That’s My Spot: Is there really room for everyone in science?

by Rosie Audino, expert in philosophy and science and health communication

In episode 18 of the sixth season of The Big Bang Theory, Leonard, Sheldon, and Howard, involved in a university project related to inclusion in STEM (Science, Technology, Engineering, Mathematics), need to find a way to encourage more girls to pursue scientific studies. They decide to go speak at an elementary school. Before their presentation, they discuss the topic and reflect on how, historically, many women have had to mask their identity to avoid prejudice: from J.K. Rowling, who chose to use initials, to Star Trek's Dorothy Fontana, who signed as "D.C. Fontana" to be taken seriously as a screenwriter.

Even today, scientific and technological careers are marked by significant gender inequalities. Did you know that, globally, only 22% of women who study STEM disciplines actually manage to work in these sectors? And that barely 2% of investment capital goes to startups founded by women?

These disparities are not just about numbers; they are rooted in a long history of exclusion. The stories of two emblematic figures – James Barry / Margaret Ann Bulkley and Lynn Conway – show how profoundly gender has determined, in different eras, who could study, work, and innovate.

The Story of Margaret Ann Bulkley 

In 1867, in London, military doctor James Barry died after an adventurous life serving the British army. Only the housekeeper, upon finding him dead in his room after a long illness and preparing the body, discovered what the army would then conceal for over a hundred years: James Barry was born a woman. Her name was Margaret Ann Bulkley. In the early 19th century, a woman could not access university, let alone surgery. To study medicine in Edinburgh and build a career, Margaret had to assume a male identity. Under false pretenses, Margaret not only completed her studies but brilliantly passed the Royal College of Surgeons exam and became Inspector General of military hospitals in Canada.

In Cape Town, she successfully performed one of the first modern C-sections in which both mother and newborn survived, the latter aptly named James Barry Munnik.

A story that seems centuries old, but which also speaks volumes about the present.

The Story of Lynn Conway

A century later, computer scientist Lynn Conway would revolutionize the way we design chips and digital architectures. Her discoveries are the foundation of modern microelectronics and still power smartphones, computers, and network technologies today. Yet, in 1968, while working at IBM, Conway was fired by CEO Thomas J. Watson, Jr., after the company learned of her gender transition. A decision that would be illegal today. Lynn didn't stop. She completed her transition and started over from scratch with a new professional identity. Hers was a brilliant career: she became Associate Director for Strategic Computing at DARPA; Professor of Electrical Engineering and Computer Science at the University of Michigan (1985); a key figure in computer innovation from the late 1960s. Lynn revealed her story only in 1999. As she herself said: "In the 1970s, I was seen as a woman who had broken the gender barrier in computing. By 2000, that barrier had become transgender." In 2024, Time recognized her as one of the most influential LGBTQ+ figures of our time.

What These Two Stories Teach Us

Margaret and Lynn are not romantic exceptions. They are two extreme examples of a very simple phenomenon: talent isn't enough if the system doesn't see you or excludes you.

The Leaky Pipeline: Where Talent is Lost

Leaky pipeline, literally a leaking pipe, is a phenomenon that perfectly describes what happens in scientific careers: at every stage – education, doctorate, research, leadership – an increasing number of women drop out.

According to the UNESCO report (2021):

44% of PhD holders are women, 33% of researchers worldwide are women, only 22% work in Artificial Intelligence, and barely 2% of investment capital goes to startups founded by women.
The system doesn't lose talent due to a lack of interest or skills, but because of a lack of opportunities and equal conditions.

Transgender and non-binary people in STEM

While data on women already shows significant asymmetries, the situation is even more complex for transgender and non-binary people. A 2025 analysis showed that over 70% of academic STEM studies still only use male/female categories, and only 5% include broader gender identities.
This means one thing: we don't know how many trans and non-binary people work or study in STEM. This makes it impossible to monitor their actual representation, observe where they encounter barriers, and consequently design effective inclusion policies or programs.

If there's no data, there's no problem, and therefore no solution...  

Indeed, when a group is excluded or considered marginal, science becomes less representative, data less reliable, and innovations less useful for the entire population. 

UNESCO data clearly shows this: scientific output continues to reflect an almost exclusively male perspective. This means that the needs and specificities of at least half the population are systematically overlooked. In Caroline Criado Perez's book "Invisible Women," which rigorously addresses this topic, a shocking fact emerges: the fact that the upper echelons of science, and medicine in particular, are still predominantly male directly influences the direction of research and, consequently, its practical applications. In other words, research tends to be modeled on a standard male body. Perez shows how many commonly used drugs have been tested almost exclusively on men, despite extensive documentation that women can experience different or more severe side effects. Not only that: often, there is no investment in developing drugs for conditions that primarily affect women, such as dysmenorrhea, simply because their clinical and economic relevance is not recognized. The author also notes how, within parts of the male scientific community, a form of denial persists regarding the "gender data gap": the lack of gender-disaggregated data and the real inclusion of women in research protocols. A significant example is the study published in 2018 in the British Journal of Pharmacology, titled "Gender differences in clinical registration trials: is there a real problem?" The authors' (all male) thesis is that, in clinical trials necessary for drug approval, women are not numerically underrepresented. However, the substantial limitation of the study is that, despite their presence, the data was not disaggregated by gender. This prevents understanding if and how the drug acts differently in the two sexes. And this is the central point: it's not enough to include women numerically; it's essential to understand how drugs work on different bodies. Only then can we speak of true gender-specific medicine.

Without wanting to draw hasty conclusions, it is plausible to assume that the significant underrepresentation of women in STEM fields is also reflected in how research is designed and conducted. If those who define scientific priorities largely belong to a single group, whether by gender, background, or experience, it is inevitable that some questions will be asked and others not, that certain problems will emerge and others will remain in the background. The scarcity of female perspectives in decision-making roles is not just a matter of professional equity, but has concrete consequences for the quality, completeness, and usefulness of the science we produce. We also see this clearly in UNESCO data: only 2% of global innovation investments are allocated to femtech, an area that includes technologies designed to meet the needs of all people who, due to gender, identity, biological characteristics, or health conditions, have historically been underrepresented and poorly considered in traditional research pathways. And this is a major limitation, because in a sector that should promote progress, inclusion, and creativity, many real needs remain invisible or marginal.