Redefining underrepresentation in global neuroscience

Redefining Underrepresentation in Global Neuroscience

Shifting the focus of equity initiatives from identity categories to structural barriers uncovers challenges that have been overlooked, potentially increasing global participation. Definitions of underrepresentation in neuroscience often center on demographic categories: gender, race and ethnicity, disability and socioeconomic status.

Most equity initiatives rely on these categories, which have contributed to expanding participation. While these categories are standardized, they focus on what people are, rather than the situations that hinder their progress. This distinction between identity and infrastructure has significant implications for who is included, supported, and unable to overcome barriers.

For example, consider a researcher presenting their work in a second language, or a first-generation student lacking prior knowledge of academic careers and facing economic challenges along the way. Imagine a scientist navigating visa applications for weeks just to attend a conference they were invited to. These scenarios are not uncommon, yet they are difficult to monitor with categories of underrepresentation that solely rely on demographic parameters.

Historically, our field has used definitions of underrepresentation based on demographic categories derived from national equality legislation and census data. Some forms of underrepresentation are genuinely region-specific, such as caste identity in India or indigenous status in New Zealand. However, many diversity, equity, and inclusion (DEI) initiatives designed to address these challenges overlook barriers faced by marginalized individuals whose identities intersect.

As members of the ALBA network, a global community committed to advancing DEI in neuroscience, we have examined these gaps and argued for a more holistic approach to defining underrepresentation in neuroscience on a global scale. We propose a broader definition that includes well-documented barriers to scientific participation, including cumulative disadvantages faced by LGBTQIA+ individuals; mobility and visa restrictions limiting international collaboration; the invisible tax of caregiving tasks disproportionately falling on women; forced displacement; being the first generation of a family to attend university; speaking English as a second language; and working in countries with low investment in science, technology, and innovation.

What happens when we apply this definition? Since 2024, we have used it for ALBA grant selection programs, asking applicants to identify the barriers they face to contextualize their achievements in relation to them. This change has revealed aspects of our applicant population that standard definitions might have overlooked. The most frequently identified barriers were being a woman, being a first-generation university student, not speaking English as a native language, or coming from a socioeconomically disadvantaged background.

Passport holders with travel restrictions were 24% of travel support program applications, significantly higher than nominations for conference support programs. Researchers working in countries with chronically low investment in research and development increased from 35% in 2024 to 47% in subsequent years, challenging the assumption that excellence can only be found in resource-rich environments.

Displaced researchers, who face forced migration due to conflicts or political instability, appeared in lesser but notable percentages among applications. Methodologically, a significant improvement came in 2025 when we disaggregated women and LGBTQIA+ applicants into separate categories. The identification of LGBTQ+ applicants fell sharply from 2024 to 2025, suggesting that the previous combined category obscured two very different patterns.

Our definition of underrepresentation is designed to be globally inclusive, but this raises a finer point: many people do not identify as underrepresented despite facing documented disadvantages, particularly women, who despite clear barriers, commonly do not identify with that label. Cultural stigma and privacy concerns further restrict the self-identification of the LGBTQIA+ category, likely explaining its low selection rate.

The "English as a second language" category illustrates a related complexity. For Latin American researchers, it captures the concrete barrier of producing science in a non-native language; in other regions where English was imposed through colonialism, however, researchers may be fluent but face prejudice due to accents. Capturing these limitations requires not only methodological refinement but also a shift in how our field evaluates success as a criterion for eligibility.

Initiatives are already pointing in the right direction. Australia's NHMRC's Relative to Opportunity policy explicitly encourages this approach.