Exclusionary gendered language discourages women from pursuing graduate and professional training programs that lead to careers in statistics by excluding them from (1) the readership of statistical literature, (2) the characters portrayed in examples and problems, and (3) those people qualified to use statistical methods; and by (4) stereotyping women characters into nonscientific careers or careers that are not as prestigious and high paying as men's, (5) reinforcing the existing imbalance in the proportion of men and women engaged in scientific research and development, and (6) portraying professional women as incompetent. Thus this article challenges the continuing use of exclusionary gendered language in statistical literature, bringing this bias to the attention of the statistical community. Numerous examples are used to illustrate how the use of gendered language has symbolically excluded women from access to statistical advancements and careers both historically and now.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education