Q&A: Giving Voice and Data to the Gender Gap in Science

Lisa M. P. Munoz

For more than twenty years, Lisa M. P. Munoz has interviewed hundreds of different scientists about their work in psychology, neuroscience, the geosciences, biotechnology, and immunology, among other disciplines. Time and time again, she heard about the unique struggles facing women in science. In her book, Women in Science Now: Stories and Strategies for Achieving Equity, she not only gives a voice to some of these scientists and their stories, but also highlights how the tools of science can help fix the research enterprise to make it more equitable for everyone. We spoke with Munoz to learn about some of her inspirations in writing, why the intersection of storytelling and data is so vital, and some of the key takeaways from her new book.

Q: Why did you write Women in Science Now?

Lisa M. P. Munoz: I wrote the book to learn how scientific organizations can create inclusive and welcoming environments that retain women scientists. Within the stories of scientists I interviewed over the course of my career were echoes of my own early struggles in engineering during my undergraduate years. After an editor at Columbia University Press approached me to write a book while I was doing publicity work for the Emmy-nominated documentary film Picture a Scientist (2020), my thoughts instantly fell to those stories. I wanted to write a book that would help equip and empower institutions, workplaces, and individuals to effect change in the culture of science for current and future generations.

Q: Can you share a bit about your own experiences within science, technology, engineering, and mathematics (STEM) fields?

Munoz: I was an undergraduate student in the College of Engineering at Cornell University. I chose engineering because I loved the idea of creatively solving problems using science. I also wanted to choose a very practical career that would lead to financial stability, and I was heavily inspired by my older sister, who was pursuing engineering as well. When I arrived at Cornell. I had no worries about fitting in or whether I could “cut it.” But as I progressed through my required engineering courses, despite being at the top of my class in high school and taking advanced math and science classes, I struggled. It felt as though I was actively being weeded out of the program. Support was not easy to find, especially from peers. Although I made it through and did alright, I decided that I did not want to be an engineer after all. I was fortunate to be able to stay within the engineering college, pivoting to an interdisciplinary earth science program while specializing in science writing. Since then, I have often thought about all the women who have been weeded out from their fields of interest, and I now see an opportunity to shift institutions from this weeding-out model to one of growth.

Q: In your book, you discuss the “leaky pipeline” metaphor to describe one of the key problems for women in science and how it needs to be addressed. Could you explain the metaphor?

Munoz: The “leaky pipeline” has traditionally referred to the attrition of women in the sciences, particularly in academia. While many undergraduate science departments begin with roughly equal numbers of male-identifying and female-identifying students, the numbers shift in favor of the male-identifying students at each phase of the educational path—from bachelor’s degrees to master’s, then master’s to PhDs and postdocs, and through to employment. I argue that the leaky pipeline needs to be retired as a metaphor for describing the forces at play for women in STEM fields. To quote from the book: “Women are not dripping through holes in the system; they are being pushed out of a system that historically did not want them in the first place, even if it wants them now.” I have seen some people use “hostile obstacle course” as a metaphor instead, which I think is closer. The point is that this is not a passive process; there are active forces pushing women out of science at different points in their careers.

Q: Why is data necessary to understand the gender divides?

Munoz: Data gives us the ability to see trends that are otherwise invisible through single stories. We see this now throughout society with machine learning, wherein data shows us new patterns that can guide action. For women in science, data is particularly important as many of the biases at play are unconscious, often making it easy for people to say they are not biased when in fact we are all subject to various biases shaped by our personal experiences and society.

For example, if a female-identifying scientist sees that her lab space is smaller than her male-identifying colleagues and brings it to the attention of her institution, they can say it is a fluke, that it’s a function of a lack of space relative to when she came in, etc. But if it turns out that all of the women at that institution have significantly less lab space relative to their male colleagues, that data then reveals a potential systemic bias. That happened recently at the Scripps Institution of Oceanography, where an institutional report found that “56 women scientists have on average half as much research space and one-third the storage space of their 157 male counterparts” and found that the trend could not be explained by the number of years at the institution, funding levels, discipline, or group size. That data, shared in a Science magazine article, only came to light through the efforts of individual faculty there.

Data is also important when it comes to how individual women feel about their place in science. When confronted with a microaggression or slight, oftentimes individuals might think “What did I do wrong?” or “Maybe it’s just because I don’t belong here.” They may think it’s something about them personally. But when individual women hear other women’s stories and see the data of the larger trend, it can be empowering, revealing that the problem is systemic and motivating them and others toward action.

Q: As a science writer, can you explain the importance of storytelling in understanding science, and how do data and narrative intersect in Women in Science Now?

Munoz: What strikes me the most when I interview a scientist for the first time is how their unique background and worldview shape the questions they are now pursuing as scientists. That story lies at the heart of science and the scientific method. I recently read a fantastic opinion piece in the Washington Post by Maya Shankar, a musician turned cognitive scientist, in which she said people should focus on anchoring their identities to why they do a job more than what they do. That’s how I think of storytelling in science: it’s the why. Data can ground us empirically in facts, but stories propel us forward as people, driving us toward discovery and asking new questions. Corinne Moss-Racusin, one of the social psychologists featured in my book, talks about how a very personal debate with her boyfriend when she was an undergrad drove her to pursue research on gender stereotypes, which ultimately lead to a rich and novel set of data on gender bias in evaluating resumes when hiring scientists. That to me is one of the intersections of story and data I wanted to capture in my book.

Q: What was one thing that surprised you while writing Women in Science Now?

Munoz: A couple of things. First, I was surprised by the breadth and depth of the literature of the gender gap in science. It was a much richer and larger dataset than I initially thought it would be, and it stretches back in time farther than I expected. I remember being shocked, for example, upon finding a 1883 paper by Matilda Joslyn Gage titled “Woman as Inventor.” Second, though in hindsight it should not have come as a surprise, there was an unexpected challenge in finding scientists who were open to telling their stories for the book, some of which were emotionally difficult to share. Some stories did not make it in, as it can be easier sometimes to tell a story orally than to see it in print. I am grateful to all the people who shared their stories with me, whether or not they appeared in the book, and feel honored to be able to share some of them to the world.

Q: Women in Science Now gives voice to stories from diverse women. What brings these women together?

Munoz: I was fortunate to talk with scientists from various disciplines for the book, including social psychology, genetics, chemistry, paleontology, the geosciences, and cognitive neuroscience. They all have different backgrounds and are in search of answering different questions, yet all are driven to pursue answers through the scientific method. At the same time, they are all driven to improve science for everyone, through mentorship, outreach, and leadership in their fields. Sadly, all are also united in the types of obstacles they have faced in pursuing these efforts. While each scientist’s path and challenges are unique, there is an eerie universality in their struggles. Things like stereotypical perceptions of who is or should be doing science, which can lead to gender- or racial-based slights and microaggressions; the feeling of being the only one of a particular identity in the room or of not belonging; working to advance their careers while juggling family, often with little support; and feelings of being an “imposter,” in part fueled by these experiences.

Q: What do you hope people take away from Women in Science Now?

Munoz: We must close the gender gap in science to fix the scientific enterprise. The good news is that we have a large body of research from scientists themselves to guide us in closing that gap. I love the idea that we can use science to help fix science, and I found it inspiring to talk to some of the people working to make that happen. I hope readers will as well, and that this book and the stories wherein will motivate individuals and institutions to think more deeply about how they can effect change.

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