DATE: November 11, 2026 at 10:00AM

DATE: November 11, 2026 at 10:00AM SOURCE: PSYPOST.ORG ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. ** ------------------------------------------------- TITLE: Greater male variability may help explain persistent gender gaps in hiring, study suggests URL: https://www.psypost.org/greater-male-variability-may-help-explain-persistent-gender-gaps-in-hiring-study-suggests/ Even when men and women earn the same average score on a job test, differences in how widely their individual scores spread out can tilt hiring toward men whenever employers screen out most applicants. A new computer simulation study published in the Journal of Applied Psychology suggests that some common multi-step screening setups can also leave employers with a workforce that is both mostly male and less productive than it could be. The findings point to practical adjustments in how organizations combine job tests and set screening cutoffs to improve both gender balance and expected job performance. At the center of the research is a statistical pattern known as greater male variability. Whenever a group takes a test or is measured on a trait, the scores have two basic properties: the average (called the mean, or the “first moment” in statistics) and the variance (the “second moment,” which measures how widely individual scores spread out from that average). Greater male variability, often abbreviated as GMV, occurs when men’s scores spread out more widely than women’s, clustering more heavily at both the extreme high and extreme low ends while women’s scores cluster closer to the middle. Under this pattern, men are overrepresented among both top and bottom scorers even when men and women share the exact same average. Many employers struggle with gender imbalances despite diversity initiatives. Women make up roughly a third of the workforce at companies such as Apple and Google, and fewer than