Academics Use Imaginary Data in Their Research

After surviving a disastrous congressional hearing, Claudine Gay was forced to resign as the president of Harvard for repeatedly copying and pasting language used by other scholars and passing it off as her own. She's hardly alone among elite academics, and plagiarism has become a roiling scandal in academia.

There's another common practice among professional researchers that should be generating even more outrage: making up data. I'm not talking about explicit fraud, which also happens way too often, but about openly inserting fictional data into a supposedly objective analysis.

Instead of doing the hard work of gathering data to test hypotheses, researchers take the easy path of generating numbers to support their preconceptions or to claim statistical significance. They cloak this practice in fancy-sounding words like "imputation," "ecological inference," "contextualization," and "synthetic control."

They're actually just making stuff up.

Claudine Gay was accused of plagiarizing sections of her Ph.D. thesis, for which she was awarded Harvard's Toppan Prize for the best dissertation in political science. She has since requested three corrections. More outrageous is that she wrote a paper on white voter participation without having any data on white voter participation.

In an article in the American Political Science Review that was based on her dissertation, Gay set out to investigate "the link between black congressional representation and political engagement," finding that "the election of blacks to Congress negatively affects white political involvement and only rarely increases political engagement among African Americans."

To arrive at that finding, you might assume that Gay had done the hard work of measuring white and black voting patterns in the districts she was studying. You would assume wrong.

Instead, Gay used regression analysis to estimate white voting patterns. She analyzed 10 districts with black representatives and observed that those with more voting-age whites had lower turnout at the polls than her model predicted.