I promised the D-Lab a blog post and then promptly felt unqualified to write it. (I wish that I were kidding.) Thus begins my ironic tale of imposter syndrome in data science.
Who am I?
As a new D-Lab Data Science Fellow and as a doctoral student in Rachel Morello-Frosch’s laboratory in the Department of Environmental Science, Policy, and Management at Berkeley, I work at the intersection of social theory, environmental epidemiology, and geography. Specifically, I research how institutional power manifests in the distribution of environmental monitoring networks in the United States. (Whose air and water do United States federal and state agencies monitor for pollutants? Whose don’t they monitor? And why?)
What is imposter syndrome?
Clinical psychologists Pauline Rose Clance and Suzanne Imes originally coined the term “imposter phenomenon”, the academic term for imposter syndrome, in 1978 to describe a pattern that they had observed in some of their women clients and students in high-ranking academic and professional positions. Specifically, their clients often felt like they were frauds or imposters despite records of high achievement. A systematic review last year of the literature on the imposter phenomenon found evidence of its prevalence across countries, genders, and minoritized groups, with a particularly high prevalence among racially and ethnically minoritized groups in the United States. The review authors report particularly robust associations across studies linking the imposter phenomenon with decreased job satisfaction, decreased job performance, and burnout, but no known published studies evaluating ways to treat the imposter phenomenon in individuals.
What’s a graduate student imposter to do?
Speaking personally from my standpoint as a white cis queer woman graduate student in the United States who is not a psychologist, I don’t know much, but here’s a humble offering of what I wish that I’d heard when I started graduate school:
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I didn’t think that I’d get into graduate school (and often felt like throwing up as I filled out the applications). I’ve felt similarly for every major grant and academic application I’ve ever written, even the one for the D-Lab. Yet here I am! If you feel similarly when you apply for things, you’re not alone.
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People at prestige-driven academic institutions like Berkeley sometimes talk as if they know more than they do. I know that I have. Thus you might not be as far behind the people pontificating around you as you think. I once worked in an environmental justice law clinic where the pressure on students to seem smart was so pervasive, and the potential consequences of not asking for help on real legal cases so dire, that the supervisor of the clinical program assigned us Martha Beck’s three-page retelling of the Harvard Smurf Redirection of Linguistic Epistemology as a cautionary tale. (If you read one link on this post, read that one. Machine-readable version on pages 77-79 of the Google book here.) As the D-Lab teaches, “it’s OK not to know” (IOKN2K)!
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Sometimes it’s not you; it’s ESRI. I cannot tell you how many hours of my mortal life I have spent cursing ArcGIS, RStudio, GitHub, and Travis. Heck, I even spent 20 minutes for this article trying to figure out how to get Zotero to play with Google Docs. Working with other people learning data science has taught me that this is normal.
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Ask for help on coding problems earlier rather than later. I’d say that eighty percent of the R and Python code I know I learned from Google and StackOverflow. People have answered questions in minutes that had me stumped for hours. (And no one’s going to stop you from using United States Women’s National Soccer Team players’ names for the variables in your reproducible examples.)
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People learn how to write papers faster and increase their rate of productivity over time. A friend told me a few years ago to stop judging my curriculum vitae by the curricula vitae of those who’ve been in academia for five more years, which seems obvious to me in retrospect but didn’t at the time.
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Supportive mentors and colleagues have made a huge difference. I’ve accomplished much of what I have so far because of those who believed in me, wanted to work with me, and pushed me to apply to opportunities for which I wouldn’t have dared to apply on my own. I’ll always be grateful to those who believed in me when I didn’t.
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Friends outside of academia have helped me maintain my perspective. I’m sure that my future rides on the quality of my dissertation prospectus. They think that one of my quals committee members might skim it before it hits the circular file. (After they ask me what a quals committee is.)
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I can’t think of a single graduate student friend of mine who hasn’t sought therapy. I personally would not have lasted this long in graduate school without a space where I can talk freely and get support.
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Lots of students struggle with mental health problems in graduate school. Graduate school as currently structured in the United States isn’t great for mental health. Graduate students here report mental health problems at higher rates than the general population, and our mental health has particularly cratered during the pandemic. A survey of 15,346 graduate and professional students in the United States in mid-2020 found that 39% reported the symptoms of generalized anxiety disorder (GAD) and 32% the symptoms of major depressive disorder (MDD), rates 13 and 17 percentage points higher, respectively, than those among graduate students in 2019 and 8 and 7 percentage points higher than those among the general United States population (estimated by a different method) in mid-2020. Indigenous, women, Latinx, low-income, non-binary, trans, and queer graduate students reported mental health problems at even higher rates. In short, if you’re struggling with mental health in graduate school these days, you’re not alone.
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Systemic problems require systemic, not individual, solutions. Structural violence within and perpetrated by the university isn’t your fault, and all the therapy and self-help articles in the world can’t make up for the impacts of that violence or replace systemic change. Reading social theory has helped me to understand my own experiences within the university in a broader social context and to take the university’s implicit messages about who has value and worth with more skepticism. Even Clance and Imes, in coining the term “imposter phenomenon,” theorized it as an introjection (internalization) of negative societal stereotypes. Mullangi and Jagsi offer a cogent critique of individualized solutions to imposter feelings that originate in response to systemic inequities and discrimination.
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A sampler of evidence of such systemic problems: Hofstra et al. found that minoritized doctoral students in the United States innovated at higher rates in their doctoral dissertations but had successful science careers at lower rates than members of majority groups. Boring et al. found large amounts of bias against female instructors in student evaluations of teaching, particularly those that male students wrote. Hoppe et al. found that the National Institutes of Health funded R01 grants both for Black and African American scientists and for the topic areas that they tended to choose at lower rates than those of white scientists. Within data science, Google fired ethical artificial intelligence researcher Timnit Gebru last month in retaliation against her critiques of the racist working conditions that she experienced at Google. The list continues.
I’ll end by saying that despite having this blog post platform, I don’t have a definitive answer to imposter syndrome and still struggle with it myself. What I can tell you, though, is that I’m glad that you’re here reading this. I doubt that you’re an imposter. And you’re not alone.