The cover of my statistics text book features a diagram depicting the relation among sex, time since obtaining a doctorate degree, number of publications, and citations on salary. I haven’t formally learned about structural equation modeling just yet, but nonetheless found it rather discouraging for women. In hopes of being potentially proven wrong, I read the chapter on causal models. The example that Cohen, Cohen, West & Aiken, 2003 give as a working frame to describe causal models is a theory of society’s reward system. This theory states that “social rewards are a function of seniority in the system, status position, productivity, and eminence.” The hypothetical situation presented is a researcher studying academic institutions to determine how well these theoretical constructs hold in academic settings. The theoretical constructs were operationalized as the following: “social rewards” = salary, seniority = time since Ph.D., productivity = publications, and eminence = citations. And status position? Gender. I found it a bit disheartening but in their defense, this is likely the case. The connotation of my sex is something I think about as a young woman beginning a career path in academia. I recently discussed the topic of women in science over lunch with an extremely accomplished autism researcher who is in her sixties. It was interesting to learn how much she had to factor her sex into academic and life decisions. For example, she chose to work with men over women and withheld starting a family until after she went up for tenure review. And while she said that the environment has drastically improved over the years, there are still implicit barriers for women in science, technology, engineering and mathematics (STEM) fields.

I just read a piece in Psychological Science summarizing a growing body of research aimed at understanding the factors that account for women’s lower participation in STEM fields. What I found particularly interesting was the positive influence of having same-gender peers for women in male-dominated fields. For example, perceptions of being outnumbered by men can reduce women’s motivation to enter male-dominated science setting and have physiological repercussions of increased stress. A corollary to this is having more female role models, which improve a woman’s identification with science. There is also compelling evidence that highlighting the contribution of women in science and increase women participation and retainment in STEM. Being exposed to female-positive environmental cues is related to lower concerns about gender stereotyping and increased implicit identification with science. In addition, perceptions of the work environment in STEM fields can influence women’s’ outcomes and decisions to continue in STEM fields.

Social psychologist Amanda Diekman noted that many STEM fields are individualistic and this perception that science is non collaborative, competitive, and individualistic may be a deterrent for individuals who are more relationally oriented (e.g. women and racial/ethnic minorities). While gender discrimination happens and is inevitable, it is important for women to recognize that they also have the potential to benefit scientific progress. Their participation matters. There are efforts in place to increase women’s (and girls’) participation in STEM, such as the Women in Science and Engineering (WiSE) programs found at many universities and colleges, great Ted Talks, the viral GoldieBlox commercial. I am hopeful that the next generation of researchers and scientists will be more gender matched. Nearly all of my former and current advisors have been men, but most of my current colleagues are women.

Taken together, small changes to reduce the salience of perceived stereotypes against women succeeding in science can lead to increased participation for women in science. A simple example would be changing the cover of the Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences for the 4th edition.