Welcome to the first post of our new series Mansplain Monday wherein we post and discuss some of our “favorite” examples of mansplaining that we have come across during the week.
For the first Mansplain Monday I want to get a little bit personal. For those of you who are regular Skepchick readers, you know that I post a lot of very technical articles that are often math and statistics heavy. Statistics and economics are part of my expertise, so it makes sense that many of my posts will focus on those topics. However, I’ve noticed that almost any time I discuss something quantitative on Skepchick some dude crawls out of the woodwork to mansplain to me why I’m wrong about everything.
My most recent stats-related post was on why the supposedly “scarily accurate” model that predicted a 98% chance that Trump will win the presidency was not actually very accurate. I explained what models were and why the one they were using in this case wasn’t very good along with explaining why the supposed “accuracy” of the model was incredibly misleading. I got mostly positive feedback on that post, but as usual it didn’t take long for some dude to jump in on the Skepchick Facebook page and mansplain statistics to me:
So, you don’t use the words data mining to point out that they’re data mining. LOL. I’m starting to think you’ve never taken a science course.
There are so many ways in which this guy is totally wrong. First of all, just because a person doesn’t use a particular word obviously doesn’t mean they don’t know what they are talking about. Even if the word in question is a more accurate or descriptive word than the words the writer actually used, it still wouldn’t mean her entire article is wrong due to the lack of that particular word.
Secondly, in the case of the model I was writing about, “data mining” would actually be a misleading word to use. “Data mining” is a layman’s term for when statisticians or data scientists comb through huge amounts of data looking for hidden patterns or correlations. However, in the post I wrote the model I was discussing was run on only 26 observations. Not 26 million. 26. Although “data mining” isn’t a very specific term and it doesn’t have a cut-off for what is considered “big data,” I think we can safely say that 26 is probably too low to be able to accurately call what that model is doing “data mining.” It wouldn’t necessarily be wrong for someone to use that term in this context if they chose to, but I personally don’t think it is a good fit to describe that particular model and might even be misleading by giving the idea that the model involved much more data than it did. In general I actually find the term “data mining” misleading in almost any context since it has such an unclear definition, so I generally stay away from it.
If you’re keeping score at home, this dude decided to come in and criticize my post for not using a word that happens to be totally inappropriate to use in this context and from that he decided I clearly didn’t know what I was talking about and “never took a science course.”
I’ve lost count of the number of times I’ve had men completely dismiss me by proclaiming that I clearly have no background in statistics. It’s strange that they would ever get this idea. Many of the posts I write are extremely technical such as this post where I discuss how p-hacking works using an evo-psych study that likely got their results via p-hacking or this post where I explain what instrumental variables are in the context of a study about the effects on teen pregnancy from the MTV show 16 and Pregnant. I don’t know how I would even understand p-hacking or instrumental variables well enough to discuss it in a blog post if I didn’t have a stats background, so it’s odd that this is the assumption that so many men reading my posts make.
I generally assume that I don’t need to attach my resume to every post I write for it to be clear that I have a pretty good idea of what I’m writing about. I’m discussing complex and technical topics in an intelligent manner, so it would make sense for the reader to assume I probably have expertise in that subject. However, it doesn’t stop men from accusing me of speaking outside my area of expertise or being “just a blogger” who doesn’t know anything about statistics or has never taken a science class. Once during a panel at SkepchickCON where I had just spent an hour discussing the economics of various dystopian futures such as one where robots have taken over most of the jobs, I actually had a man during the Q&A flat-out accuse me in front of my fellow panelists and the entire audience of having no academic training in economics. When I told him that I actually had a master’s degree, he demanded to know where from. When I replied with “University of Chicago” he then accused me of lying. Apparently it really is impossible for some men to believe that any woman might actually know what she is talking about or even have background in a subject that outshines their own.
I don’t generally like to drop information about my academic or work background in order to lend myself cachet as I believe my writing should speak for itself, but apparently there are men that will dismiss anything I say until they have perused my resume and declared me qualified enough to speak, so let me be clear that I do have a background in statistics and economics. I have a master’s degree in public policy from the University of Chicago which included extensive advanced statistics, economics and game theory courses. I spent a year working on digital analytics in the Obama Campaign headquarters and now work for a large retail company as a data scientist. I spend my work days combing through incredibly large amounts of data, writing code in various programming languages, analyzing complex datasets, and building predictive models of human behavior. This is what I do. This is my area of expertise. I’m goddam tired of having to deal with men like “Willis” accusing me of “never taking a science course” when it’s really damn likely that I’ve had way more “science courses” than he will ever take in his entire lifetime. I’m tired of being flat out accused of lying about my academic background at a conference for which I was an invited guest. I’m sick of being inundated by tweets from men calling me “just a blogger” in order to dismiss all my actual qualifications. Regardless of how much my writing should speak for itself, these men and men like them are always going to assume that they know more than I do because they are men and I’m a woman. This is mansplaining at its finest.