I love a good polemic but lately I have been disappointed by polemics as a genre because they generally don’t ground themselves on data at a suitable scale.
When people try to write about a social problem, they are likely to use potent examples as a rhetorical device. Their particular ideological framing of a situation will be illustrated by compelling stories that are easy to get emotional about. This is often considered to be the hallmark of A Good Presentation, or Good Writing. Somebody will say about some group X, “Group X is known for doing bad things. Here’s an example.”
There are some problems with this approach. If there are a lot of people in Group X, then there can be a lot of variance within that group. So providing just a couple examples really doesn’t tell you about the group as a whole. In fact, this is a great way to get a biased view of Group X.
There are consequences to this kind of rhetoric. Once there’s a narrative with a compelling example illustrating it, that spreads that way of framing things as an ideology. Then, because of the well-known problem of confirmation bias, people that have been exposed to that ideology will start to see more examples of that ideology everywhere.
Add to that stereotype threat and suddenly you’ve got an explanation for why so many political issues are polarized and terrible.
Collecting more data and providing statistical summaries of populations is a really useful remedy to this. While often less motivating than a really well told story of a person’s experience, it has the benefit of being more accurate in the sense of showing the diversity of perspectives there are about something.
Unfortunately, we like to hear stories so much that we will often only tell people about statistics on large populations if they show a clear trend one way or another. People that write polemics want to be able to say, “Group X has 20% more than Group Y in some way,” and talk about why. It’s not considered an interesting result if it turns out the data is just noise, that Group X and Group Y aren’t really that different.
We also aren’t good at hearing stories about how much variance there is in data. Maybe on average Group X has 20% more than Group Y in some way. But what if these distributions are bimodal? Or if one is more varied than the other? What does that mean, narratively?
It can be hard to construct narrations that are not about what can be easily experienced in one moment but rather are about the experiences of lots of people over lots of moments. The narrative form is very constraining because it doesn’t capture the reality of phenomena of great scale and complexity. Things of great scale and complexity can be beautiful but hard to talk about. Maybe talking about them is a waste of time, because that’s not a good way to understand them.