I’m taking a class this semester to learn how to teach; specifically, I’m taking a class to learn how to deal with the challenges and opportunities inherent in a classroom with a diverse student body. What exactly is meant by “diverse” ranges from national origin to race or ethnic identity, or from gender to sexual orientation to even just your mastery of the English language. It’s a recognition that every student in your class is coming at your subject from a different place from every other student, and ignoring that background diversity can impede your ability to actually get a point across – and conversely, acknowledging that diversity can make you a much more effective teacher. Being a graduate-level seminar, we read a paper or two before class and then our class is a two-hour discussion/activity session related to the theme of the paper.

Today’s theme was a concept called “stereotype threat”. We read a paper by a Stanford professor calledHow Stereotypes Shape Intellectual Identity and Performance (long-ass PDF warning, if you feel like reading it), which focuses on the stereotypes of women as being bad at math and of African Americans as being bad at school in general, and the negative impacts of those stereotypes on those groups. The first half of class we spent talking about the implications of stereotype threat. Generally, a negative stereotype about a group in a particular discipline is more threatening the more strongly you identify as a member of that group AND that discipline. For me, it has a lot to do withimpostor syndrome, which is the general feeling that I don’t belong in my field, despite the fact that by most measures, I’m doing pretty well in it.

The second half of class, however, we focused primarily on racial attitudes, by way of a CoBRAS inventory. CoBRAS, or a Color-Blind Racial Attitudes Scale, is one of those fantastic corporate quizzes (“please indicate your level of agreement on a scale of 1-6”) that reduces your awareness of race-based issues to a handy-dandy number that you can compare to other people’s numbers and say “ha ha I’m more racially sensitive than you are” or whatever. But what is really interesting about it is not the numbers it produces but the conversations it begins.

We discussed a few of the specific inventory items, but moved quickly to a discussion of the overall inventory. Why did you agree or disagree with certain statements? Why did you have the strength of reaction that you did? What does your response say about your identity?

Our class, of 25 people on a good day, has one Black (well, biracial) student. She spoke up as being somewhat surprised by the categorization of her responses as being “kinda racist”, particularly in comparison with mine (which were somehowmore racially-aware than the average POC response by a standard deviation and a half). However, her Black dad is African, and her mother is a White American, so she has no identificiation with the African American culture as such – she was told as a small child that she “sounded White” and didn’t know why anyone would want tonot. That led to a teachable moment where I introduced a bunch of graduate students to the concept ofAAVE and its cultural significance (in Jude’s words: WHO DOES NOT KNOW THIS but that’s a rant for another time), but also a salient underscore to the concept of stereotype threat.

A stereotype is an assumption made about another person based on certain characteristics of that person: You’re a lady so you can’t do math. You’re African American so you’re bad at school. You’re young so your opinions are uninformed. How much these stereotypes are threats to you, though, has a lot to do with how strongly you identify with either the group (e.g. “African Americans”) or the domain (e.g. “academics”). Here, lemme draw you a picture:

Stereotypes are threatening to people in the overlap of that first Venn diagram. If you’re not a part of the group, it’s not a threat; if you don’t care about the domain, it’s not a threat. Men generally don’t feel threatened by stereotypes about women and math; similarly, women who don’t care about math don’t find the stereotypes to have any influence in their lives.

The real insiduousness of stereotypes isn’t that they keep underrepresented groups from trying: they push out those people who care enough to try to get in.