Our data collection efforts began by acquiring the meta-data on all articles published in these 10 journals from 2000 to 2015. Web-scraping techniques allowed us to gather information on nearly 8,000 articles (7,915), including approximately 6,000 research articles (5,970). The journals vary in terms of the level of information they provide about the nature of each article, but we were generally able to determine the type of article (whether a research article, book review, or symposium contribution), the names of all authors—from which we could calculate the number of authors—and often the institutional rank of each author (for example, assistant professor, full professor, etc.). In what follows, we describe the variable generation process for all types of articles in the dataset, but note that the findings we report stem from an analysis of authorship for research articles only, and not reviews or symposia.As you can see from the table below, there were low percentages of women among authors across all 10 journals:
Using an intelligent guessing technique (compared against a hand-coding method) we used authors’ first names to code author gender for all articles in the database. We also hand-coded the dominant research method employed by each research article. We were further able to generate women among authors (%) which is the share of women among all authors published in each journal, as well as other variables related to the gender composition for each article, which include information about whether each article was written by a man working alone, a woman working alone, an all-male team, an all-female team, or a co-ed team of authors. Because the convention in political science is generally to display author names alphabetically, we have not coded categories like “first author” or “last author” which are important in the natural sciences.
One explanation people offer for underrepresentation of women is that there are simply fewer women in the field. But that's not the case here:
Women make up 31 percent of the membership of the American Political Science Association and 40 percent of newly minted doctorates. Within the 20 largest political science PhD programs in the United States, women make up 39 percent of assistant professors and 27 percent of tenure track faculty.Instead, they offer 2 explanations:
1) Women aren't being offered as many opportunities for coauthorship:
The most common byline across all the journals we surveyed remains a single male author (41.1 percent); the second most common form of publication is an all-male “team” of more than one author (24 percent). Cross-gender collaborations account for only 15.4 percent of publications. Women working alone byline about 17.1 percent of publications, and all-female teams take a mere 2.4 percent of all journal articles.2) The research methods most often used by women political sciences (qualitative methods) are less likely to be published in these top journals than studies using quantitative methods. As a mixed methods researcher, I frequently use qualitative methods - this was especially true in my work for the Department of Veterans Affairs, where we studied topics that were not only complex and nuanced, but poorly studied and sometimes occurring in a small subset of the population. These are the perfect conditions for a well-done qualitative study to establish some concepts that can be studied quantitatively. But it's difficult to write a survey or create a measure without that basic knowledge. (That doesn't stop people from doing it, leading to bad research. But hey, it uses numbers, so it must be good, right? </sarcasm>) I frequently received snide remarks from other researchers and consumers of research, who didn't believe qualitative methods were rigorous or even scientific. And, as I've blogged about before, I received similar comments in some of my peer reviews.
The authors recognize that perhaps the reason for low representation of women may be because they simply aren't submitting to these journals. But:
[I]f women are not submitting to certain journals in numbers that represent the profession, this is the beginning and not the end of the story. Why not?
Political scientists have helped forge crucial insights into the “second” and “third faces” of power — ideas that help explain that the effects of power can be largely invisible.
The second face of power refers to a conscious decision not to contest an outcome in light of limited prospects for success, as when congressional seats go uncontested in districts that are solidly red or blue.
The third face of power is more subtle and refers to the internalization of biases that operate at a subconscious level, as when many people assume, without thinking, that wives — and not husbands — will adjust their careers and even their expectations to accommodate family and spouse.
Let’s apply those insights to the findings from our study. If women aren’t submitting in proportional numbers to prestigious journals, that may result from conscious decisions based on the second face of power: They don’t expect their work to be accepted because they don’t see their type of scholarship being published by those journals. Or they may refrain from submitting because of a more internalized, third-face logic, taking it for granted that scholars like “me” don’t submit to journals like that.
Either way, publication patterns are self-enforcing over time, as authors come to see it as a waste of time to submit to venues whose past publications do not include the kind of work they do or work by scholars like them.