As I returned home from this year’s Women in Statistics and Data Science Conference, one word rang loudly in my ears: patriarchy.

In a presentation on the impact of gender on women’s careers, Carnegie Mellon statistician Dalene Stangl boldly claimed that although the term may be out of favor, patriarchy is “alive and well” and that “it happened to me.”

At first, there was little I recognized in Stangl’s story. The term “patriarchy” is loaded with the history of gender oppression that, thanks to the determination of women like Stangl who came before me, seemed worlds apart from my own experience. I’ve had many male supporters and have never felt discriminated against, even as a female student in a male-dominated field. And yet, as Stangl spoke, I slowly realized that despite my initial resistance to the word itself, I had indeed encountered patriarchy — in the data from my own research.


Later in the same session, I was scheduled to present a paper on gender disparities in medical journals, co-authored with my thesis adviser, Francesca Dominici, and our collaborators at Elsevier publishing. We studied authorship of invited commentaries, a prestigious type of article in which a journal invites an author, typically an eminent scientist, to give his or her expert opinion on cutting-edge research. Writing invited commentaries is a recognition of expertise and provides high-profile exposure to the author.

What we found was jarring. Women in our study were about 20% less likely to author invited commentaries than men who had worked in the same field of health research for the same length of time, accumulating the same numbers of publications and citations — all key measures of scientific achievement. Since our dataset included more than 70,000 articles from about 2,500 medical journals, there was no doubt that this phenomenon is widespread.


There are many possible ways to explain this gender gap. But as Stangl spoke, they coalesced in my mind under a single heading — patriarchy.

Our study dismantled a pervasive assumption: that prestigious scientific papers are most often written by men because most senior scientists are men. This viewpoint implies that to resolve gender disparities at the top, we need only wait patiently while younger, increasingly gender-balanced generations progress through the scientific pipeline.

But passively playing the waiting game won’t be enough. Although patriarchy is most often associated with overt discrimination against women, indifference and inaction by those in positions of privilege can be equally powerful drivers of inequity.

Science is not a pure meritocracy: Scientific ideas and opportunities spread across professional and social networks. Same-gender preferences exist in whose articles are approved by peer reviewers, who is appointed by editors to conduct peer reviews, who is cited by authors of published articles, and in patterns of co-authorship.

As long as men are the dominant gatekeepers in scientific publishing and hold the vast majority of senior research positions, the social-scientific process will continue to perpetuate entrenched gender inequities. This is the legacy of patriarchy in science.

Our study also showed that the gender disparity in invited commentary authorship is larger among more senior researchers: The most experienced female scientists in our dataset were about 40% less likely to author an invited commentary than their male peers. One explanation is that authors who have been invited to contribute invited commentaries are more likely to receive future invitations, allowing the advantage afforded to junior men to increase across their careers. Greater vigilance against inflicting gender bias on young researchers is needed to prevent small gaps from ballooning into large ones.

The gender gap we detected in our study may be an underestimate of the true advantage male scientists have in writing invited commentaries compared to women of equal merit. If female scientists’ careers are hampered by systematic disadvantage, women may actually have greater expertise in their chosen field, on average, than men with the same external indicators of scientific merit, including those measured in our study, such as career length and publication metrics. Overreliance on these superficial measures of scientific status as a proxy for the quality of research solidifies the advantage of researchers who have historically been able to amass status and intensifies the disadvantage of those who have not.

The beneficiaries of history are often white men, but as a white woman studying at Harvard, there’s no denying that I, too, reap dividends from who I am and where I work On the first day of the conference, Rabab Elnaiem, a student at the University of Maryland, Baltimore County, who is black, drew public attention to the racial composition of women on the opening panel: all were white.

While I can’t know what led to the lack of diversity in that instance, it was a stark reminder of the risk of lazy decision-making in my own professional life. If I were to fall back on my current professional connections to convene a conference panel, I would likely oversample white men and women at the expense of equally talented researchers from under-represented backgrounds.

The solution is to breach the confines of our immediate professional circles and consciously seek connections — scientific and otherwise — beyond our comfort zones.

I do not intend to minimize the importance of support networks for researchers who face the same barriers — at the data science conference, I benefited from such a network. Nevertheless, we only stand to gain from increasing the diversity of our contacts and collaborations. Those who have historically held positions of privilege carry the greatest responsibility.

We are fortunate to live in an age where data and technology extend the potential reach of new connections more than ever before. Our study used text mining of published abstracts to identify thousands of women with expertise on invited commentary topics, even though they were underrepresented as commentary authors. This result, while dispiriting, shows the potential of data science to unearth underutilized talent.

Ending inequity in science will require more than playing the waiting game. I, for one, intend to wait no longer, and will use data — and connections — to help close the gender gap in science.

Emma Thomas is a doctoral student in the biostatistics department at the Harvard T.H. Chan School of Public Health in Boston.

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