“For a Girl”, Paper Cuts, & Confirmation Bias: A Response to Alison Coil’s "Why Men Don't Believe the Data on Gender Bias in Science"
by Sinead Li
“You're good at math, for a girl." This sort of backhanded compliment has haunted me my entire life. I’m good at math. Period. That’s the end of the sentence, it should stop there. And the worst thing? The people saying this kind of stuff view it as a compliment. A compliment! Can you imagine -- they thought I should be pleased when they put down my entire gender.
As such, I've always been... apprehensive about pursuing a STEM career. I don’t want to be seen as the minority hire. As someone who didn't deserve their spot, but in the name of diversity, I was given it. Moreover, there’s the fear of sexual harassment and the uncomfortably hyper masculine culture. One female engineer at Google reported the sexism to be "like death by one thousand paper cuts.” No wonder over 40% of female engineers end up leaving the field. That's what I am apprehensive about; I am apprehensive about this suffering.
"Why Men Don't Believe the Data on Gender Bias in Science", written by Alison Coil for WIRED, addresses some of my concerns. Coil, a physics professor at UCSD, first begins by proposing that the real reason there is a disproportionate number of women in STEM fields is that “[leaders] in the field—men and sometimes women—simply don’t believe that women are as good at doing science.”
According to Coil, men are reluctant to accept the clear evidence demonstrating that gender bias is deeply ingrained into their industry because of the following two reasons:
The careers of scientists are rooted in rational objectivity. It would be difficult to come to terms with the fact that the whole field is plagued with fundamental logical errors concerning the gender disparity.
There is a sense of guilt inherent in the admission that women are being systematically discriminated against -- men are forced to grapple with the idea that their position is less-than-deserved, that the invisible hands of privilege worked in their favor.
Coil’s argument is clear and concise. But is it true? I certainly believe so. Scientists are the worst of statistical cherry-pickers, incessantly choosing specific flawed studies over broad trends in research, to substantiate cultural norms. That said, I propose another explanation to follow Coil’s two: scientists are in closer proximity than others to the underrepresentation of women in STEM fields, and thus are more susceptible to confirmation bias.
Confirmation bias is the tendency to favor information in a way that confirms one’s preexisting beliefs. In this case, sexism is deeply entrenched in our society, encoded into our collective subconscious. The perception of women as naturally less skilled than men is our preexisting belief. Take the “violin behind the curtain” story, for instance: blind auditions for orchestras in the 1970s doubled the number of women advancing. Women were immediately dismissed the moment they stepped on stage to perform; they had to obscure their face to be seen as equal! And all of this operates at a subconscious level, one that is difficult to control... As such, men are oftentimes unaware of this pre existing belief that automatically devalues women. And due to confirmation bias, this sexism is only emboldened -- If you look at the current makeup of STEM fields, the statistics are dismal: women account for only 29% of the science and engineering workforce, with minority women at less than 10% (compared to around 20% of the U.S. population), and female engineers at 15%. So when scientists look around and see their male colleagues, their male bosses, and their female... secretaries, all this information solidifies their subconscious views that women are naturally less skilled than men. The average person may read about, say, Albert Einstein and Stephen Hawking and Isaac Newton, all these male scientific geniuses that play into confirmation bias. However, the personal connection that scientists have -- “their male colleagues, their male bosses” -- is far more significant. Therefore, when scientists are confronted with empirical data that demonstrates gender bias, thus conflicting directly with their preexisting beliefs, they are prone to dismiss it.
Historically, the privileged have always gravitated towards the information that best confirms their preexisting beliefs. In the 1800s, black “inferiority” due to “natural” neurological differences was used to defend the institution of slavery. As recently as last year, James Damore, author of the infamous anti-diversity Google memo, utilized the same argument: female inferiority due to natural neurological differences was used to defend the systematic sexism exhibited by Silicon Valley. And the themes present in Coil’s article will be just as present in the future.
However, not all hope is lost. Just a few decades ago, Asian scientists were seen as genetically inferior to white scientists due to the lack of Asian Nobel prize-winners back then. Now, that idea is laughable. Asians account for 17% of scientists and engineers despite being only 5% of the U.S. population. Now, confirmation bias works for Asians rather than against them. The same will happen for women, I can guarantee this. We have fought for our property rights, our voting rights, our rights to our bodies, even -- discrimination in science is just another example of a ridiculous obstacle that we will triumph over. We will fight for the freedom from stigma. And then, men won’t have to believe the data on gender bias in STEM fields anymore. Why? Because this bias will cease to exist. One day, people will tell me “You’re good at math” and stop there.