Thanks to Director of Institutional Research Chris Winters ’95, here is the racial/gender breakdown of Williams for the fall of 2008.

                           First Year    Total
                              M/F         M/F
Nonresident alien            31/15       88/56
Black                        21/35       77/117
Native American               0/4         2/9
Asian                        28/36       100/122
Hispanic                     23/30        88/97
White                       152/164      635/592

Total                       255/284      990/993

Chris notes that this data has already been reported to IPEDS and should appear there sometime this fall. Comments:

1) Many of these patterns are common among elite colleges. There are many more Black females than males and a similar, although less striking, imbalance among Hispanics and Native Americans. The standard explanation for this effect is that female URMs on average have much stronger high school academic records than make URMs. So, it its attempts to get enough URMs while simultaneously maximizing a student’s chances of success at Williams, the College has no choice but to put up with a gender imbalance. Isn’t that the standard story?

2) Why the gender imbalance among Asians? Obviously, a single year tells us little, but I did not expect to see this. A random effect? True for other elite colleges? Caused by differential rates of classifications. (See more below.) For example, are bi-racial Asian-American females more likely to identify as as Asian-American? I am stumped. UPDATE: See below.

3) As hwc has noted in the past, it is very hard to get data out of IPEDS. Looking at trends over time, both at Williams and its peer group, would be an interesting exercise.

4) The biggest difference between Williams data and that from similar schools is that Williams somehow manages to assign a single ethnic/racial category to every single student. Chris provided the exact details of the process 2 years ago. See that post for all sorts of interesting discussion as well as fun ideas for trouble-making. Summary: Williams tries very hard to classify students and gives them a chance to “opt-out.” None (not a single one?) do. Other schools report very different results. More than 20% of the students at Amherst (pdf) are classified as “Race/ethnicity unknown.” I believe that, if those students were at Williams, they would be classified as white. Not that there is anything wrong with that!

5) All these numbers are somewhat skewed because they ignore students studying abroad and those students are more likely to be female.

UPDATE: hwc kindly provided this graphic.


I second his analysis:

One thing that may be happening here is that engineering and tech oriented schools (at least the elite schools) are considerably more Asian American than their all-purpose equivalents. These schools also tilt heavily male. So, it could be that male Asian Americans tend to mass at these tech-oriented schools, leaving the equivalent all-purpose schools more heavily female in the Asian American cohort. This is logical and echoes the overall gender trends.

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