A novel way of measuring prejudice

[lpetrich]

By counting up Internet searches, because many searchers perceive their searches as anonymous.

Some background:

Lee Atwater - Wikiquote

You start out in 1954 by saying, "Nigger, nigger, nigger." By 1968 you can't say "nigger" — that hurts you. Backfires. So you say stuff like forced busing, states' rights and all that stuff. You're getting so abstract now [that] you're talking about cutting taxes, and all these things you're talking about are totally economic things and a byproduct of them is [that] blacks get hurt worse than whites. And subconsciously maybe that is part of it. I'm not saying that. But I'm saying that if it is getting that abstract, and that coded, that we are doing away with the racial problem one way or the other. You follow me — because obviously sitting around saying, "We want to cut this," is much more abstract than even the busing thing, and a hell of a lot more abstract than "Nigger, nigger."

Interview with Alexander P. Lamis (8 July 1981), as quoted in The Two-Party South (1984)‎ by Alexander P. Lamis; originally published as an interview with an anonymous insider, Atwater was not revealed to be the person interviewed until the 1990 edition; also quoted in "Impossible, Ridiculous, Repugnant" by Bob Herbert in The New York Times (6 October 2005)

The main deal:

Association between an Internet-Based Measure of Area Racism and Black Mortality
Abstract:

Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the “N-word” in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004–2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health.

From inside the paper:

In this study, we examined a previously developed Internet-based measure of “area racism” that did not rely on the provision of responses to survey questions and is less susceptible to social desirability bias; it may also more directly assess racial attitudes in a geographic area [23]. This measure, calculated based on Internet search queries containing the “N-word”, was strongly associated with the differential in 2008 votes for Barack Obama, the Black Democratic presidential candidate, vs. 2004 votes for John Kerry, the White Democratic presidential candidate. Studies have found that Internet searches on other subjects, including religiosity and firearms, reflect socio-demographic characteristics of the underlying population [24, 25]. For example, the percent of a state’s residents believing in God explains 65% of the variation in search volume for the word “God” [23]. Internet queries of health conditions have also been used for disease surveillance, including influenza outbreaks, and have been found to be a stronger predictor than pharmacy records [26, 27]. Socially unacceptable attitudes or actions may also be less likely to be censored on the Internet given perceptions of anonymity, and may in fact serve as an outlet for unpopular beliefs.