As I’ve mentioned many times, I hold a lead position on The Ace Community Survey. One of the things we track, is ethnicity/race. Many years of dealing with that nightmare of a section has greatly impressed upon me the complexity and ambiguity of the concepts.
One of the big complications is, we’re an international survey. Well, the survey is in English and recruits from English-speaking online communities, so it tends to be biased towards predominantly White countries and the US in particular. But you know what they say about race being a social construct? The primary consequence is that different cultures have constructed race in different ways. The secondary consequence is that even within a single country there are multiple interacting constructions of race. There’s basically no neutral way to ask about race, nor analyze the results.
So I’m going to talk about the ins and outs of race, drawing upon my experiences with our international (but US-dominated) survey.
Our survey questions
You can take a look at our 2018 survey questionnaire; race, ethnicity, and nationality are addressed on pages 5-19.
- We ask people to write in their race and/or ethnicity.
- We ask people to choose any number of racial/ethnic categories from a long list of options. The list consists of various racial categories common in the studied population (e.g. Brown, White, Jewish), and various regions of the world (e.g. North African or Southeast Asian).
- We ask people if they’re an ethnic minority in their community, and then in their country.
- We ask people for their primary country of residence. Basically this is a nationality question, but asking about nationality gets complicated for multinational people.
- For the three most common countries (US, UK, and Canada), we ask a set of questions based on the national censuses of those countries
When we started out, we just asked for nationality, and then the national census questions. This is necessary, because we’d like to compare our data to national census results, which requires asking questions in a similar way. And yet, it was unsatisfactory, because national censuses have a few strange ideas about race and ethnicity. So that’s why we added sections 1, 2, and 3.
Although the US, UK, and Canada are culturally quite similar compared to other parts of the world, there are already slight differences in how they model race and ethnicity.
In the UK Census, the major ethnic categories are: White, Black, Asian, Other, and mixed. Each category is further subdivided. White includes “Irish” and “Gypsy or Irish Traveller”, and everyone else is “Other White”. There are several Asian subgroups, but one thing that might surprise US readers, is that the biggest Asian groups are Indian and Pakistani–the word “Asian” makes most people in the UK think of South Asian groups, rather than East Asian. “Black” includes “African”, “Caribbean” and “Other Black”. The only named subgroup of “Other” is “Arab”.
The Canada Census has a more expansive list of groups–which are not called ethnic groups but “visible minorities”. The visible minorities are: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean, Japanese, other, and multiple of above. They also measure a few Aboriginal groups, which are considered ethnic groups rather than visible minorities. White is defined to be those who are neither a visible minority nor Aboriginal.
In the US Census, the major racial categories are: White, Black, American Indian or Alaskan Native, Asian, and Native Hawaiian or other Pacific Islander. If you’re in at least two of those categories, then you instead get placed in the “Two or more races” category. Hispanic and Latino are not considered races, but ethnic groups, and are asked about separately. So apart from the “White” group, we also have the “White, not Hispanic or Latino” group.
So, let me observe some differences. First, in the UK it’s called “ethnicity”, while in Canada it’s called “visible minorities”, and in the US it’s “race”. The Canada and the US also have a separate concept of “ethnicity”, a seemingly arbitrary distinction between some racial/ethnic groups and others. You also might notice differences in granularity, with the UK using the broadest categories, and Canada choosing to spell out a lot more distinct groups.
Finally, there are differences in which groups are even counted. For instance, the Canada Census cares a lot about Canadian Aboriginal groups, but the other countries do not. The US has several Native groups that the other countries do not. And the UK doesn’t have a Latino group.
Race in the US vs Race in the US Census
The differences between the three censuses are indicative of how race is differently understood in the different countries. But also, each census isn’t entirely accurate to how race is actually understood in that country. I can’t speak to the UK or Canada, but in the US, there are some pretty glaring issues.
First of all, the distinction between race and ethnicity is bogus. Because Hispanic and Latino are not considered “race”, they’re omitted from the question about race, which tends to really confuse Hispanic and Latino people. The real purpose of asking about Hispanic and Latino origins in a separate question, is that the census didn’t allow people to select two or more races until the 2000 Census. So it was a way for people to select Hispanic/Latino and something else, and be counted as both things. Even now, combining ethnicity and race questions would be problematic, since a lot of Hispanic/Latino people are mixed, and therefore would be placed into “Two or more races” instead of “Hispanic/Latino”. Which, is a problem that already affects other groups, especially decreasing the count of American Indians, and the count of Asian people in Hawaii.
The second biggest problem in my opinion, is a lack of accounting for people who are Arab, or from the Middle East or North Africa (MENA). Arab and MENA are not among the options for race, and the stance of the US Census is that such people are “White”. I’m not sure how they’re actually categorized in practice, but I suspect many of them end up in the White category in one way or another. It’s funny because some of these people definitely don’t have light skin, and would not be read as White in real life. Even the ones with light skin might not be read as White any more, not since 9/11.
There’s some tricky politics in there. NPR says that MENA groups have been pushing to add a MENA category for a long time. But at the moment, some people are worried that the Trump administration would add it and then use it for evil. The Trump administration for its part, mostly just wants to count more people as White, to contribute to the perception that White people are still holding onto dominance. Oh, and the Trump administration wants to add a citizenship question, which will not actually get accurate numbers on citizenship, will discourage people from responding, and reduce representation of blue states and districts. Yeah, that’s a thing.
Let’s back off from the politics, and ask some broader questions about how race and ethnicity are understood. There aren’t any right answers to these questions, instead I’m identifying questions that different cultures might have different ways of answering.
- Are race and ethnicity distinct concepts? Which categories are racial categories, and which ones are ethnic categories?
- Is race/ethnicity distinct from nationality? This is not so much an issue in the US, UK, and Canada, but in other countries the concepts are often partially collapsed. For example the Japanese Census only asks about nationality.
- How granular should each group be?
- How do we deal with mixed people? For instance, I’m White/Chinese/Filipino, should I be counted as both White and Asian, just one, or just a separate “two or more races” category? Next, consider the case of a Chinese/Filipino person, who might be considered mixed in Asia, but in the US is just considered Asian.
As far as granularity goes, there’s effectively no bottom. The other day, I was reading about how there are over 300 native ethnic groups in Indonesia. Obviously in the US we can’t tell. We don’t know enough Indonesian people, and barely understand the distinction between Indonesia and India. (Hint: India is the 2nd most populous country in the world, Indonesia is the 4th.) I think there’s a tendency to collapse these “exotic” groups into very broad categories that they would not have chosen themselves.
On the flip side, there’s also a tendency for “dominant” groups to collapse themselves all into a single category. Like how in the US all these distinct groups consider themselves simply “White”. Or in Japan, most Japanese nationals ignore ethnic differences and just consider themselves “Japanese”. I also want to use China as an example, but China has a lot of things going on, and I hardly feel qualified to comment.
How our survey interprets race
In the context of a survey, there are two distinct levels of granularity: the level of granularity used to write the survey questions, and the level of granularity used to analyze and report the results. I’ve already described the granularity we used for the questions, but what about the analysis? If you want the details, you can read our report on the 2016 survey, pages 11 to 15. Honestly it’s too much to explain here.
But I’ll note a few general strategies. First, we believe in reporting on multiple levels of granularity. This increases the number of tables and makes it more confusing, but hopefully more people can find the statistics relevant to them. In the US, UK, and Canada, we include analyses that are identical to those of their respective censuses, for comparison purposes. For international data (that is, the entire pool), we include an analysis based on US-centric categories (although not quite the same as the ones in the US Census).
Maybe using US-centric categories is cultural imperialism or something. But the idea is that the cultural imperialism is already occurring, and we’re just trying to describe it. These people are from all over the world and have different concepts of race, but they’re still occupying these online communities that are dominated by the US and culturally similar countries, so they get read through that lens whether they like it or not.
So there you have it. Race. Much credit goes to Bauer McClave for her work on this part of the survey.