Because no two human beings are exactly alike, no two groups of human beings are exactly alike either. That’s the consequence of what some call “the snowflake principle” of human life: While we all are alike in some ways, no two of us are quite the same. We have different talents, backgrounds, attitudes, habits, goals, inclinations, beliefs, and friends. Because we do, we experience different outcomes and results, which in turn yield differing socio-economic statistics about us.
That’s another way of saying that statistical disparity does not equal discrimination, the way that so many on the left frequently assert. Differing outcomes can imply many things, discrimination is just one of them. Let me give you four examples:
(1) Let’s say that a major American city has a population that is 80% black. Let’s say as well that its police force is 80% white. (The numbers here are purposely exaggerated in order to underscore the point. No major American city and its police force are so disproportionate). One could not, from those data, conclude that the police force discriminates against minorities in its hiring or promotion practices. If, in urban black culture, the police force is held in low regard, then black youths, whether male or female, will be less likely to want to grow up to be police officers. They will choose other options, however wise or unwise. If, at the same time, in white urban culture, the police force is held in much higher regard, then, predictably, far more white youths will aspire to that career than do their black counterparts. The difference in outcome here is rooted in cultural values, not discrimination. That would be the case even though minority applicants to the police force, and minority applications for promotion within it, actually receive preferential treatment such that a test score for them yields better results than the same score does for whites. Statistical disparity, even radical statistical disparity, does not mean discrimination. It might actually indicate preference.
(2) If, as studies show, educational expectations within the Asian–American subculture tend to emphasize mathematics and the hard sciences, and if, in the African-American subculture, those preferences tend toward the social sciences; and if the hard sciences pay more money than do the social sciences, then it is not a matter either of hiring or payroll discrimination that Asian-Americans with graduate degrees in mathematics and the hard sciences make noticeably more money per year than African-Americans with graduate degrees in the social sciences. Their two cultures’ differing values and expectations dictate the outcome, not discrimination.
(3) If black drug offenders go to jail more often than white drug offenders and serve more time when they do, that statistical difference does not prove discrimination. To prove discrimination, one must ask and answer many other previous questions before deciding the issue. For example, one must take into account things like mandatory sentences and recidivism. If drug usage or drug arrests are less frequent in predominantly white jurisdictions than in black ones, and if judges in those predominantly black jurisdictions are more inclined to render stricter sentences as a result, it does not mean the judge is racially prejudiced. It might mean the judge is quite concerned for public safety and the rule of law, even if, in a nearby jurisdiction, judicial discretion is exercised more leniently. Or if a judge works within a jurisdiction that has mandatory sentencing requirements in such cases, and if the mandatory sentences are harsher than those in other, non-mandatory, jurisdictions just over the state line, and if the offenders here are predominately black, it does not prove racial discrimination. Or if whites are less inclined to be repeat drug offenders (and therefore are more likely to get lighter sentences as a result), it does not prove racial discrimination if their average sentence is lighter than the average sentence of their black counterparts. Racial discrimination is but one of many possible explanations. Statistics alone cannot establish the fact. Things like recidivism need to be considered in the mix. In a system like ours, with multiple jurisdictions, all of which work on varying bases, differences in sentencing inevitably emerge. To label them discrimination is reckless and goes beyond the evidence.
(4) Or, simply because the average salary of women is 60-70% of the average salary of men in the same field (The exact percentage is always changing.), it does not mean that sexual discrimination is the reason. On average, women work fewer hours per day and fewer days per year. They also work fewer total years and take more time off during those years than do men. As a result, they make fewer dollars per hour, week, and year than do men. But when those differences are erased, when women have the same education as their male counterparts, and when they have the same work experience and work record, they actually make 102% of what men make, and have done so for nearly 30 years. Statistical disparity is not proof of discrimination.
Discrimination is easy to assert. Our leftist friends do it all the time. But it is notoriously difficult to prove, and invoking mere statistical disparity does not prove it.
I am not saying something so silly as that there exists no discrimination in America. It does exist, and you might be surprised where to find it.