Currently, one of my project teams is working on a report using data where respondents could select more than one race category. We are trying to decide if we should count anyone with more than 1 race in a “two or more races” category, count race identity combos that come up frequently as separate categories, or do a duplicate count with an additional box/graph that shows the number who identified as more than one race. Some of our sites have relatively high numbers of certain race combos, and it doesn’t feel equitable to lump all of these individuals into a “two or more races” category, but we wanted to ask to see if there was any advice/resources/experiences that others have had that we could consult.
Hello there, we are dealing with a similar challenge on handling multiple option selections - I expect that this is a frequent concern. I found this article helpful: A Practical Approach to Using Multiple-Race Response Data: A Bridging Method for Public-Use Microdata - PMC as well as this Pew Research Centre overview: 1. How different weighting methods work - Pew Research Center Methods | Pew Research Center, both of which seem dependent on high volume of data. I hope this is helpful and would be pleased to further collaborate and share. Thank you!
Great question @etaber2! We strongly encourage the minimization of catch-all categories if at all possible. One of the key elements to figuring out how to handle this situation is to spend a little bit of time getting very clear on what it is you’re trying to measure. Is it a common culture? Is it an experience of racism? Is it another type of experience? This will help you understand the best way to group folks who don’t identify as a single race.
I really love the article that @lisapurdy shared. I’ve just finished reading it and I think we should consider creating a summary and an example from this article for the We All Count website. Thanks for finding this!