Jul 6 JDN 2460863
There are a lot of stereotypes in the world, from the relatively innocuous (“teenagers are rebellious”) to the extremely harmful (“Black people are criminals”).
Most stereotypes are not true.
But most stereotypes are not exactly false, either.
Here’s a list of forty stereotypes, all but one of which I got from this list of stereotypes:
(Can you guess which one? I’ll give you a hint: It’s a group I belong to and a stereotype I’ve experienced firsthand.)
- “Children are always noisy and misbehaving.”
- “Kids can’t understand complex concepts.”
- “Children are tech-savvy.”
- “Teenagers are always rebellious.”
- “Teenagers are addicted to social media.”
- “Adolescents are irresponsible and careless.”
- “Adults are always busy and stressed.”
- “Adults are responsible.”
- “Adults are not adept at using modern technologies.”
- “Elderly individuals are always grumpy.”
- “Old people can’t learn new skills, especially related to technology.”
- “The elderly are always frail and dependent on others.”
- “Women are emotionally more expressive and sensitive than men.”
- “Females are not as good at math or science as males.”
- “Women are nurturing, caring, and focused on family and home.”
- “Females are not as assertive or competitive as men.”
- “Men do not cry or express emotions openly.”
- “Males are inherently better at physical activities and sports.”
- “Men are strong, independent, and the primary breadwinners.”
- “Males are not as good at multitasking as females.”
- “African Americans are good at sports.”
- “African Americans are inherently aggressive or violent.”
- “Black individuals have a natural talent for music and dance.”
- “Asians are highly intelligent, especially in math and science.”
- “Asian individuals are inherently submissive or docile.”
- “Asians know martial arts.”
- “Latinos are uneducated.”
- “Hispanic individuals are undocumented immigrants.”
- “Latinos are inherently passionate and hot-tempered.”
- “Middle Easterners are terrorists.”
- “Middle Eastern women are oppressed.”
- “Middle Eastern individuals are inherently violent or aggressive.”
- “White people are privileged and unacquainted with hardship.”
- “White people are racist.”
- “White individuals lack rhythm in music or dance.”
- “Gay men are excessively flamboyant.”
- “Gay men have lisps.”
- “Lesbians are masculine.”
- “Bisexuals are promiscuous.”
- “Trans people get gender-reassignment surgery.”
If you view the above 40 statements as absolute statements about everyone in the category (the first-order operator “for all”), they are obviously false; there are clear counter-examples to every single one. If you view them as merely saying that there are examples of each (the first-order operator “there exists”), they are obviously true, but also utterly trivial, as you could just as easily find examples from other groups.
But I think there’s a third way to read them, which may be more what most people actually have in mind. Indeed, it kinda seems uncharitable not to read them this third way.
That way is:
“This is more true of the group I’m talking about than it is true of other groups.”
And that is not only a claim that can be true, it is a claim that can be quantified.
Recall my new favorite effect size measure, because it’s so simple and intuitive; I’m not much for the official name probability of superiority (especially in this context!), so I’m gonna call it the more down-to-earth chance of being higher.
It is exactly what it sounds like: If you compare a quantity X between group A and group B, what is the chance that the person in group A has a higher value of X?
Let’s start at the top: If you take one randomly-selected child, and one randomly-selected adult, what is the chance that the child is one who is more prone to being noisy and misbehaving?
Probably pretty high.
Or let’s take number 13: If you take one randomly-selected woman and one randomly-selected man, what is the chance that the woman is the more emotionally expressive one?
Definitely more than half.
Or how about number 27: If you take one randomly-selected Latino and one randomly-selected non-Latino (especially if you choose a White or Asian person), what is the chance that the Latino is the less-educated one?
That one I can do fairly precisely: Since 95% of White Americans have completed high school but only 75% of Latino Americans have, while 28% of Whites have a bachelor’s degree and only 21% of Latinos do, the probability of the White person being at least as educated as the Latino person is about 82%.
I don’t know the exact figures for all of these, and I didn’t want to spend all day researching 40 different stereotypes, but I am quite prepared to believe that at least all of the following exhibit a chance of being higher that is over 50%:
1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 17, 18, 19, 21, 24, 26, 27, 28, 29, 30, 31, 33, 34, 36, 37, 38, 40.
You may have noticed that that’s… most of them. I had to shrink the font a little to fit them all on one line.
I think 30 is an important one to mention, because while terrorists are a tiny proportion of the Middle Eastern population, they are in fact a much larger proportion of that population than they are of most other populations, and it doesn’t take that many terrorists to make a place dangerous. The Middle East is objectively a more dangerous place for terrorism than most other places, and only India and sub-Saharan Africa close (and both of which are also largely driven by Islamist terrorism). So while it’s bigoted to assume that any given Muslim or Middle Easterner is a terrorist, it is an objective fact that a disproportionate share of terrorists are Middle Eastern Muslims. Part of what I’m trying to do here is get people to more clearly distinguish between those two concepts, because one is true and the other is very, very false.
40 also deserves particular note, because the chance of being higher is almost certainly very close to 100%. While most trans people don’t get gender-reassignment surgery, virtually all people who get gender-reassignment surgery are trans.
Then again, you could see this as a limitation of the measure, since we might expect a 100% score to mean “it’s true of everyone in the group”, when here it simply means “if we ask people whether they have had gender-reassignment surgery, the trans people sometimes say yes and the cis people always say no.”
We could talk about a weak or strict chance of being higher: The weak chance is the chance of being greater than or equal to (which is the normal measure), while the strict chance is the chance of being strictly greater. In this case, the weak chance is nearly 100%, while the strict chance is hard to estimate but probably about 33% based on surveys.
This doesn’t mean that all stereotypes have some validity.
There are some stereotypes here, including a few pretty harmful ones, for which I’m not sure how the statistics would actually shake out:
10, 14, 22, 23, 25, 32, 35, 39
But I think we should be honestly prepared for the possibility that maybe there is some statistical validity to some of these stereotypes too, and instead of simply dismissing the stereotypes as false—or even bigoted—we should instead be trying to determine how true they are, and also look at why they might have some truth to them.
My proposal is to use the chance of being higher as a measure of the truth of a stereotype.
A stereotype is completely true if it has a chance of being higher of 100%.
It is completely false if it has a chance of being higher of 50%.
And it is completely backwards if it has a chance of being higher of 0%.
There is a unique affine transformation that does this: 2X-1.
100% maps to 100%, 50% maps to 0%, and 0% maps to -100%.
With discrete outcomes, the difference between weak and strong chance of being higher becomes very important. With a discrete outcome, you can have a 100% weak chance but a 1% strong chance, and honestly I’m really not sure whether we should say that stereotype is true or not.
For example, for the claim “trans men get bottom surgery”, the figures would be 100% and 6% respectively. The vast majority of trans men don’t get bottom surgery—but cis men almost never do. (Unless I count penis enlargement surgery? Then the numbers might be closer than you’d think, at least in the US where the vast majority of such surgery is performed.)
And for the claim “Middle Eastern Muslims are terrorists”, well, given two random people of whatever ethnicity or religion, they’re almost certainly not terrorists—but if it one of them is, it’s probably the Middle Eastern Muslim. It may be better in this case to talk about the conditional chance of being higher: If you have two random people, you know that one is a terrorist and one isn’t, and one is a Middle Eastern Muslim and one isn’t, how likely is it that the Middle Eastern Muslim is the terrorist? Probably about 80%. Definitely more than 50%, but also not 100%. So that’s the sense in which the stereotype has some validity. It’s still the case that 99.999% of Middle Eastern Muslims aren’t terrorists, and so it remains bigoted to treat every Middle Eastern Muslim you meet like a terrorist.
We could also work harder to more clearly distinguish between “Middle Easterners are terrorists” and “terrorists are Middle Easterners”; the former is really not true (99.999% are not), but the latter kinda is (the plurality of the world’s terrorists are in the Middle East).
Alternatively, for discrete traits we could just report all four probabilities, which would be something like this: 99.999% of Middle Eastern Muslims are not terrorists, and 0.001% are; 99.9998% of other Americans are not terrorists, and 0.0002% are. Compared to Muslim terrorists in the US, White terrorists actually are responsible for more attacks and a similar number of deaths, but largely because there just are a lot more White people in America.
These issues mainly arise when a trait is discrete. When the trait is itself quantitative (like rebelliousness, or math test scores), this is less of a problem, and the weak and strong chances of being higher are generally more or less the same.
So instead of asking whether a stereotype is true, we could ask: How true is it?
Using measures like this, we will find that some stereotypes probably have quite high truth levels, like 1 and 4; but others, if they are true at all, must have quite low truth levels, like 14; if there’s a difference, it’s a small difference!
The lower a stereotype’s truth level, the less useful it is; indeed, by this measure, it directly predicts how accurate you’d be at guessing someone’s score on the trait if you knew only the group they belong to. If you couldn’t really predict, then why are you using the stereotype? Get rid of it.
Moreover, some stereotypes are clearly more harmful than others.
Even if it is statistically valid to say that Black people are more likely to commit crimes in the US than White people (it is), the kind of person who goes around saying “Black people are criminals” is (1) smearing all Black people with the behavior of a minority of them, and (2) likely to be racist in other ways. So we have good reason to be suspect of people who say such things, even if there may be a statistical kernel of truth to their claims.
But we might still want to be a little more charitable, a little more forgiving, when people express stereotypes. They may make what sounds like a blanket absolute “for all” statement, but actually intend something much milder—something that might actually be true. They might not clearly grasp the distinction between “Middle Easterners are terrorists” and “terrorists are Middle Easterners”, and instead of denouncing them as a bigot immediately, you could try taking the time to listen to what they are saying and carefully explain what’s wrong with it.
Failing to be charitable like this—as we so often do—often feels to people like we are dismissing their lived experience. All the terrorists they can think of were Middle Eastern! All of the folks they know with a lisp turned out to be gay! Lived experience is ultimately anecdotal, but it still has a powerful effect on how people think (too powerful—see also availability heuristic), and it’s really not surprising that people would feel we are treating them unjustly if we immediately accuse them of bigotry simply for stating things that, based on their own experience, seem to be true.
I think there’s another harm here as well, which is that we damage our own credibility. If I believe that something is true and you tell me that I’m a bad person for believing it, that doesn’t make me not believe it—it makes me not trust you. You’ve presented yourself as the sort of person who wants to cover up the truth when it doesn’t fit your narrative. If you wanted to actually convince me that my belief is wrong, you could present evidence that might do that. (To be fair, this doesn’t always work; but sometimes it does!) But if you just jump straight to attacking my character, I don’t want to talk to you anymore.