Picturing a New STEM Workforce
Photo / BYU-Hawaii
Close your eyes. Now picture a scientist. Do you see a white man, maybe cloaked in a laboratory coat with his hair in wild disarray? If so, you’re hardly alone.
In 1957, Margaret Mead and Rhoda Metraux had 35,000 high school students write essays describing their perceptions of a scientist. Nearly everyone’s descriptions matched the one above.
Close your eyes. Now picture a scientist. Do you see a white man, maybe cloaked in a laboratory coat, with his hair in wild disarray? If so, you’re hardly alone.
In 1957, Margaret Mead and Rhoda Bubendey Métraux had 35,000 high school students write essays describing their perceptions of a scientist. Nearly everyone’s descriptions matched the one above. Then in 1983, David Wade Chambers developed the Draw-a-Scientist Test (DAST), which asked participants to do just that. In the initial study, 5,000 students were tested, and only 28 girls drew a female scientist. In the last three decades, the test has been administered many times to participants of different ages, races, genders, and nationalities. The results are almost always the same.
In reality, science and other STEM fields are not quite as homogenous as they are on DAST paper. The presence of women and people of color is thankfully a bit higher than it typically is in these studies. But not by much. Last year, Google released its demographic data, confirming suspicions about the makeup of its workforce. As of June 2014, Google employees were 70 percent male and 91 percent white or Asian. A US Census Bureau study from 2011 found that although women composed almost one-half of the nation’s workforce, they composed only one-quarter of STEM professionals.
How do prevalent images of scientists—in our minds, on paper, in the media—relate to the reality of STEM fields?
“Inoculating the perception of a scientist is tantamount to fixing the leaky STEM pipeline,” wrote Ainissa Ramirez in Edutopia last month. Her claim is a bold one, and it’s not quite substantiated. Nobody can say for sure whether our stereotypes of scientists are caused by—or help perpetuate—the demographic makeup of STEM. A child asked to draw a particular type of professional will produce an image of the type of person she, consciously or subconsciously, believes belongs in the field.
Some studies suggest exposure to diversity in a field positively affects perception and stereotypes. A DAST study in 2014 involved undergraduate students taking a class on science education methods and graduate students studying science education. The scientists in the graduate students’ drawings were less likely to be white (66 percent versus 95 percent) or male (70 percent versus 90 percent) than those in the undergraduates’ drawings. The graduate students were immersed in the field, and their awareness of female colleagues may have influenced their perceptions.
In 2013, two researchers compared the gender makeup of those enrolled in high school physics (a nonmandatory, higher-level science class) with that of STEM workers from the same communities. They found that “the male advantage in high school physics is significantly smaller or nonexistent in schools situated in communities where more women are employed in STEM professions.” Again, they acknowledged there’s no evidence for causation here, but they wrote, “In communities where a higher percentage of working women are employed in STEM occupations, larger gender stereotypes at the societal level may be subverted by a picture of what is possible that differs from that typically associated with more traditional gender roles.
More role models and other women working in STEM fields might be a powerful “fix” to the imbalance. Research has shown that when people fear they’re living up to stereotypes of them—such as “women aren’t good in math”—it affects their performance. First identified by C. M. Steele and J. Aronson in 1995 in a now famous study, “stereotype threat” causes members of a group to worry that their poor performance will confirm the perceived negative stereotype about their group. This threat can cause stress that undermines performance. Further, consistent exposure to stereotype threat, like that of women in math and science, can lead them to no longer value the subject or choose not to pursue it further. The resulting poorer performance induced by stereotype threat can create a feedback loop that convinces girls that, indeed, they are not smart enough for STEM courses.
In Pittsburgh, many organizations have long worked to combat disparities in STEM by introducing students to role models and pathways into STEM fields. The Carnegie Science Center runs Tour Your Future, a program that introduces girls to female professionals in a range of STEM careers. STARTup SOMETHING, a program through Big Brothers Big Sisters of Greater Pittsburgh, pairs at-risk youth with mentors at tech companies. In addition, high school students throughout the region join Girls of Steel, a competitive female robotics team that has competed in international tournaments. Hosted and supported by Carnegie Mellon University, the team welcomes applicants of all financial levels from the Greater Pittsburgh area.
Scientists—and engineers, mathematicians, and technologists—look alike, on paper and on TV, as well as in most offices and laboratories. Groups like those in Pittsburgh are working hard to show our future professionals that this doesn’t need to be the case.