The effect is the same isn't it? Less chance for a student with ancestors from a particular geographic locale getting a placement.
The "high performance means there's a bias" theory only works if you assume that everyone is starting from the same social, cultural, and physical baseline. They aren't.
Maybe a better metric would be if there were no mediocre data points among a certain group; that would be more evidence (but still not necessarily good evidence) that you have to exceptional to get attention and overcome the "bias barrier", not simply that most of a certain type of performer does better than a different type.
In [14]: x = norm(0.0,1).rvs(100000)
In [15]: mean(x[where(x > 2.0)])
Out[15]: 2.3774795090391301
In [16]: y = norm(0.5,1).rvs(100000)
In [17]: mean(y[where(y > 2.0)])
Out[17]: 2.4372124830289557
I.e., a difference in the mean of 0.5 sigma corresponds to 0.06 in Graham's test statistic.Graham is a little bit off - a better place to look for bias is the bottom of the accepted distribution than at the mean.