IZA DP No. 11000 SEPTEMBER 2017 Gender Bias in Teaching Evaluations* This paper provides new evidence on gender bias in teaching evaluations. We exploit a quasi-experimental dataset of 19,952 student evaluations of university faculty in a context where students are randomly allocated to female or male instructors. Despite the fact that neither students’ grades nor self-study hours are affected ...

Pattabiraman et al. add a subtle and unexpected entry to the long list of differences between the sexes. The researchers discovered that a protein that controls gene expression in maturing sperm performs a different function in maturing oocytes, where it promotes chromosome condensation and stability (1). Once meiosis is complete in male mammals, the resulting cells, known as spermatids, underg...

Scientists are trained to evaluate and interpret evidence without bias or subjectivity. Thus, growing evidence revealing a gender bias against women-or favoring men-within science, technology, engineering, and mathematics (STEM) settings is provocative and raises questions about the extent to which gender bias may contribute to women's underrepresentation within STEM fields. To the extent that ...

This paper provides new evidence on gender bias in performance evaluations of university teachers. We exploit a quasi-experimental dataset on 19,962 teaching evaluations, where students are randomly allocated to female or male teachers. Despite the fact that neither students’ grades nor self-study hours are affected by the teacher’s gender, we find that in particular male students evaluate fema...

Gender bias remains a serious problem in the workplace. In order to begin addressing this complex issue, we must isolate the factors that influence these inequalities. Is one such factor political ideology? If so, how does it relate to these inequalities? Research methods used in previous and relevant studies were modified in order to explore this issue. The current research used fictional samp...

During the last decades research has reported unmotivated differences in the treatment of women and men in various areas of clinical and academic medicine. There is an ongoing discussion on how to avoid such gender bias. We developed a three-step-theoretical model to understand how gender bias in medicine can occur and be understood. In this paper we present the model and discuss its usefulness...