So, after I left AIDS, I got thinking about how homophobia, as a societal norm, affects health. Not just queers' health, but how it also affects the health of the whole population.
In my last post, I talked a bit about my journey through thinking about health disparities, and how nobody seemed to be measuring the causes of these disparities. That leads directly to my doctoral thesis, which was about how to measure normative heterosexuality, and from there, estimating the impact of it on suicide. Not just on "gay" suicide, but suicide in the whole population, and also in various sub-populations defined by sex, age, and race/ethnicity.
So, following the lead of thinking about residential segregation by race/ethnicity, and income inequities, I began thinking about how to measure normative heterosexuality, the presumed cause of the health disparites that epidemiologists had begun to document with greater and greater precision.
How do you measure the degree to which a group of people (a large group of people) share a rigid set of beliefs about sex, gender, who ought to be having sex with whom, and how? My first thought was that the frequency of hate crimes directed against gay men would be a good measure. If this set of rigid beliefs dominated a social setting, then the informal "enforcement" of those beliefs would be enacted through the commission of bias-motivated crimes, presumably mostly by young men with "something to prove".
When I pulled the data down off the FBI's Uniform Crime Reporting (UCR) System, I quickly realized something was amiss. San Francisco had by far the highest number of anti-gay hate crimes in the country, and several Southern and Mountian states reported not a single one.
I've put more recent statistics by state in a table, based on numbers from 2004 to 2008, the five most recently reported. Basically the same trend holds - bias-motivated crime tends to be higher in places we think of as gay-friendly, and extremely low in the deep South. Then there are also strange jurisdictional oddities - Pennsylvania for example appears to have an extraordinarily low rate of bias-motivated violent crime.
The way I've come to understand this data is that it represents not the phenomenon of crime occurring, but rather on two phenomena: 1) how comfortable victims feel about reporting a bias-motivation to law enforcement, and 2) local law enforcement customs and legal constraints about recording and validating these reports. If it was just the first of these, then one could use the reporting of hate crime as a measure of homophobia at a societal level, that is the more hate crime reported in an area is evidence of how little homophobia there is there, as perverse as that sounds. But alas that second factor, particularly the bit about jurisdictional quirks in how different local law enforcement agencies deal with the reports that are made to them, really throws the whole thing off.
So, I couldn't use hate crime statistics. But maybe I could use the presence or absence of a law for reporting hate crime statistics that specifically included sexual orientation. Or, how about the presence or absence of a law prohibiting discrimination on the basis of sexual orientation?
So, the next thing I looked at was which states had gay rights laws, and when they were enacted. Various of the states have enacted gay rights laws over the years, the first being Wisconsin in 1981, a few more in the late 1980's, and a lot during the 1990's. Recently, state-by-state gains have slowed considerably, as gay activists have pressed for a national law (ENDA), or been distracted by the marriage thingy.
The point for my purposes is that the enactment of state-wide gay rights laws has been a pretty hotly-contested issue, debated for years within each state's legislature, rather than by a small cadre of legalistic judges, or the flash of public opinion of a referendum. As a result, the enactment of a gay rights law represents something of a local watershed, the point in time at which the balance of adverse consequences for elected officials switches from a net negative to a net positive.
So, looking at the enactment of gay rights laws seemed to hold promise, at least from a theoretical perspective, as a good measure of the broad social environment of a State in regards to the level of normative heterosexuality.
Another potential measure of normative heterosexuality to be considered is public opinion polling. The gay rights law thing seems a bit crude - a yes-or-no variable to measure something which I claimed varied by degree from one place to another, and one time to another within those places. Public opinion polling, on the other hand, offered the promise of a finely-tuned measure of normative heterosexuality. There are some relevant questions that have been asked the same way for decades. For instance, Paul Brewer has examined the time trends in how Americans feel about the "wrong"-ness of same-sex sex, which increased during the AIDS years, followed by a precipitous drop recently, the majority of Americans now saying it is not "always wrong" (small consolation that!).
So, public opinion polling looks like it might be a better "thermometer" to gauge how people feel about homosexuality. And there is longitudinal data to work with, so I could look at changes over time.
On the other hand, public opinion polls, by design, ask the smallest number of people possible in order to get accurate results. Thus a "large" national poll might have only 500 respondents. The GSS from which the data above is generated is a good bit larger than that, but still it is only a few thousand in any given year. A few thousand sounds like a lot of people, but what I needed to do was compare across places, not just time. So a few thousand breaks down into a few dozen in some states, and in others, fewer than ten. It would be a stretch to characterize the whole State of Connecticut based on how 15 randomly chosen people answered a question (for the record, I'm pulling that number out of thin air, but that's about what it comes down to).
So I was stuck with public opinion polling, too. Good temporal trends, but lousy in terms of geographic specificity.
A related idea was to look at how people voted on anti-gay referenda, such as the Briggs Initiative in California in 1978, Measure 8 in Oregon in 1988, and Colorado's Amendment 2 in 1992. These explicitly anti-gay referenda had the advantage of high geographic specificity, presumably accurate down to the precinct level, but represented a snap-shot in time. Also, they represented a small number of states, and the questions addressed in each one were quite different.
While I was working on my thesis, though, another opportunity to think about voter referenda came up. The issue of same-sex marriage cropped up. Although same-sex marriage has been contested in U.S. courts since 1970, it had never gotten much notice one way or the other - the Christian right didn't feel threatened by it, and most gay acitivists thought marriage was a non-starter politically, or at any rate a horrid reminder of heterosexuality run amok that should not be emulated.
But in 1998, Hawaii and Alaska voters chimed in on same-sex marriage, a few more did in the 2000 and 2002 elections, and then the 2004 election was swamped with voter initiatives to restrict marriage, in part a cynical manipulation by Republic Party operatives in order to keep their guy at the helm.
These referenda share the problem that opinion polling data have, in that they are a snap-shot in time (except for a few states which have had multiple referenda on this issue), but there were major advantages. For one thing, the question being asked was nearly identical in every state, some slight variation on whether legal recognition of marriage should be restricted to "one man and one woman". As an aside, no state has yet offered to restrict marriage to "one woman and one man" - something to consider when thinking about marriage as a forum for liberty and equity. And, the geographic scope was huge, with most states chiming in on the issue one way or another. The map I made here shows how different areas voted, from strongly in favor of restricting marriage (red) to being against restricting marriage (dark green).
On the whole, this map comports more or less with what one would expect, there's more red in the rural areas, more green in urban centers and on the Pacific coast, and there seems to be a trend towards more green in the Northeast. But there are some unexpected spots, too, such as South Dakota, which was substantially less in favor of restricting marriage than its neighbors Nebraska and North Dakota, And Arizona, which was the first state to reject restricting marriage in 2006 (alas, they went to the dark side in 2008).
So, there are some tricky issues to deal with in using this data. I haven't quite figured out how to make it comparable across time periods.
The final method I've thought of for measuring normative heterosexuality is using counts of same sex couples. The number of same sex couples was counted (albeit inadvertently) by the U.S. Census in 1990. For the 2000 Census, they did a better job of it, and the upcoming 2010 Census is expected to do better yet.
In any event, the number of people who identify themselves as married same-sex partners and un-married same-sex partners in the Census is probably mostly a factor of three forces: 1) How comfortable people in same-sex couples feel identifying themselves as such on the Census forms; 2) The degree of selective in-migration and out-migration of people in same-sex couples (or destined to join one), and 3) The degree of confusion by people in mixed-sex couples who inadvertently identify themselves as same sex partners.
The first two of these factors (net migration and comfort identifing as a same-sex couple) are related to what I want to measure - how accepting an area is of homosexuality. The third factor is a pain in the butt, not in a good way. I've discussed that issue at length before.
So, counting same-sex couples has two huge advantages: it uses the same methodology for the entire United States, and you can get comparable data down the the neighborhood level (census tracts). On the other hand, the data itself has some big caveats - it doesn't identify young people, single people, or couples living in separate residences, and it is essentially useless when considering older people (for reason 3 above). And although there will soon be three time points to compare, the methodology has changed in each Census, and it remains to be seen if the 2010 Census data will be comparable to the 2000 Census data (probably not, but for the reason that the methods are becoming more accurate).
So, in the end, I decided to pursue three measures of normative heterosexuality further:
1) The enactment of gay rights laws,
2) How people voted on referenda to restrict marriage to one man and one woman, and
3) The proportion of same-sex couples identified in the Census.
More to come...