Demographics, not biases, best predict traffic

image: Calvin Lai, Assistant Professor of Psychological and Brain Sciences, Arts and Sciences, Washington University in St. Louis
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When it comes to predicting how often black drivers will be stopped by traffic police versus how often white drivers will be stopped, it’s better to look at census numbers than to ask people what what they think of other races.

New research from the lab of Calvin Lai, an assistant professor in the Department of Psychological and Brain Sciences at Washington University in St. Louis, suggests that at the county level, the higher the percentage of white residents , the greater the proportion of black drivers who are stopped.

“We were surprised how much more racial demographics mattered than racial attitudes, Lai said.

The study was published in March in the journal Psychological sciences.

For this study, Lai and her team looked at county-level disparities in police traffic stops between black and white drivers and compared them to the implicit and explicit racial biases of residents in those counties.

Traffic stop data comes from the Stanford Open Policing Project, an ongoing effort to collect, analyze and share traffic stop data across the country. For implicit and explicit racial bias, the team used county-level data from Project Implicit, a nonprofit research and education organization that uses online tests to collect data on a variety of biases. different. Lai is a member of the Implicit Project Scientific Advisory Board.

After analyzing the data, Lai and his team found that the presence of anti-black/pro-white attitudes was a reliable indicator of disparities in traffic stops.

But they also found that the strength of these attitudes was primarily a signal of how many blacks or whites lived in a county. Counties with a higher proportion of whites had stronger anti-black/pro-white attitudes.

The distinction may be subtle, but the ramifications are clearly laid out in the paper: where white Americans were more prevalent, anti-black/pro-white attitudes were more prevalent, and black quit rates tended to exceed White’s save rate.

“We get caught thinking, ‘well, if people didn’t have prejudices or if we just had egalitarian impulses, we’d be fine,'” Lai said. “But a lot of it depends on which group you belong to.”

Although the article didn’t make strong claims about why race was a better predictor than racial attitudes, Lai suggested that race affects more than just how biased people tend to be.

“When you think about what constitutes race in the United States, part of that is a person’s position in society, social class, education, political attitudes and so on,” Lai said. . Race not only affects prejudice, but it also reaches into areas their study cannot quantify – how children were treated in school, how people are cared for in hospitals, where people live.

Race use is a better predictor than race attitudes because the scope of race effects is much more comprehensive.

“Racial attitudes effectively dominate the day because they are so strongly tied to racial identity that it effectively follows,” Lai said.

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