An ordinary e-mail once caught the eye of Modupe Akinola,Assistant Professor of Management at Columbia Business School. It was from a prospective Ph.D. student, an African-American woman, asking for a meeting.
Dr. Akinola wondered: “Would I have reacted differently if this was from a man? Would it make a difference if the request was for today and not next week?” She joined with colleagues Katherine Milkman and DollyChugh to turn these questions into research questions in a field experiment measuring discrimination in academia.
The creative and elaborate experiment started with putting together a representative sample of over 6,500 faculty members from 260 universities. The team used publicly available demographic information on professors to ensure a good sample. The researchers then created a few prospective Ph.D. students. The names of these imaginary students were tested and proved to be easily recognizable as either male or female and as Caucasian, Black, Hispanic, Indian or Chinese.
At 8:00 am on a Monday, e-mails from Brad Andersons, Latoya Browns and 18 others went out to unsuspecting subjects, asking to meet “today” in half the cases and “next Monday” in the other half. The research team was impressed by how quickly most faculty wrote back and how often they agreed to meet, but when and with whom they agreed to meet was more interesting.
One would think academia, with its affirmative action and enlightened world views, might be a post-racial, post-gender sphere. As it turns out – not so much, especially not when there is time to think about it.
In the now condition, Akinola, Milkman and Chugh found no significant difference between number of responses to white males and to others, but when the request was for later, white men received both more responses and more meeting acceptances than any other prospective students. The white men fared better than all other racial categories across almost all disciplines. The effect remained even when the race or gender of faculty and student matched.
According to construal level theory (CLT) immediate events demand concrete reasoning focused on feasibility, whereas decisions about distant events trigger abstract thinking and a focus on desirability of the event. Thus, future events create more room for unconscious stereotypes and biases to enter the decision-making process. In this study, for instance, the responses received to the “now” requests systematically displayed a focus on “how,” whereas the “later” e-mails were more likely to be answered with a request for credentials or more information – a “why” response.
The point of this experiment and other studies that spotlight the influence of stereotypes and biases on consequential decisions is not to call people racist or sexist. The point is to come up with ways to address the biases and to improve minority outcomes. For instance, referring all prospective students to the Ph.D. program coordinator would take the burden off individual professors and ensure that all students get their questions answered. This is just one option that an experiment like this might bring up for discussion.
Unfortunately, some faculty did not take kindly to the experiment. When debriefed and told that they had been used in a study of bias, many expressed outrage and demanded to speak with the Institutional Review Board.
To me, their reaction suggests the thorny subjects of race and gender are not studied enough in academia. Perhaps academia, more so than other spheres, makes it taboo to have biases, but shaming does not make biases go away! Nobody wants to be called a racist or sexist, not even a little bit, but simply feeling guilty is not productive. We can structure decision-making in ways that level the playing field, and we need creative researchers like Akinola, Milkman and Chugh to make that happen.
Anya Malkov is an MPP2 at the Harvard Kennedy School, a WAPPP Cultural Bridge Fellow, and an alumna of From Harvard Square to the Oval Office.