It strikes me that I use the word "depressing" far too often in conjunction with readings from "Class, Race, & Gender" class. I'd like to use words like "action-inspiring" (or some other trumpet-blasty, call-to-action sound effect) instead, but... there's so much to notice, problematize, and fix, and I... am tired. So here is thinking and writing, which is an action in and of itself.
Of all the readings on intersectionality last week, the original data grabbed me most: the Nelson Diversity Surveys are now-famous statistics of faculty diversity in "top 50" USA STEM departments. Wikipedia's summary is pretty good. Nelson tracked down complete statistics for every. single. faculty member. in each of those departments. Every. Single. One. I have an overwhelming respect for how much tenacity that must have taken: universities don't publish these statistics (probably because they sound bad), so Nelson had to write and call and hound and hound and hound department chairs with superhuman persistence.
Click on any dataset. Look at the "Native" column. Empty, almost always. Hispanic? Black? Asian? So many singletons. So many lonely individuals: not only are you the only Hispanic woman in your department, but (as Alice said in class) now you can look around and see that you're the only Hispanic woman with tenure at a top research university in your entire discipline. You are a unicorn!*
Compare the 2002 and 2007 versions of the same dataset. See any changes? In minority groups, can you pick out individuals -- ah, there was a Black male assistant professor of Computer Science at University of Such-and-So in 2002, and not in 2007; he probably did not get tenure, and if we look at the old university directory we can probably find his name...
As an Asian-American, I also wondered: how many of the Asians in the "Asian" column were American-born? I stroll the hallways of my own R1 and see the office doors of Chinese professors strung out down the hallway, but they feel like people who are Not Like Me -- not that international hires are fundamentally bad, but not all Asians are alike and we can't "support diversity" by importing people; their genes may be similar to mine, but their culture isn't. So in a department full of Chinese-born Chinese, I still feel very, very much alone.
Nelson Diversity Surveys" Donna J. Nelson, Diversity in Science Association: Norman, OK, 2004; http://chem.ou.edu/~djn/diversity/top50.html
*The Unicorn Law, coined by Emma Jane Hogbin, states that "If you are a woman in Open Source, you will eventually give a talk about being a woman in Open Source." I personally think the Law extends to STEM in general.