Roberto Bedoya has asked some amazing questions lately, all designed to interrogate the concept of whiteness in the arts. He’s asked a few bloggers to think about the questions he has raised and write back (so watch for posts in the coming weeks on Jumper, Createquity, Barry’s Blog, Engaging Matters, Museum 2.0, etc), and this is mine. Or at least my first attempt.
Before going into it though, I think it’s important to say that I feel a little like a lamb in the woods on this diversity stuff, not so much because I am innocent to the effects (or causes) of casual racism as because I was naïve about the extent of the issue. As I continue to delve into this data, much of which (at least in relation to race—other forms of diversity, which I’m also looking at, are not really touched on here) paints a picture where whiteness, this giant mass that surrounds almost all institutional arts presenting in the US today, should be excruciatingly obvious, and is instead so large and ever-present as to become invisible, like air.
I am afraid that I find myself, as I work through some of this information, losing my words at both the monumentality of the problem and at the systemic nature of the disparity. It has me asking all sorts of questions about will and form—are we really so stubborn as to not change? What does “change” mean, and would it actually make our art more appealing to these large swaths of people who aren’t coming?—and about time, and energy, and coordination, and money. Like all clarity, or partial clarity, seeing the true weight of the whiteness in the arts, illustrated in numbers and graphs, analyzed and parsed, is both exciting for its inherent opportunity and terrifying for the scope it reveals. Where the air is cold and thin, and the wind pushes the clouds away, you can suddenly see all the other mountains you aren’t climbing, and you can fall or you can fly.
The weight of whiteness in the arts is about 15 percentage points. It only weighed about 10 percentage points in the early 80’s, but now, well:
This is a comparison of the percentage of non-whites in the general US population (wide-dotted red line), the general Bay Area population (narrow-dotted red line) and the US theatergoing population (black line) comparing 1980 to 2010. That black line is weighed down, depressed below the general population, slowly diverging from it further over time, by the weight of the whiteness of our theatres.
It’s a stark picture, I think.
This is a comparison of aggregated demographic data on 532,000 theatre attendance records in the San Francisco Bay area spanning 2006 to 2012. This data comes from 25 theatre companies, 137 total seasons. The theatre companies range from LORT houses to under $150,000 per year annual budget, present all types of work, and are distributed among 5 Bay Area counties.
The table shows, in red, the average racial demographics of the half-million audience records, and in black, the average demographics for those 5 Bay Area counties per the 2010 US Census.
In this case, the weight of whiteness is 46 percentage points.
I’ve got to say, going into all of this analysis, I didn’t think it would be quite this bad.
This one does away with percentage points and converts it to something I’ve developed called the Arts Diversity Index. It takes the relative diversity (in this case, race/ethnicity diversity) and converts it into a standardized score where 1.0 is as diverse as possible (which is to say, complete parity) and 0.0 is as homogeneous as possible (which is to say, only one race). The green bars are the average ADI scores for each county’s theatres in the study, with variance indicated by the boxes and lines. The red dots are the ADI scores for the general populations of each county using US Census figures. The only place we’re coming close is in Marin County, and then only because it’s so relatively racially homogeneous.
Giving Whiteness Context
As a corollary to this data analysis that forms the core of the report I’m writing, we also surveyed our theatre company members in the Bay Area to understand what the diversity of their boards, staffs and artists were like. To date, 54 companies have provided data on their boards, staffs and artists for the season ending in 2012, with the following results:
While it is difficult to make any definitive conclusions because the audience data is drawn from a different sample of companies than the rest of the data, this information is encouraging and discouraging at the same time. On the encouraging hand, the percentage of white people serving on the boards, staffs and shows of the survey respondents is actually below the percentage of whites in the overall US population and, in most categories, close to on-par or below Bay Area percentages. On the discouraging hand, despite these great numbers, audience data indicates we’re still seeing an absolutely staggering lack of diversity all the same.
Interesting, and apropos of Diane Ragsdale’s post on coercive philanthropy, we asked these companies whether they had received direct or indirect pressure from funders via program officers or granting guidelines to diversify. When filtered to reflect those that had versus had not gotten pressure, here’s what the table looks like:
What strikes me about this table is how close the percentages are. The pressure, when it exists, exists in companies where more of the board, staff and artists are white (generally). Regardless, and with a caveat that further study is really, really necessary here, the diversity of the people making the art doesn’t seem to really get reflected out into the seats.
What Affects Whiteness?
So what does affect whiteness? As part of this research, we cross-referenced the audience numbers with the California Cultural Data Project (as well as with the other types of diversity we were looking at), and found some interesting correlations.
(For the sake of this blog post’s legibility, I’m going to spare you the p-values, but all of these relationships were determined to be statistically significant. It’s also important to note here that correlation and causation aren’t the same thing—we can’t say that more differently-aged people caused there to be more racial diversity—but what this basically means is that where one was high, the other was high, too.)
– Racial/ethnic diversity was positively correlated with:
- household income diversity
- age diversity
- marital status diversity
– Racial/ethnic diversity varied in statistically significant ways based on:
- the age of the company. The older a company was, the more racial diversity existed (though as you can see below, this difference was marginal at best—but still statistically significant).
- the size of the company’s annual budget. The larger the company was, the more racial diversity existed.
- the average ticket price. Very cheap and very expensive tickets yielded more racial diversity than in between.
So, What’s That All Mean?
Well, honestly, I’m not sure yet. But what it provides, in a way, is a lot more specificity about where the meager amount of racial/ethnic diversity that does exist is coming from. Company budget size is highly correlated with age, which basically means that the larger companies within this study, probably more by virtue of being more known and more “mainstreamed” to more people, demonstrate slightly more racial and ethnic than smaller companies. While increased racial diversity correlating with marital status seems somewhat random to me (I need to think about that one more), the fact that it correlates both with age diversity (which, in this sample, is the same thing as saying “more young people”) and household income diversity (which, in this sample, is the same thing as saying “more less-wealthy people”) makes sense—we know that younger people generally are more diverse, and that both younger people and non-white people are generally less financially well-off.
It’s interesting to me that we only really see increased racial diversity among the very cheapest tickets, and then not again until the largest category. It says that the idea of discounting may only work when you’re talking about a price that is untenable to a company of any real size.
Which is all to say, the goal of this report isn’t to necessarily provide all the solutions. It’s to give people a hard, data-driven and statistically tested baseline from which to start a very complicated conversation. I’m pleased that the blogosphere is carrying forward with it, and I hope very much that once the report is out there in the world, arts communities across the country will engage with it as well.