A new paper by political scientists Brian Schaffner, Matthew MacWilliams, and Tatishe Nteta puts the blame back on the same factors people pointed to before the election: racism and sexism. And the research has a very telling chart to prove it, showing that voters’ measures of sexism and racism correlated much more closely with support for Trump than economic dissatisfaction after controlling for factors like partisanship and political ideology:

 Brian Schaffner, Matthew MacWilliams, and Tatishe Nteta

As the paper acknowledges, clearly economic dissatisfaction was one factor — and in an election in which Trump essentially won by just 80,000 votes in three states, maybe that, along with issues like the opioid epidemic and poor health outcomes, was enough to put Trump over the top. But the analysis also shows that a bulk of support for Trump — perhaps what made him a contender to begin with — came from beliefs rooted in racism and sexism.

Specifically, the researchers conclude that racism and sexism explain most of Trump’s enormous electoral advantage with non-college-educated white Americans, the group that arguably gave Trump the election. “We find that while economic dissatisfaction was part of the story, racism and sexism were much more important and can explain about two-thirds of the education gap among whites in the 2016 presidential vote,” the researchers write.

Now, the researchers didn’t measure just any kind of racism and sexism. For racism, they evaluated the extent that someone acknowledges and empathizes with racism — acting as a proxy measure for actual racist beliefs. (Research shows that these kinds of measures correlate with actual racism, which is tricky to measure in a more direct way since people will do what they can to avoid looking racist.) For sexism, they evaluated someone’s hostile sexism — which, through several questions, gauges hostile attitudes toward women. (For more on how hostile sexism is typically measured and compares with other types of sexism, read Libby Nelson’s explanation for Vox.)


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