lead linguistic change, in dozens of specific changes in specific cities and regions. Young women are also consistently on the bleeding edge of those linguistic changes that periodically sweep through media trend sections, from uptalk (the distinctive rising intonation at the end of sentences?) to the use of “like” to introduce a quotation (“And then I was like, ‘Innovation’”). The role that young women play as language disruptors is so clearly established at this point it’s practically boring to linguists who study this topic: well-known sociolinguist William Labov estimated that women lead 90 percent of linguistic change in a paper he wrote in 1990. (I’ve attended more than a few talks at sociolinguistics conferences about a particular change in vowels or vocabulary, and it barely gets even a full sentence of explanation: “And here, as expected, we can see that the women are more advanced on this change than the men. Next slide.”) Men tend to follow a generation later: in other words, women tend to learn language from their peers; men learn it from their mothers.
What’s less clear is why. Lots of reasons have been proposed, from the fact that women still dominate the caregiving of children in the societies studied, that women may pay more attention to language to compensate for relative lack of economic power or to facilitate social mobility, and that women tend to have more social ties. But in many cases, gender (like age) seems to be a proxy for other factors related to how we socialize with each other.
Several internet studies have highlighted the importance of differentiating between gender and social context. One study, by linguists Susan Herring and John Paolillo, looked at how people write blogs. At first, it seemed like there was a significant gender difference in the language of blogs. But when they looked again, the linguists found that what was really going on was a genre difference: men were more likely to write topic-based blogs and women more likely to write diary-style blogs. But of course, there were also many people who didn’t pick the genre most typical for their gender. When the researchers compared within each genre, the original “gender” difference disappeared.
Another study, looking at a corpus of 14,000 Twitter users, and guessing their gender based on the skew of their first name in census data, appeared at first glance to show clear gender differences: people with predominantly female names were more likely to use emoticons, for example, while people with male-associated names were more likely to swear. But when the researchers looked one step further, they found that the words people most often tweeted formed natural clusters into over a dozen interest groups, such as sports fans, hip-hop fans, parents, politics buffs, TV and movie fans, techies, book fans, and so on. True, many of the groups had a gender skew, but none of them were absolute, and they also had clear associations with other demographic factors like age and race. Sometimes whole groups defied gender norms—men overall tended to swear more, but techies, a cluster that was male-dominated, didn’t swear much at all, presumably because they were using Twitter as an extension of the workplace. At the individual level, people followed the norms of their clusters rather than their genders—a woman in the sports cluster or a man in the parenting cluster tweeted like their fellow sports fans or parents, rather than like an “average woman” or “average man.” Moreover, restricting the analysis to accounts with names that showed a clear gender skew in census data excludes precisely those users that would complicate a binary view of gender, including nonbinary people and others who’ve deliberately chosen a non-census-gendered username.
Offline, ethnographic research has also pointed to the importance of network factors. Linguist Lesley Milroy was doing a pretty standard study of language change in a couple working-class neighborhoods of Belfast, Northern Ireland. As with many communities, the young women were leading a linguistic change—in this case, changing the vowel in “car” to sound more like “care.” This vowel is common elsewhere in Northern Ireland, but it was new to this particular community, and it was the young women who were bringing it in. What was mystifying was how they were getting it. When Milroy asked the women who they were close to, they named friends, family, and coworkers, all from their neighborhood—the same neighborhood where no one else yet had this vowel change.
In a later paper with James Milroy, the two figured out why by linking linguistic change