by anonymous, ’14
My mother likes to tell the story of how I applied for Stanford as a hardcore biology major with a concentration in genetic engineering, then called her after one quarter to come out as a drama major. For perspective, I’d never been involved in theater in any shape or form before college. For her, this makes an amusing anecdote about the liberalizing/artsy big blue blob that is California. For me, it’s a sobering reminder of just how alienated I felt in the STEM courses I’ve taken at Stanford.
It’s not that the material is too difficult or uninteresting—I was actually really engaged with my biology, physics, and calculus courses in high school, and looked forward to working in labs and doing research when I “grew up.” My shift from STEM is rather due to the different approaches to discussing (or not) marginalized peoples in the humanities and sciences. Whereas most of my Theater and Performance Studies professors (and especially my Comparative Studies in Race and Ethnicity professors) regularly use examples and materials that validate and explore the experiences of people who aren’t at the top of the privilege food chain, my STEM professors often make me feel angry, invalidated, and anxious. In TAPS and CSRE courses, I can speak to and learn about the lived experiences of people like me (and unlike me!). In STEM courses, data which appear to be objective often show that marginalized groups are inferior to dominant groups, without including a discussion of the systematic challenges that can produce those data. Put another way, we don’t discuss confounders that happened before we began our study.
Let me give you an example from a popular statistics course at Stanford. While learning about bias in data, our professor chose to discuss sex bias in graduate admissions. At first, I was absolutely thrilled to approach the topic—“finally we get to discuss women’s issues!” However, the gist of the talk was this: ‘Given that 44% of men and 35% of women were admitted to that university, you would think that this shows a clear bias against women. However, using the power of statistics, we can show how it is actually biased against men!’
He proceeded to break the data down by major (rather than looking at it holistically), showing the number of applicants broken down by gender, and then what percentage of those applicants were admitted. In the largest major, 825 men applied, and 108 women. Of the men, 62% were admitted; 82% of the women. I was incredulous as my professor said (with a straight face): ‘Clearly there is no bias against women since a larger percentage are being admitted here. If anything, this is actually biased against the men.’ The second largest major was even more upsetting: 560 men applied (of whom 63% were admitted), whereas 68% of the 25 women who applied got in. He explained that women usually applied to the harder majors and men to the easier ones, and that this justified the different admission rates.
I was appalled that my professor didn’t see ‘any evidence of discrimination’ when looking at data showing that 20 times more men applied for a major than did women. I wanted to talk about how female prospective students weren’t even bothering to apply, about how they were growing up in a society that steered them away from certain careers paths due to their gender, about how seeing almost exclusively men in a department would alienate them from applying (much less staying for their entire course of study), about how faculty (of all genders) are less likely to take applicants seriously if they think they are women… but none of that happened. Instead, we got a coup-de-grace comment clearly meant to be amusing: ‘Maybe women should stop only applying for the hard majors.’ Remember: it’s the womenfolk’s fault that many of us don’t feel safe or qualified to work in certain fields.
Later, in section, we did another practice problem, this one dealing with former Harvard President Lawrence Summers’ comments in 2005 about women in science. The short version of this story is that he noted that men outnumbered women two-to-one in the top 5% of IQ scores, and theorized that this contributed to the disproportionate lack of women in STEM. Our (male-identified) TA then walked us through Summers’ calculations, which he supported (though he never explicitly endorsed the conclusion, merely all the of the data that supports it). Several of the women in the section were visibly upset, and a few of us spoke up and started discussing the sociological factors what would contribute to this data (the lack of equal access to education across genders, bias in IQ testing, etc.). The TA chuckled, waved away their comments, and moved on to the next question.
These examples are not confined solely to gender: one homework question addressed the idea of a “permanent underclass in American society,” asking us to determine whether a given set of data supported this concept. As someone who has studied race and socioeconomic class, I’m familiar with how ‘upward mobility’ is a myth in the vast majority of cases, but they didn’t provide us with data to support that (even though such data exists). My favorite part of this question was the instruction: “Discuss briefly.” There’s no way to have a brief discussion about a “permanent underclass in American society.” As much as I would love to find an “equation of the permanent underclass” (as equations are generally solvable), the issues at hand are much more complicated than can be summed up with a chart and a TI-89.
It’s fascinating to me that a group of public high school teachers from a Midwestern town (a red-leaning town with fewer people in it than the Class of 2016) was far more welcoming and encouraging of marginalized students than the “world class faculty” of Stanford University. We so often pat ourselves on the back for our “liberal” university, but we need to spend more time thinking critically about where and how that actually manifests itself. There’s more to an inclusive STEM program than mentioning women or using stereotypically “ethnic” (read: racialized) names in your problem sets.
The author is a junior at Stanford.