Fact Check: No, There Is Not A New Survey Showing Trans Identity Is Decreasing
https://www.erininthemorning.com/p/fact-check-no-there-is-not-a-new
>On Tuesday, Kaufmann posted a Twitter thread declaring that “trans identification is in free fall among the young.” The graph he used to prove it, however, was fundamentally flawed—it showed students who identified as “neither male nor female,” a category that excludes most transgender men and women. In other words, Kaufmann’s supposed evidence of a collapse in “trans identification” was actually a selective chart of nonbinary students, not transgender people as a whole.
>The error didn’t stop there. Researchers quickly discovered that Kaufmann’s graph—based on data from the Foundation for Individual Rights and Expression (FIRE), a right-leaning organization [Fire disputes this characterization| that studies campus speech—contained a fundamental methodological mistake. Data scientist Jacob Eliason was the first to spot it: Kaufmann had run his analysis using the raw survey responses rather than applying the weighting provided by FIRE to make the results nationally representative. Without weighting, the data dramatically misrepresented the population—and created the illusion of a drop where none existed. When Eliason re-ran the numbers correctly, the trend line flipped entirely, showing that the share of students identifying as neither male nor female had increased, not decreased. Kaufmann’s analysis, in other words, didn’t reveal a cultural shift—it revealed statistical malpractice.
>On Tuesday, Kaufmann posted a Twitter thread declaring that “trans identification is in free fall among the young.” The graph he used to prove it, however, was fundamentally flawed—it showed students who identified as “neither male nor female,” a category that excludes most transgender men and women. In other words, Kaufmann’s supposed evidence of a collapse in “trans identification” was actually a selective chart of nonbinary students, not transgender people as a whole.
>The error didn’t stop there. Researchers quickly discovered that Kaufmann’s graph—based on data from the Foundation for Individual Rights and Expression (FIRE), a right-leaning organization [Fire disputes this characterization| that studies campus speech—contained a fundamental methodological mistake. Data scientist Jacob Eliason was the first to spot it: Kaufmann had run his analysis using the raw survey responses rather than applying the weighting provided by FIRE to make the results nationally representative. Without weighting, the data dramatically misrepresented the population—and created the illusion of a drop where none existed. When Eliason re-ran the numbers correctly, the trend line flipped entirely, showing that the share of students identifying as neither male nor female had increased, not decreased. Kaufmann’s analysis, in other words, didn’t reveal a cultural shift—it revealed statistical malpractice.
