People from all corners of the technology world (and beyond) have offered their take on the topic of women in tech, from Paul Graham’s infamous summation to Sheryl Sandberg’s Lean In empire. Even Louis C.K. has thoughts on the matter.
We recently analyzed Meetup data to see what we could learn about the global tech scene. This inspired us to go a level deeper. We wanted to use this same data set to see what Meetup patterns might tell us about the state of women in tech.
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So do we. Our data journalism has been cited by The New York Times, The Wall Street Journal, and Fast Company.
How we got the data
For the first round of Meetup analysis, we used Meetup’s publicly accessible API, downloaded the data for every global meetup in the technology category, and analyzed it in RJMetrics. To analyze gender data, we had to get a little more creative.
Meetup will, via its public API, tell you the member name for every member in a public group. (Pause for reader to unsubscribe from all controversial meetup groups.) The API won’t give you much beyond name, but fortunately, that’s all we needed: about 75% of users supply a name that maps to a name as recognized by the US Census Bureau. We mapped name data to census data to arrive at gender.
One more data-gathering challenge: Meetup is huge. There are thousands of tech meetups, many with thousands of members—many millions of total tech meetup memberships. We couldn’t pull every single member for every single group. Instead, we chose the 50 biggest cities, and pulled the members for the biggest group in every city.
Typically the biggest group in a given city is a large group with general membership that is representative of the overall tech scene. The biggest of all tech meetups, the New York Tech Meetup, fits this model nicely, as does our own Philly Tech Meetup. Using these groups as a proxy for overall city population seems reasonable to us.
Women in tech
According to our analysis, women make up 29% of the tech community. This matches up closely with other data sets. 2011 census data showed that 25% of computer workers were female and data from the Bureau of Labor Statistics reported this year that 26% of computer and mathematical occupations are held by women. Sanity check: passed.
Cities going beyond the 29%
It’s clear that women still comprise a minority in the tech industry, but we were interested in exploring the cities that broke the mold. Out of the top 50 biggest tech centers in the US, which cities’ tech communities are more than 29% female?
17 of the 50 major tech centers in the US have higher-than-average numbers of women in tech:
|Nashville||43.49%||Miami||40.33%||Dallas||39.97%||Phoenix||37.63%||San Mateo||34.60%||Houston||34.25%||Portland||32.66%||Atlanta||32.34%||New York||31.90%||San Jose||31.09%||Palo Alto||30.19%||Seattle||29.89%||Austin||29.65%||Baltimore||29.65%||Washington||29.00%|
The first thing we notice about this list? Las Vegas is the only city where women make up the majority in tech.
What makes Vegas so special?
In Las Vegas, women make up 65% of the tech scene. This is the only top tech center where women are the majority. Why the anomaly?
Outside of the tech bubble, Vegas is a welcoming place for females on a number of fronts. For one, the city has had a female mayor, Carolyn Goodman, since 2011. Across the country, only 18.4% of cities with populations over 30,000 can claim that level of female leadership. Additionally, Nevada ranks highest in the nation for gender paycheck equality, with women earning around 85 cents on the dollar compared to men.
The female mayor piece got us thinking about the other cities on the above average list. So we did some counting:
|Las Vegas||female mayor|
|San Mateo||male mayor|
|New York||male mayor|
|San Jose||male mayor|
|Palo Alto||female mayor|
We thought we might be onto something. To confirm, we ran a regression analysis on the 50 biggest tech cities. What we found is that a female mayor is positively correlated with more women in tech.
Other research corroborates that female leaders in civic roles influences the educational choices of younger females. Of course it’s worth noting that female mayors is by no means the primary influence on women in tech. A city is an ecosystem and big changes tend to happen as a result of many small factors shifting.
Do female group leaders matter?
Buoyed by our discovery on the impact of female mayors, we wanted to further examine the impact of female leadership. 22% of all tech Meetup groups are led by women. Are these groups more likely to have higher numbers of female members?
We regressed the percentage of female group members against the gender of the leader of that group. The answer? No dice. Having a female group leader doesn’t lead to greater female membership based on our data. While a female mayor is correlated to more females in tech, we can’t say that the same relationship plays out at the group level.
How does a city’s tech density impact female membership?
When we first starting looking at Meetup data, we were curious what the most densely concentrated tech centers were. Not surprisingly, Palo Alto tops this list:
|City||Meetup % of Population|
|Palo Alto, CA||148.62%|
|Mountain View, CA||92.49%|
|Cambridge, MA||48.45%||San Francisco, CA||47.95%||Santa Monica, CA||36.30%||Princeton, NJ||32.55%||Boulder, CO||30.56%||Sunnyvale, CA||22.40%||Menlo Park, CA||16.95%||Herndon, VA||16.53%||Oak Brook, IL||15.94%||Washington, DC||15.49%||Vienna, VA||14.62%||Santa Clara, CA||14.60%||Addison, TX||14.17%||Hoboken, NJ||13.91%|
Our top cities by women in tech, however, are mostly absent from this list. Is there a connection? Do tech-dense cities have fewer women in tech?
We ran another regression analysis of the density of a tech scene vs. the % of female membership. Tech density has a small negative impact on the number of women in tech, but it’s not statistically significant.
We certainly think the disparity in these lists is interesting, and we don’t consider our analysis exhaustive. The data is out there for anyone who wants to dig deeper!
The future of tomorrow’s tech centers
The reasons keeping more females from getting involved in tech are complex. They range from the “brogrammer” culture of the industry to educational systems that discourage women from pursuing STEM programs. Solving this problem isn’t just beneficial to women who want good, high-paying jobs; it’s beneficial for the entire tech industry.
It’s quite possible that Vegas, Oakland, Nashville, and other cities exceeding the 29% standard will have an advantage in the coming years. By creating environments conducive to women in tech, they’re expanding the size and diversity of their technical human capital.
As with any complex issue, we think that the most productive conversations include a healthy dose of real data. We hope these new data points we’ve uncovered will help develop productive conversations in the hundreds of tech communities that are thriving around the world.