The most common example of what statistically discrimination is why there would be more hiring of women as nurses, examples in football
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Statistical discrimination is an economic theory of racial or gender inequality based on stereotypes. According to this theory, inequality may exist and persist between demographic groups even when economic agents (consumers, workers, employers, etc.) are rational and non-prejudiced. This type of preferential treatment is labeled "statistical" because stereotypes may be based on the discriminated group's average behavior.
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The theory posits that in the absence of direct information about a certain fact of ability, a decision maker would substitute group averages. For instance, labor market discrimination may exist because employers don't know with certainty workers' ability, therefore they may resort to basing employment decisions on the workers' visible features, such as group identity, as long as these features correlate with some desirable but more difficult to measure trait. The result is that atypical individuals from the disadvantaged group suffer unfair discrimination.[3] This type of discrimination can result in a self-reinforcing vicious circle over time, as the atypical individuals from the discriminated group are discouraged from participating in the market,[4] or improving their skills as their (average) return on investment (education etc.) is less than for the non-discriminated group.[5]
A related form of (theorized) statistical discrimination is based on group variances, assuming equal averages. For discrimination to occur in this scenario, the decision maker needs to be risk averse; such a decision maker will prefer the group with the lower variance.[6] Even assuming two theoretically identical group distributions (in all respects, including average and variance), a risk averse decision maker will prefer the group for which a measurement (test) exists that minimizes the error term.[6] For example, if two groups, A and B, have theoretically identical distributions of test scores well above the average for the entire population, but group A's estimate is considered more reliable because a large amount of data may be available for group A in comparison to group B, then if two people, one from A and one from B apply for a job, using statistical discrimination, A is hired, because it is perceived that his group score is a more reliable estimate, so a risk-averse decision maker sees group B's group score as more likely to be luck. Conversely, if the two groups are below average, B is hired, because group A's negative score is believed to be a better estimate.
Statistical discrimination is often used and tolerated, for example, when older people are charged more for life insurance, or when a college diploma is required for a job (because it is believed that college graduates perform, on average, better). Some well-documented instances of statistical discrimination for involuntary group membership also do exist and are tolerated. For example, many countries allow auto insurance companies to charge men and women with identical driving records different rates (or factor in gender when deciding whether to deny coverage). The same society may not tolerate statistical discrimination when it is applied to protected groups. For example, it has been suggested that home mortgage lending discrimination against African Americans, which is illegal in the United States, may be partly caused by statistical discrimination.[7]
https://en.wikipedia.org/wiki/Statistical_discrimination_%28economics%29
Sports have well-known examples of this for a long time black quarterbacks out of high school or college were moved to the outsides, backfield, receivers, perceived as speedy and whatever reasoning (false) why they couldn't play. Statistically discrimination is still fairly common in baseball with blacks relegated to outfield positions while the infield positions go elsewhere and I think the number of overall pitchers black/white/other are similar but higher rates of white pitchers are starters while higher averages of black pitchers spend their careers as relief. From they describe this is reinforced from high school to the minor leagues.
Not saying is or isn't racist as far as the association with the toilet example, reminded of statistical discrimination which there are many examples of, but I don't think in her case because she was trying to make a point with Donald Trump who is saying "rapists" or this or that when in reality or around here in Arizona those sort of jobs which there aren't many as Arizona ranks last in job recovery since the "great recession" there would be white people too in janitorial, construction, or anything else but I don't think it would be in inaccurate example to make based on the racism of those that hire the people, promote, appoint whoever. He says "rapists" and I think the point she was attempting to make is rather than "rapists" or the other thing he said that they are just like most of any of us just trying to make it through day-to-day lives working the jobs that are available when they're available but probably wrong to assume to assume the person that cleans his toilet his Hispanic but I don't think she meant that literally.
---This is Arizona
The current selection system excludes broad public input. Maricopa County, with 60.5 percent of the state's population, of which 30 percent, (1,987,987), are of Hispanic/Latino descent, has one Hispanic commissioner. Pima County, with 15 percent of the state's population and 36 percent Hispanic/Latino, has one Hispanic commissioner. Pinal County, with 6 percent of the population and 29 percent Hispanic/Latino, has one Hispanic commissioner. No Hispanics sit as Appellate Court commissioners. The state is 30 percent Hispanic/Latino; Hispanic Commissioners — 4 percent.
http://www.azcentral.com/story/opinion/op-ed/2014/09/23/arizonas-judicial-review-system-fair/16119391/
In a way I think she was attempting to point something like this he is saying this when in she was trying to say in reality it this. She could be working of her own experiences or she very well could be racist. I don't know. Just the example alone doesn't say one way or the other for me.
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