Understanding the Gender Deficiency in CS
As of 2014, only 10% of employees at Twitter were women software engineers — an embarrassing statistic that also found itself consistent with several Silicon Valley giants. Unlike other STEM fields, Computer Science (CS) has witnessed a decrease in women engineers since the 1990’s — an ongoing trend that makes it hard to believe that the first computer scientist, Ada Lovelace, was a woman, or that Grace Hopper built the first compiler for a programming language. This trend of moving away from computer science sees itself relevant also to young college women, and not surprisingly, to the women at Barnard. Although I currently pursue computer science as my major, my first introduction to the field involved initial feelings of intimidation. I had mentally characterized the field as an elitist male dominated club. This personal reflection on my initial encounter with the field, confirmed for me the existence of a concrete and prominent hindrance for women attempting to pursue CS — a hindrance that helps answer the question: Why is it still so hard for women at Barnard to pursue computer science?
Stereotype threat theory and the Sapir-Whorfian hypothesis amalgamate in unpacking this prominent roadblock. While Claude M. Steele describes the prevalence of a “stereotype threat” in his discourse to explain the psychological barrier that interferes with women’s identification and self-confidence in their abilities, Tom Shachtman’s “The Inarticulate Society,” discusses how language affects the way we think — a theory I use to frame how coding languages challenge our minds to think and structure information in different ways. Consequently, both Steele’s “stereotype threat” and the initially difficult process of acquiring a new language and way of thinking (though integral to growing as a programmer) dissuade women from sustaining their presence in the field.
As a speaking fellow, I aspire to extend the relevance of speaking in all contexts and show others how to leverage speaking skills to their advantage. Although this two-component hindrance lends itself heavily in erecting barriers in making women feel inferior, I want to help women overcome this pervasive stress and learn how to communicate in a way that allows them to learn confidently in an environment that may feel as though is rooting for their failure. Although this certainly applies to the difficulty in entering Computer Science, I will help my fellow Barnard women acquire the proper skills to combat the initial intimidation of any field so they can feel empowered to enter any challenging field they desire and feel equipped to succeed.
In his essay, A Threat in the Air, Stanford University’s Claude M. Steele discusses the prevalence of a lingering “stereotype threat” that can be applied in order to understand what stops women from staying in computer science. Steele explains that stereotype threat arises when someone is already in a space in which negative stereotypes about one of their identities is well known and the risk of potentially confirming that stereotype influences their “intellectual functioning,” and more specifically elicits pressure and stress (Steele 614). Before Steele dives into explaining how certain societal stereotypes mentally influence certain groups associated with that stereotype, he establishes his overarching claim that the individuals affected by this stereotype threat are those who care about success in school. His underlying reason for establishing such a foundation allows him to later show how consequently, these individuals “identify with school achievement” and as a result hold themselves to a certain degree of accountability to succeed (Steele 617). It is in that vulnerable space that the stereotype threats surfaces — in which this “self-identification,” or one’s attachment to a particular domain, potentially can be threatened. In fact, the more a person identifies with their domain, the more they are at risk of having their self-identification be threatened.
In my third year of taking computer science courses, a particular experience resonated strongly with this feeling of constant pressure during my learning process, a product of the stereotype threat’s pervasive nature. As Steele highlights, this nervosity was not a function of my personal lack of confidence in the field, but rather a result of fearing to confirm a stereotype that I never wanted to believe to begin with. Specifically, because I made a conscious effort to help debunk the validity of the “dumb woman in CS” stereotype, I felt at risk of failing at my own personal mission. My yearning to impact an overarching societal perception of the field stemmed from my strong self-identification with the CS domain.
I saw this feeling of pressure play out last year when I found myself struggling with a difficult coding assignment. A male friend of mine offered to help out. While I generally tend not to ask for help because I believe that sometimes struggling through the pain of not knowing something teaches you a lot (a point that I will elaborate further on), I also tend not to ask for help because I don’t want to challenge my ego. Naturally, my immediate reaction was a blunt, “No- I can figure it out.” My refusal to ask for help was further layered with a desire not to let a man be my immediate resort for help. Not to mention, saying that “I can figure it out” had the implicit intention of reassuring both myself and him that I was more than capable of solving the problem, even though he never denied my ability to do so. Again, my mental reasoning in this moment was a product of “interpreting,” as Steele suggests, my friend’s innocent inquiry question in a way that challenged my standing in the CS domain (Steele 616). Aware of my common habit of dodging help in all circumstances, he said genuinely, “It’s okay to ask for help, you know.” Perhaps because his words acknowledged to a certain degree that he respected my ability to code, I gave in for the first time. But everything that followed made me wish I never did — not because he wasn’t helpful, but because the way I interpreted the following interaction resulted in me again confirming (in my eyes) a stereotype that I was trying to hard to fight.
After explaining my confusion, he contemplated for 5 minutes and soon was explaining to me how it worked. My shock in his ability to solve the problem quickly overtook me. Rather than focusing on his thorough explanation as he spoke, I instead questioned my own abilities and used that time to compare our abilities: why is he so much faster than I am? Am I so slow at understanding this because I am a woman? Rather than learning something and acknowledging how normal it is to sometimes not know, numbness consumed me and an overbearing feeling of inadequacy lingered. I helplessly said, “You think I’m so stupid, don’t you?” Since that question is usually responded to with an immediate denial, I saw my question as a last effort to potentially salvage any respect he may have lost for me. “Um, no,” he responded, perplexed. His confused response confirmed for me that he was not questioning my ability- he was simply helping. Rather, it was my own interpretation of the situation that left me with residual feelings of inferiority. Similarly, several other women’s experiences in CS fall along similar lines.
The way to combat this involves inculcating in communities affected, confidence in uncertainty and lack of knowledge, and the ability to communicate in a meaningful way when answers are not clear. As a speaking fellow, I yearn to provide individuals with the tools to fight the impending war of emotional instability that the stereotype threat graciously welcomes. That involves, teaching women how to maintain mental clarity despite external pressure and teaching women not to conflate initial ignorance or struggle with confirming a negative stereotype about themselves.
Although the stereotype threat contributes in great part to explaining the gender diversity deficiency in CS, the challenge of learning a new coding language (and arguably a different way of thinking) is also an essential ingredient in understanding why women are so easily pushed away from the field. In his article, Tom Shachtman posits whether there is really a “standard” English. In exploring that question and discussing the barriers many non-English speakers face, he also delves into the many theories behind how language affects the way we think. Although the following theory usually finds itself applicable in the context of spoken rhetoric, I argue that its relevance transfers to the “language” of computer science, equally a communicative and syntactically rich language similar to English. In particular, he discusses the Sapir-Whorfian hypothesis — the idea that “we are the language through which we think,” pointing to the idea that our mental structure is shaped by the means through which we communicate (Shachtman 50). Although Shachtman makes clear that he disagrees with the Sapir-Whorfian hypothesis, he clearly finds more disagreement in an deeper conclusion implied by the hypothesis which suggests that some individuals are mentally superior to others who do not speak a certain language. While even I do not agree with such an elitist suggestion, I do not deny the validity in the idea that language affects the ways the way we think.
Shachtman showcases how differently literate and illiterate cultures think in an experiment where the two groups (literate and illiterate groups) were asked the following question: “In the Far North, where there is snow, the bears are all white. Novoya Zelyma is in the Far North. What color are the bears?”(Shachtman 45). While the literate group was able to easily use the contextual clues of the sentence to come to the conclusion that the bears are in fact white, the illiterate group was incapable of using the structure of the sentence to arrive at the same answer. This difference in categorization between literate and illiterate cultures suggests that language does in fact influence the way people think. In particular, this difference is the “commitment of word to space” that Schachtman cites Father Walt Ong Sr. citing in discussion of the transition from oral systems to writing systems (Shachtman 43). The “space” in which this word is “[committed]” finds itself differently structured depending upon language. As Aristotle put it, he envisions the space of “a great building with niches, patterns, details” (Shachtman 42). The Whorfian hypothesis imagines that these “[buildings]” vary in their intricate detail and pattern from language to language, consequently affecting the lens through which one views the world. Although the premise for Schatman’s article is not necessarily to hone in on the Whorfian hypothesis, his overarching discussion allows for much exploration of what the hypothesis does have to offer — content that should not be overlooked since it provides ample insight into understanding a roadblock for women in computer science.
Although this critical period of pain affects both men and women equally in their first introduction to the field, the pervasive nature of Steele’s stereotype threat contributes to women “disidentifying” with their domain, more so than men. At least, the prevalence of men in the industry allows men to feel some degree of comfort that they will be able to overcome their pain due to the overabundance of male role models in the industry since role models “carry the message that stereotype threat is not an insurmountable barrier there” (Steele 625). As a result, these men feel that they, like the other male role models, can overcome the pain and succeed. However, the very conspicuous gender disparity of women in CS doesn’t provide women with the same number of examples to motivate them to stay. When women juxtapose their difficulty during the critical period with the fact that there are not as many women in the tech industry, these two pieces only serve as confirmation that perhaps CS is not for them.
Embracing this time of especial initial difficulty is essential to later success and enjoyment in the field. Sometimes, professors recommend that individuals “struggle” through a problem because learning how to deal with pressure and the uncertainty of a problem only makes one a stronger programmer. Although there is certainly a line to be drawn at which it is very essential to ask questions, it ought to be acknowledged that many professionals recommend embracing this critical initial process of pain since computer science in its nature often welcomes unpredictable problems during the coding process.
Women in particular are likely to take the easy way and out and resort to the help of a more experienced coder during this time period, seeing it as a reflection of their own inabilities and inadequacy. For example, a friend of mine (taking her first computer science course) found herself stuck on a difficult programming assignment. Although there is no denying that she didn’t work hard on the project, her immediate willingness to go ask a male friend to finish it for her almost discredited all of her previous hard work and thought into the assignment. Women need to have more sustained confidence in their ability to succeed no matter how uncertain any prospect of success like that may seem. But when one does choose to ask for help, she ought to be aware of how to ask for help. In particular, she ought to ask for help in a way that doesn’t detract from her learning, but only compliments it.
As a speaking fellow, I aspire to teach the fellow women around me to achieve these two main components: how to have more faith in oneself despite the ever prominence of such impending stereotypes threats and how to ask for help in meaningful ways that will empower one in the learning process. That involves using effective rhetoric to ask relevant, detailed and specific questions that support the learning process. My goal is not to impose upon anyone my passion for computer science, nor proclaim that computer science is the best field to pursue. However, my goal is to show people that there is no such thing as not having the “mind” for something. I reject the notion that one simply is not a “technical person” simply because I used this familiar argument to reason against any pursual of computer science initially. I hope that women will bask in the glory of the notion that they can do anything and not feel intimidated by underlying social threats or intellectual challenge. Although I’ve centered this narrative around computer science, perhaps these universal skills of gaining unwavering confidence to overcome societal threats, and knowing how to communicate in meaningful ways, can apply to several contexts beyond computer science.
Steele, Claude M. “A Threat in the Air. How Stereotypes Shape Intellectual Identity and Performance.” The American Psychological Association, 1997. Print.
Shachtman, Tom. “The Inarticulate Society: Eloquence and Culture in America.” (1995): 39–63. Print.