Alice Wu, a doctoral student at Harvard conducted a groundbreaking Master’s thesis that used machine learning to look at over a million posts on EconjobsRumors.com, a site where economists ‘gossip’ about upcoming roles and the industry as a whole. Because so many informal conversations have migrated to the online space, it offers us a statistically significant amount of anonymous water-cooler talk amongst professionals. Using machine learning technology, she looked at the 30 most commonly used words when people were discussing women and men. As explained by economics writer Justin Wolfers in the New York Times, horrifically, the top 10 for women were: hotter, lesbian, baby, sexism, tits, anal, marrying, feminazi, slut and hot. The top ten words for men however do not make for such uncomfortable and hostile reading and include positive words relevant to economics such as: adviser, Austrian (a school of thought in economics), mathematician, pricing, textbook, Wharton (Donald Trump’s alma mater), goals, greatest, Nobel.
Interestingly, the male list also has a gendered tone with words suggesting competition amongst men at the forefront such as bullying, burning and fought. Ms. Wu states ‘the anonymity of these online posts eliminates any social pressure participants may feel to edit their speech’ and so perhaps allowed her ‘to capture what people believe but not would not openly say’. She’s been criticised for her sample population and while her sample may not represent the economics community as a whole, it is very worrying for two main reasons. First, as we’ve seen in politics even a vocal minority can shift a culture when allowed to spread falsehoods. Anonymously sourced gossip can spread like wildfire, harming people’s careers. The second reason for concern is that the people most likely to use this particular online site are younger on average – suggesting that waiting for better behaviour from seemingly more progressive millennials to ’trickle down’ is not sufficient. Third, economists make decisions every day about what topics to research, which data to assess, which social & business issues deserve public attention that like everyone else are borne out of their personal biases. These results don’t make for optimistic reading as to how they’ll regard the topics that will affect both women and me in the years to come.