To build upon this naturalistic study of online comments, another research team then designed an experimental test of biased reactions to evidence of bias (Handley et al., 2015). This way, the researchers could more carefully control what they were looking at (e.g., making sure that the same person doesn’t get counted twice). The abstract from the original 2012 study was given to a sample of 205 males and females, who were asked to rate the quality of the evidence. Handley et al. (2015) showed that men evaluated the evidence of bias less favorably than women did. You might think that STEM faculty, who have been trained throughout their careers to be objective thinkers, would be less susceptible to bias than faculty in other departments, but actually this isn’t the case. Using a separate sample of 205 faculty members, they found that this difference between male and female ratings was specific to STEM faculty – professors in the arts and humanities showed no gender bias in their reaction to the 2012 abstract.

The researchers then tested whether the opposite effect would hold: do females rate evidence reporting no gender bias less favorably than males? By tweaking a few words in another abstract reporting gender bias, the researchers created a fake version purporting the absence of gender bias. Indeed, females rated the fake abstract that reported no gender-bias less favorably than males and vice versa. This implies that both men and women are capable of behaving defensively when they encounter a study that doesn’t line up with their lived experience.

These findings reveal that scientists have subjective biases--as well as biased reactions to evidence of biases--that could negatively impact under-represented minorities in STEM. Importantly, both men and women have implicit biases, and people who value their objectivity the most may actually be the most likely to fall prey to these biases. There are many possible explanations for the biases revealed by these studies, including confirmation bias (being disinclined to believe evidence that goes against our prior beliefs), social identity theory (we tend to perceive our own social groups favorably), and system justification theory (privileged groups may sub-consciously seek to justify their privileged status).

How can we overcome gender biases in science and in other realms of our lives? One simple but powerful method to combat negative implicit biases is just to recognize them in ourselves. By accepting that we all have biases and by attempting to replace our snap judgments with careful consideration, we can reduce the extent to which our assumptions influence our decisions. In order to fully acknowledge our biases, however, we must be able to accept the evidence that they exist.

Upcoming Blog Series

In our upcoming blog series, we will take a deep dive into several studies that characterize issues faced by under-represented minorities in STEM. We will engage in rigorous discussion of these works, and the implications that the data have for hiring and career progression, mentorship opportunities, support for family commitments, and workplace discrimination. We will talk about sexism, the visibility of women in academia, and our perceptions of others’ abilities. We will also review the effectiveness of different intervention approaches to directly address these issues, including a look at how virtual reality can reduce racism. Although we mainly focus on studies of gender bias due to the relative lack of data on other underrepresented groups, we believe that many of these issues affect many groups in similar ways. There is a strong need for more focused research on specific experiences going forward.