we do need to consider cases where men are discriminated against: in the past, we could just focus on cases where women were, but in the modern age of rampant tort lawyers, we have to consider all kinds of disparity lawsuits. For example, the New York Post of 12 May 2009, p. 21, writes of a a self-identified “white, African, American” student from Mozambique who is suing a New Jersey medical school for discrimination.)

Now, if a woman saw that there were two men hired, she might be inclined to sue the company for discrimination, but it’s unlikely. Why? Because most understand that with only two employees, the chance for seeming, or false discrimination is high; that is, disparity resulting by chance is pretty likely (in fact, 50%).

So let’s increase the size of our company to 1000 employees. Exact parity would give us 510 men and 490 women, right? But the probability of exact parity—given random hiring—is only 2.5%! And the larger the company the less it is likely exact parity can be reached.

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