A while back, a writer I like got in trouble with a lot of people who would otherwise be fans over something she wrote:
In it, Dr. Harris-Perry (who I follow on Twitter) lays out an argument for why white voters, who supported Barack Obama in the first election, may be abandoning him now at a greater rate than they did President Clinton in the 90′s – despite the many political and situational similarities between the two. Given that so many of the ostensible reasons for withdrawing support are balanced between the two administrations, racism may explain, at least in part, any differences in voter support and approval. It’s hard to argue that race and racism have not played a role in this particular presidency far more than in others.
Because I liked both this article and a related one that more closely explored the racial attitudes of Bill Clinton more specifically and liberals more generally, I fired a quick message to Dr. Harris-Perry in support, because I knew that she was taking quite a bit of flack for her audacious temerity to suggest that liberals weren’t the immaculate paragons of fairness that we make ourselves out to be. Basically, just a “hey, I liked your piece in the Nation.”
The problem, of course, is that racism is notoriously difficult to pin down as a single causal factor. Because we’ve gotten so good at obfuscating it through clever language and self-inflicted racial blindness, it’s particularly challenging to detect positively. Usually you have to try and remove all other potential causal factors and then measure the size of a racial disparity and say “well this has to be racism, because what else could it be?” That is far less psychologically satisfying than being able to point at something definitively, objectively racist and say “look, there’s your monster”.
Which is why I find this a particularly fascinating exercise:
Can we really quantify racial prejudice in different parts of the country based solely on how often certain words are used on Google? Not perfectly, but remarkably well. Google, aggregating information from billions of searches, has an uncanny ability to reveal meaningful social patterns. “God” is Googled more often in the Bible Belt, “Lakers” in Los Angeles.
The conditions under which people use Google — online, most likely alone, not participating in an official survey — are ideal for capturing what they are really thinking and feeling. You may have typed things into Google that you would hesitate to admit in polite company. I certainly have. The majority of Americans have as well: we Google the word “porn” more often than the word “weather.”
And many Americans use Google to find racially charged material. I performed the somewhat unpleasant task of ranking states and media markets in the United States based on the proportion of their Google searches that included the word “nigger(s).” This word was included in roughly the same number of Google searches as terms like “Lakers,” “Daily Show,” “migraine” and “economist.”
The cool thing about this is that Google functions like the untramelled id of the internet. It is used away from the prying eyes of social norms, when people are their most natural, disgusting selves. Also, the word ‘nigger’ isn’t exactly a word that isn’t unequivocally racist. I can think of a handful of circumstances wherein someone would we looking for information about niggers that doesn’t necessarily reveal a hatred for black people, but the frequency of those types of occurrences is vanishingly small.
So now that we have a measure of racism, and some data to go with it, what do we find?
Once I figured out which parts of the country had the highest racially charged search rates, I could test whether Mr. Obama underperformed in these areas. I predicted how many votes Mr. Obama should have received based on how many votes John Kerry received in 2004 plus the average gain achieved by other 2008 Democratic Congressional candidates. The results were striking: The higher the racially charged search rate in an area, the worse Mr. Obama did.
Consider two media markets, Denver and Wheeling (which is a market evenly split between Ohio and West Virginia). Mr. Kerry received roughly 50 percent of the votes in both markets. Based on the large gains for Democrats in 2008, Mr. Obama should have received about 57 percent of votes in both Denver and Wheeling. Denver and Wheeling, though, exhibit different racial attitudes. Denver had the fourth lowest racially charged search rate in the country. Mr. Obama won 57 percent of the vote there, just as predicted. Wheeling had the seventh highest racially charged search rate in the country. Mr. Obama won less than 48 percent of the Wheeling vote.
Add up the totals throughout the country, and racial animus cost Mr. Obama three to five percentage points of the popular vote. In other words, racial prejudice gave John McCain the equivalent of a home-state advantage nationally.
Now you don’t have to be an economist to see that there are some weaknesses in this methodology. First, this only measures overt racism, not total racism. People in New York and Pennsylvania might be searching for ‘nigger’ less often because even they don’t use that word (despite having strong anti-black feelings). John Kerry and Barack Obama are not the same person, nor did they run on identical platforms, so using him as a comparison has limited utility. There is no way to measure anti-white racism, as there is no real equivalent to ‘nigger’ that can be used against a white person.
All that being said, while we may not know the exact magnitude of the effect that racism played in the last presidential election (or will in the next one), we can certainly say that it is likely to exist.
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