In a real-world setting, typically the most we can do is identify differences in outcome. A man is selected for hire over a woman; fewer women reach tenure track positions; there’s a gender gap in publications. Bias may be suspected in some cases, but the difficulty in using outcomes to prove it is that the differences could be due to many potential factors. We can speculate: perhaps women are less interested in the field. Perhaps women make lifestyle choices that lead them away from leadership positions. In a real-world setting, when any number of variables can contribute to an outcome, it’s essentially impossible to tease them apart and pinpoint what is causative.(side note: that salary jump might seem small, but when you earn that little it's a huge difference in quality of life, particularly if you have kids)In a randomized double-blind study....Half the scientists were given the application with a male name attached, and half were given the exact same application with a female name attached. Results found that the “female” applicants were rated significantly lower than the “males” in competence, hireability, and whether the scientist would be willing to mentor the student. The scientists also offered lower starting salaries to the “female” applicants: $26,507.94 compared to $30,238.10.
Sexism exists. It’s real. Certainly, you cannot and should not argue it’s everything. But no longer can you argue it’s nothing.
We are not talking about equality of outcomes here; this result shows bias thwarts equality of opportunity.Both male and female scientists were equally guilty of committing the gender bias. ...“If faculty express gender biases, we are not suggesting that these biases are intentional or stem from a conscious desire to impede the progress of women in science. Past studies indicate that people’s behavior is shaped by implicit or unintended biases, stemming from repeated exposure to pervasive cultural stereotypes that portray women as less competent…”When scientists judged the female applicants more harshly, they did not use sexist reasoning to do so. Instead, they drew upon ostensibly sound reasons to justify why they would not want to hire her: she is not competent enough.Practically, this fact makes it all the more easy for women to internalize unfair criticisms as valid. If your work is rejected for an obviously bad reason, such as “it’s because you’re a woman,” you can simply dismiss the one who rejected you as biased and therefore not worth taking seriously. But if someone tells you that you are less competent, it’s easy to accept as true.http://blogs.scientificamerican.com/...hy-it-matters/I’m willing to bet that many in the study, just like people who take Implicit Association Tests, would be upset to learn they subconsciously discriminate against women, and they would want to fix it. Implicit biases cannot be overcome until they are realized, and this study accomplishes that key first step: awareness.
The study was recently published in PNAS, a very prestigious scientific journal, and their methodology looks sound.