Women’s Contributions to Early Genetics Studies Were Relegated to the Footnotes

While women scientists were frequently “acknowledged programmers” in population genetics research, few of them received full authorship

Computer Technician
Computer technician Joyce Cade works on a UNIVAC computer at a United States Census Bureau installation in Maryland which was used to tabulate the results of the 1954 Census of Business. Bettmann / Getty Images

As a postdoctoral researcher at the University of California, Berkeley, Emilia Huerta-Sánchez noticed something strange in the fine print of an old population genetics study. In the acknowledgements, the study’s author, a well-known geneticist, wrote, “I wish to thank Mrs. Jennifer Smith for ably programming and executing all the computations.”

Huerta-Sánchez showed the odd credit line to fellow postdoc Rori Rohlfs. Smith’s level of computing, she remarked, would normally warrant authorship today. In all likelihood, the two scientists mused privately, other women’s contributions to the burgeoning field of population genetics had also been relegated to the footnotes.

Years later, after watching the 2016 movie Hidden Figures, which depicts the black female mathematicians behind NASA’s human spaceflight program, Huerta-Sánchez and Rohlfs—now with university appointments of their own—discussed the idea again. This time, they wanted to test the hypothesis. How many programmers had been left in the footnotes of their field, they wondered, and how many of those less-acknowledged contributors were women?

Huerta-Sánchez and Rohlfs assembled a team of student researchers to flip through the archival pages of 20 years’ worth of articles in the programming-heavy journal Theoretical Population Biology, documenting the authors and the names in the acknowledgements and categorizing them by gender. After the group reviewed 800-plus articles by over 1,000 authors (about 93 percent of whom were men), Huerta-Sánchez’s initial suspicion proved correct. Women who’d contributed to influential studies tended to receive a hat-tip in the acknowledgements rather than full authorship.

In a recent study published in the journal Genetics, the San Francisco State University and Brown University researchers found that just under half of the 46 “acknowledged programmers” they identified in theoretical population genetics studies were women, in contrast to only about seven percent of credited authors. Ezequiel Lopez Barragan, one of the San Francisco State University students who worked on (and got authorship) for the new study, says he felt the skewed acknowledgement of women as programmers was “just not fair, not equitable.”

By identifying the biases in old research conventions, the team hopes to draws attention to who does—and does not—receive acknowledgement in scientific papers today.

Population genetics, which sprouted up in the first half of the 20th century after the rediscovery of Gregor Mendel’s foundational work in genetics, is a computation-heavy field that looks at genetic variation to better understand how natural selection and population makeup influence evolution. By the 1970s, one of the decades reviewed in the new study, computer-generated models had become accessible tools for scientists, and technological advances made it possible to gather detailed protein variation data. “The field of population genetics took off,” Rohlfs says.

Some of the data couldn’t be analyzed by hand, which is where the “acknowledged programmers” came in, computing on the new machines to conduct numerical analysis. These programming roles were often carried out by women, but the researchers crunching the numbers didn’t receive the same acknowledgment in published research that they might expect today.

The practice of downplaying women’s scientific contributions isn’t anything new, says historian Marsha Richmond, who studies women’s early contributions to academic biology. Instead, she says, “it follows a long trend” that was probably first established in astronomy. The “Harvard computers,” for example, who calculated the positions and characteristics of thousands of stars at Harvard Observatory at the turn of the 20th century—and made many important discoveries in astronomy along the way—mirrored the mathematical roles that women played at NASA more than half a century later.

Historically, women tended to enter emerging fields like ecology or radiation science, and as employees, they were cheaper to hire than their male counterparts. But “once the field develops, they get rather marginalized and the men take over,” Richmond says. Although the 1960s and ‘70s heralded increased visibility for some female scientists, like ecologist Rachel Carson and geneticist Charlotte Auerbach, both genetics and the initially “pink-collar” field of programming followed the pattern of sidelining women contributors. The proportion of female “acknowledged programmers” in the new study, for instance, decreased between the 1970s and 1980s as the field became more male-dominated and lucrative.

Richmond calls Huerta-Sánchez and Rohlfs’ paper “exciting.” It was the first she’d learned of women involved in this era of evolutionary biology. The lack of female scientists and programmers in the historic record, Richmond says, is “not just a problem of science and society but also of historians. Historians have tended to gravitate towards the males who are considered geniuses.”

Both Richmond and the study’s principal investigators emphasized that uncovering the presence of women in population genetics could inspire future scientists and guard against the negative impact of gender stereotypes in science. Such work reveals paths to success in a field that’s still relatively male-dominated. “The more we see women doing science, the more it’s normal,” Rohlfs says, “and we hope that will lead to change.’

Margaret Wu is an early contributor to population genetics and one of the “acknowledged programmers” whose name cropped up repeatedly in the new study. As the Atlantic’s Ed Yong explains, her work help develop a statistical tool—still used today—that approximates the level of genetic diversity in a population.

But when the team behind the study finally reached Wu, she initially thought they’d contacted the wrong person. Wu, after working as a research assistant at Monash University in Australia, has gone on to specialize in educational statistics, not population genetics. She earned a PhD almost 30 years after the highly-cited study that she contributed “numerical work” to, and she is now on the faculty of the University of Melbourne.

“I was in no way frustrated about the authorship. I didn’t even think I should be acknowledged … that was the norm in those days,” Wu writes in an email. But she also says she’s observed and experienced gender discrimination throughout her career in academia. “My conclusion was that men are often ‘mates’ (to use an Australian term),” she says, “and they unite and are unwilling to contradict each other even though someone is not doing the right thing.”

Upon reading about Margaret Wu in the Atlantic, Jess Wade, a physics postdoc at Imperial College London who’s created around 510 Wikipedia pages for female scientists, made Wu a Wikipedia page. Wade says via Twitter that her first reaction to the study was anger. “I made [the Wikipedia page] because I’m sick of these people being written out of history.”

Rohlfs also pointed to norms, not individuals, as being responsible for the lack of acknowledgement for women. Because authorship, which is “totally crucial” for career advancement, can be distributed subjectively, it’s “subject to all the biases we have,” she says. Today, for instance, the contributions of technicians might be overlooked, and technicians, Rohlfs says, are more often women and people of color.

“Everybody just thought it was okay that these women didn’t get authorship,” she says. “I think that leads us directly then to think about what are our authorship norms today, and who are we excluding because we just tacitly agree that it’s right to exclude those people.”

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