Say a person wants to make a decision by relying on a generalization that "Children reared by single parents are more likely to be involved in criminal activity. It's quite another to say we should ignore an accurate generalization just because there are exceptions to it. The real question is: What makes some uses of stereotypes inappropriate and others appropriate? Age requirements. Most accept that a person should be a certain age to vote or drive a car.
Neither is based on universally valid generalizations: Some year-olds shouldn't be voting and some year-olds would be competent to do so. Some year-olds could reasonably drive a car. Nor is individual testing always a workable solution to such problems. Testing is expensive and not without its own errors and abuses. Imagine the controversies that would attend any individualized test for voter competence. Answers appear at the bottom of this paragraph. If you got at least one right, you now have your own personal evidence that not all stereotypes are necessarily wrong.
If you got three or more right, congratulations — your stereotypes assessed here were quite accurate. Lots of people hold stereotypes about as accurate as yours. Why is that? Combating oppression is a good thing, and oppressors exploit stereotypes, so stereotypes are seen as bad. Thus, any evaluation of the validity of your claim is short-circuited by the peremptory dismissal.
Still, high moral purpose or lack of it does not translate to scientific truth or its absence. We do not usually presume people making other generalisations — say, about the weather in Madrid or the taste of oranges — are doing something bad and inaccurate. Despite this point, the notion of generalisations about people as inherently bad and inaccurate has long been baked into the science without any proof.
It is almost impossible to conduct social scientific research on stereotypes without running into the scholarly emphasis on their inaccuracy. When I first began my research, I had assumed all those social scientists declaring stereotypes to be inaccurate were right. I wanted to know the basis for those claims — not to refute them, but to promote them and proclaim to the world the hard scientific data showing that stereotypes were wrong.
So, when some published article cited some source as evidence that stereotypes were inaccurate, I would track down the source hoping to get the evidence. Claims of stereotype inaccuracy were based on… nothing. This is important so that anyone can find the evidence for such a claim. There is no source here. A s I read more of the literature on stereotypes, I discovered that this pattern was pervasive.
Every article or book that declared stereotypes to be inaccurate either similarly cited no source, or ended in an identical dead end via a slightly different route. And Allport did declare that stereotypes exaggerated real differences. But, aside from an anecdote or two, which is hardly scientific evidence, he presented no evidence that they actually did so. Subsequent researchers could declare stereotypes inaccurate and could create the appearance of scientific support by citing articles that also made the claim.
Only if one looked for the empirical research underlying such claims did one discover that there was nothing there; just a black hole. If all beliefs about groups are stereotypes, and all stereotypes are defined as inaccurate, then all beliefs about groups are inaccurate. It is, however, logically impossible for all beliefs about groups to be inaccurate. The inexorable logical necessity of discounting thousands of studies as meaningless goes too far. One could eliminate this problem by changing what is meant by defining stereotypes as inaccurate.
Perhaps stereotypes are the subset of beliefs that are inaccurate. In this case, only inaccurate beliefs are stereotypes; accurate beliefs about groups may exist, but they are not stereotypes. This solves the logical incoherence that stems from presuming that all beliefs about groups are inaccurate. But it produces a new sort of incoherence. Before declaring some belief to be a stereotype you would need to first empirically establish that that belief is inaccurate — otherwise, you could not know that it is a stereotype.
Vanishingly few social scientists performing research on stereotypes ever present such evidence; anyone subscribing to the idea that we need empirical proof must conclude that work without it does not count. I am willing to be quite critical of research on stereotypes, but the inexorable logical necessity of discounting thousands of studies as meaningless goes too far, even for me.
A n early review of the evidence on stereotype accuracy appeared in my book, Social Perception and Social Reality: Why Accuracy Dominates Bias and Self-Fulfilling Prophecy , and was subsequently updated in recent articles. Over 50 studies have now been performed assessing the accuracy of demographic, national, political, and other stereotypes. The evidence is clear. This correspondence is one of the largest and most replicable effects in all of social psychology.
Stereotype accuracy has been obtained and replicated by multiple independent researchers studying different stereotypes and using different methods all over the world. People have been found to be quite good at perceiving academic achievement, personality, and a variety of social and economic characteristics among racial and ethnic groups in the United States and Canada.
For example, way back in , in a study reported in the Journal of Personality and Social Psychology , social psychologists Clark McCauley and Christopher Stitt first obtained US census data showing that, compared to other Americans, African Americans are less likely to complete high school or college, and more likely to have an unwed mother, be unemployed, and have a family with four or more children.
He then asked people from various walks of life — college and high school students, union members, a church choir, masters of social work students, and caseworkers in a social service agency — about their beliefs about the percentages of Americans in general and African Americans in particular with these characteristics.
People are also quite good at perceiving many gender differences. Much as McCauley and Stitt started with US census data, social psychologist Janet Swim, in two studies reported in a issue of Journal of Personality and Social Psychology , took this meta-analysis research as her starting point, which showed, for example, that males outperform females on math tests, and are more restless and aggressive, whereas females are more influenced by group pressure and are more skilled at decoding nonverbal cues.
She then asked people to estimate the size of these differences; again, people were quite good, and their estimates again were very highly correlated with the actual differences. Similar results have been found for all sorts of other stereotypes, including those about ethnic groups, age, occupational groups, college majors, and sororities. A lthough there is some evidence of inaccurate national and political stereotypes, in general, evidence for stereotype accuracy has been trickling in for 40 years, and has become so overwhelming that even social scientists who might prefer to do so are finding it hard to simply ignore or deny.
Minimise the importance of stereotype accuracy. Sometimes, modern researchers grudgingly acknowledge that stereotypes are accurate, but go on to declare or imply that this is not very important.
But are these sorts of extreme exaggerations common? Or do people use their stereotypes approximately rationally? Even if stereotypes of groups have some accuracy, that does not justify using them to judge people. We should be judging individuals on their merits, not on the basis of stereotypes! There is some truth to this objection. Relying on inaccurate generalisations will produce inaccuracy in judging individual cases.
This can be seen with a nonsocial example. If Fred believes that Anchorage, Alaska is warmer than Madrid, Spain, and he relies on that belief for guessing where it will be warmer, he will be wrong most of the time.
Stereotypes are no different. If Elmer believes that professional basketball players are unusually short, and if he relies on that stereotype to guess their sizes, he will usually be very wrong. In other words, men experienced a boost in performance when gender stereotypes were relevant to the situation, compared to when they were irrelevant. Downward Social Comparison , a process whereby people elevate their self-esteem by comparing their group to a lower-status group, is thought to be the basis for this lift in performance Wills , Men are able to boost their self-esteem and improve their math performance by comparing themselves to women, who are stereotypically believed to be worse at math than men.
They may think to themselves, this test is difficult but at least I know I am better at math than women. However, when stereotypes are made irrelevant to the given test, men are no longer able to use this line of thinking to boost their self-esteem.
She is currently pursuing a PhD in social psychology at Skip to main content. Select issue Are Stereotypes True?
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