Psychol Sci Public Interest
July 2023
Purpose: To analyze the relationship between gender, race/ethnicity, and the probability of being awarded an R01 grant from the National Institutes of Health (NIH).
Method: The authors used data from the NIH Information for Management, Planning, Analysis, and Coordination grants management database for the years 2000-2006 to examine gender differences and race/ethnicity-specific gender differences in the probability of receiving an R01 Type 1 award. The authors used descriptive statistics and probit models to determine the relationship between gender, race/ethnicity, degree, investigator experience, and R01 award probability, controlling for a large set of observable characteristics.
Front Psychol
September 2015
Women are an increasing percentage of Bachelors in Engineering (BSEs) graduates-rising from 1% in 1970 to 20% in the 2000s-encouraged by increasing K-12 emphasis on attracting girls to STEM and efforts to incorporate engineering and technology into K-12 curricula. Retention of women in STEM and in engineering in particular has been a concern historically. In this paper, we investigate whether this gap has increased because a larger proportion of females entering engineering find themselves ill-matched to this field, or whether the gap has decreased as engineering becomes more accommodating to women.
View Article and Find Full Text PDFLeslie et al. (Reports, 16 January 2015, p. 262) concluded that "expectations of brilliance" explained the gender makeup of academic disciplines.
View Article and Find Full Text PDFMuch has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/computer science, and the physical sciences.
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