highly relevant: bias in science.

*facepalm*
well, this is highly discouraging ..

In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student.

~ from "Science faculty’s subtle gender biases favor male students" @PNAS
by C.A. Mοss-Racusina, J.F. Dοvidio, V.L. Brescοll, M.J. Grahαm, & J. HandeΙsman

(see also the discover magazine article about it.)

by the way, i'm a mathematical analyst, not a statistical one. so does anyone know, based on the conclusions of the study, if n = 127 is a sufficiently large sample size for rigor?