The world has been abuzz with news that the Rosetta spacecraft landed on a comet 500 million kilometres from Earth, in an attempt to collect vital data about the origins of our solar system. The aim is to benefit humanity. Unfortunately, this event is also marred for women in STEM and our allies due to the pervasive power of sexism. Rosetta Project scientist Matt Taylor chose to wear a shirt with semi-nude women, effectively telling the world and our next generation of STEM workers that sexism is still very much part of our professional culture.
By the way, this is not the first time he’s publicly worn this shirt. He tweeted that he received the shirt as a present in early October and none of his 2,700 followers on Twitter paid attention. Most worrying is that he is photographed in an office – which suggests he may have worn this shirt to work and none of his management nor colleagues pointed out the inappropriate attire.
This comes only a couple of weeks since The New York Times declared that sexism in academia is dead (as we noted, this claim was based on a highly flawed study). What this wardrobe choice says is that some male scientists in strategic positions for major science organisations do not see equality as a serious issue. Taylor works for the European Space Agency and he is prominently featured on a NASA website.
Here is an examination of the scientific flaws in the recent New York Times (NYT) Op-Ed: “Academic Science Isn’t Sexist.” The Op-Ed authors, psychologists Professor Wendy Williams and Professor Stephen Ceci, put forward various wide-sweeping statements about the effect of gender on academic careers of women scientists. The article outlines the fact that women make up a minority of junior faculty members, particularly in maths-intensive fields like engineering and computer science (25%-30%) and an even smaller proportion in senior positions (7%-15%).
Williams and Ceci argue that much of the empirical studies that established gender inequality in academia are outdated (mostly published prior to the year 2000). They argue that more recent data show that inequality has been diminished in academia. The researchers claim that women are promoted and remunerated at the same rate as men – except in economics. Williams and Ceci further argue that women’s numbers have been steadily growing in the life sciences and psychology. They note that the proportion of women in maths-intensive fields has also been growing, but not as much. Their analysis attempts to explain why this is the case.
The central argument presented in their NYT article is that women would fare well in maths-intensive subjects, “if they choose to enter these fields in the first place.” To put it another way, the problem as they see it, is that gender inequality is a myth, and that the discrepancies between men and women would be reduced if women chose to stay in STEM.
The Op-Ed is based on the co-authors’ study published in November in the journal, Psychological Science in the Public Interest. In their study, Ceci is first author and they are joined by two economists, Professor Donna Ginther and Professor Shulamit Kahn. The research team see that the sex variations within the fields of Science, Technology, Engineering and Mathematics (STEM) represent a “contradiction” and a “paradox.” The logic of their argument is that because there are more women in STEM fields today in comparison to the 1970s, and because there are different patterns of attrition amongst various disciplines, this is evidence that sexism in academia is a moot point. The crux of their argument is simple: if there are differences between men and women’s career trajectories in STEM, these arise from personal preferences, and not due to a culture of sexism.
The are several problems with the Op-Ed, which overly simplifies the body of literature the authors reviewed, but the analysis of study itself is highly flawed. The most glaring issues include the concepts used, such as the authors’ confusion of sex and gender and how these relate to inequality. Another set of problems arise from the authors’ methods. Put simply: the way they measure gender inequality does not match the data they have available, and their interpretation and conclusions of the data are therefore invalid. In science, a study can be seen to be valid when the phenomenon measured matches the instruments used. The concepts, data collection and analysis need to match the authors’ research questions. This is not the case with this study.
Let’s start with the key concept the authors measured: gender inequality, which is also discussed as “academic sexism.”