Class and Data

Amber A’Lee Frost has a post at Jacobin titled “Bro Bash.” The post has many points, but the leading one is well-summarized by that thing that goes under the title, which says “There‚Äôs nothing feminist about leaving numbers to the bros.” Frost criticizes both the tendency to categorically dismiss quantitative approaches to analyzing things and the tendency to suggest it is a man (or bro) thing.

I don’t want to reiterate Frost’s point here because she writes it better than me and so it makes sense to just read her take. I do want to add a class point to it though.

As I’ve written before, all of these Left conversations take place among groups of people who are mostly from high-socioeconomic-status (high-SES) backgrounds. You can back into this conclusion by observing that those engaging in them are mostly people with at least bachelor’s degrees from mostly very good colleges. This is the path of high-SES kids.

It’s not ambitious to suggest that this background and the experiences that go along with it significantly affect their topical interests. This is why we see disproportionate amounts of energy dedicated to the plights of four-year college students, interns, recent college graduates, adjuncts, and people on the bottom-rung of media and other similar high-SES jobs. This is why we get a great deal of focus on cultural and interpersonal oppression, which is the kind of oppression high-SES individuals are more likely to face. And this may also be why more florid, impressionistic, literary takes on things get such a big audience as well in this crowd. They aren’t generally helpful when it comes to specifics, but specifics aren’t that interesting to you when you haven’t personally dealt with them that much.

As someone who comes from a low-SES background however, specifics surrounding the economic structure have always been one of my primary interests. In particular, I have been interested in the specific mechanisms that drive economic inequality. You cannot understand those specifics very precisely unless you dive into quantitative distributive concepts and the historical spreadsheets that accompany them. Labor income stratification, capital income stratification, income life-cycles, and so on cannot be well understood without having figures and manipulating them with math.

Additionally, quantitative analysis is indispensable when it comes to thinking about the various ways to restructure the economy for the better. It’s helpful, for instance, to look at other countries that don’t have the material difficulties we do to figure out why. To do that, you need numbers to actually identify those countries via social statistics. Then you need to decompose the various channels through which they distribute resources to figure out which ones differ and which ones are responsible for their success. This is also not possible without the use of data. I could go on.

The point here is that, perhaps owing to my own personal situation, I find myself much more interested in working through specific plans to cut inequality rather than stories about inequality. That means numbers, a lot of them from a lot of sources. Watching high-SES kids who have no stake in any of this beyond their own self-concept and political identity take a run at that kind of thing is thus pretty hilarious. It always reads to me as if they are demanding a more artistic product that is more pleasurable to their literary-derived reading tastes.