Gender Stereotypes, Gendered Self-Expression, and Gender Segregation in Fields of Study: A Q&A with Professor Maria Charles

Here, we situate the Gender Equality Paradox in the larger field of understanding gender segregation in STEM fields by talking to renowned scholar Professor Maria Charles, Professor of Sociology, Director of the Broom Center for Demography, and Feminist Studies affiliate at the University of California, Santa Barbara. Professor Charles has worked for decades to understand why postindustrial countries have greater segregation in STEM fields, and she draws on her broad expertise on the persistence of gender inequalities in gender-progressive societies and global variation in gender equality to help us understand the Gender Equality Paradox.

Measuring Gender Equality

According to the Gender Equality Paradox, the more gender equal a country, the fewer women in that country participate in STEM. But how is a country's gender equality measured? In this post, we show how looking carefully at measurement choices might lead us to re-think scientific claims about the so-called Gender Equality Paradox.

Gender Equality Paradox Monkey Business: Or, How to Tell Spurious Causal Stories about Nation-Level Achievement by Women in STEM

This post is an explainer and supplement to our Psychological Sciences Commentary. We discuss five key problems with data and inferences that we identified in Stoet and Geary’s study. In places it’s a bit of a wonky read, but we unpack some serious issues, including issues with replicating the findings, spurious correlations, study design, and the ecological fallacy.

Three Years In: “Sex as a Biological Variable” Policy in Practice - and an Invitation to Collaborate

In 2016 the NIH issued a policy requiring consideration of sex as a biological variable (SABV) in all NIH-funded preclinical research on vertebrate animals and human cells and tissues…three years later, what have been the impacts of the policy on scientific research?

To answer this question, this year I conducted in-person, semi-structured interviews with nine basic science researchers from three different laboratories on the East Coast of the United States that use animal and tissue models to study metabolic disease. I transcribed the full interviews and then conducted thematic analysis of the data using the NVivo software to help organize my coding.