Introducing: Identity Sorting Dials

Analysis, Communication & Distribution, Data Collection & Sourcing, Project Design

This article begins a 4 part series on what We All Count calls Identity Sorting Dials.

“If I want to be inclusive on my survey, shouldn’t I use as many identity options as possible?”

“If we want our results to be statistically significant, aren’t we going to need to aggregate our categories?”

“Why wouldn’t I do an intersectional analysis? Isn’t getting more specific categories better?”

“I want to see differences between racial groups, but the sample sizes for the groups I’m most worried about are too small to use!”

“If we want to get results than mean anything at all, we should use an “Other” category for all of the people who don’t fit into the big three groups…”

At We All Count, there are 4 dials that we think about any time we are breaking people out into groups in our data process. We think about them during data collection, during analysis, and during reporting. When we sort people into different “boxes” in our data, we need to be very intentional about what boxes we draw (and why!) and particularly how we are affecting the 4 key considerations in the Identity Sorting Dials.