“Women don’t want to be programmers” and other famous myths that serve as common excuses for not setting and measuring specific diversity goals.
There are plenty of myths circling around about why there aren’t more women and people of color in leadership and other male-dominated roles. These excuses may even seem plausible – “That makes sense” – because they confirm common stereotypes about gendered roles and leadership traits. Remember Barbie’s famous 1992 quip, “Math class is tough!” -now a generation of men and women think it is not “normal” for women to excel in STEM.
“Women just don’t want to be programmers! They naturally don’t like STEM. They don’t have the competitive nature to succeed in tech.”
What’s fascinating about this is that for much of the period after programming was invented in the 1940s- women were the programmers. Then came personal computers and the internet, which elevated the status (and pay) for programmers, and the women got edged out. Dank basements full of smelly geeks with no social skills replaced cleaner, brighter, more collaborative programming labs, computers were positioned as toys for boys, and school-age girls were told that math isn’t for them. In Silicon Valley, male programmer and engineers made so much money, their highly-educated wives “didn’t have to work” after having children, even if they once out-earned or had more skills than their husbands. And who would want to work in tech anyway, with beer kegs, pool tables, and scooters roaming the hallways; many women felt it was like going to work in a frat house. Companies decried the lack of available talent in the US and instead of making their environments more inclusive, imported male programmers in droves from overseas. This is how a stereotyped field is born and sustained. Jodi, who spent her early career as a programmer, says she remembers when there was a shift, when elbows were suddenly thrown and women were bullied out of the field. “It was a systematic pressure of exclusion.”
Fast forward to today, and we have a resurgence of women entering STEM fields. Brands like Lego have helped by making building blocks more colorful and little lego people with ponytails, skirts, and multi-racial hair and skin tones. Math education has changed to include more relevant contexts, different types of assessments, and more inclusive role models. And many tech firms have changed from dank basement or frat house environments to open, collaborative and flexible workspaces.
Unfortunately, though, the stereotypes persist and have become an excuse for continuing to sustain a male-dominated power structure in tech and for failing to set and measure change goals for diversity everywhere. “There could be differences in some underlying factor, some input that is relevant to the outcome (for example a sex difference in how much men or women enjoy sports or computer programming) says Greg Lukianoff and Jonathan Haidt in their recent book, “The Coddling of the American Mind” (an otherwise very thought-provoking read). “There are other causal pathways.” They worry that setting outcome goals is equally arbitrary and unfair to the dominate group because the subordinate groups “don’t want those jobs” and would thus be unfairly over-represented. Their justification? There isn’t a need to take into consideration one’s race, gender, and other intersectional identities, because there is already a working meritocracy that fairly selects and promotes the best employees for the role. Basically, anyone could achieve success if they worked hard enough or had enough talent, goes the thinking.
We respectfully disagree. The problem with this perspective is that it is based on a massive assumption that is, as we have described, flawed. It assumes there is a working meritocracy and that the only reason women and people of color are not in certain roles is because they don’t want to be, or aren’t naturally as skilled at those things. What is invisible to these authors – they can both be forgiven as they are members of the dominant group – is all of the forces that have discouraged and pushed underrepresented groups out. Why are there few Black Male hockey players? One would think if there was a working meritocracy, a sport that favors football-style physiques would be dominated by African Americans like the sport of football. Is it because they “do not want to play”? Probably! But that is not because they couldn’t excel at the sport but rather because of a myriad of other forces that have made it not particularly enjoyable in a way that is playing football. If those forces were removed, we suspect the demographics of hockey players would be very different indeed.
Nothing changes in business without outcome-based goals. No leader hones skills that are unrecognized and unrewarded. Nobody changes just because they wish things were different. So, we highly recommend all DEI initiatives include measurement and accountability for outcomes. The goal needs to be increased diversity, equity, and inclusion. It is hard to imagine a measurement for this that didn’t include counting!
Here’s what setting diversity goals does. It motivates women and POC to apply despite any barriers. It motivates recruiters to give their resumes a second look. It motivates managers to make their ongoing workplace experiences better to help mentor people to make them successful. Everyone becomes invested in success. And all of that stuff works! Until we push for a more representative workplace, we won’t be able to disrupt the flawed system that discourages underrepresented groups and negatively influences their ambitions.
Our new book, The Next Smart Step: How to Overcome Gender Stereotypes and Build a Stronger Organization, helps organizations identify where barriers exist in the development pipeline for women, BIPOC, LGBTQ+, disabled individuals, and other out-groups by providing a framework that pairs accountability with training and organizational change.
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