Redefining underrepresentation in global neuroscience

Shifting the focus of equity initiatives from identity categories to structural barriers may reveal overlooked challenges and increase support and participation worldwide. Definitions of underrepresentation in neuroscience often focus on a familiar set of demographic categories: gender, race and ethnicity, disability, and socioeconomic background.

These classifications underpin most equity initiatives and have helped to increase participation. These categories, however standardized, focus on who people are—and not on the systems that hinder their progress. This distinction, between identity and infrastructure, has significant consequences for who gets counted in the statistics, who receives support, and who continues to be left behind.

For example, consider a researcher presenting their work in a second language, or a graduate student who is the first in their family to attend university, without prior knowledge of how academic careers work and without a family network able to absorb financial pressures along the way. Or imagine a scientist who spends months navigating the visa process just to attend a conference to which they were invited.

These researchers are not exceptions, but they are not easily identified by categories of underrepresentation that rely exclusively on demographic data.

Historically, our field has used definitions of underrepresentation based on demographic categories drawn from national equality legislation and census data. Some forms of underrepresentation are exclusively regional, such as caste identity in India or Indigenous status in New Zealand, for example. But many diversity, equity, and inclusion (DEI) initiatives aimed at addressing these challenges overlook the barriers faced by people with overlapping marginalized identities.

Furthermore, common indicators, such as World Bank income classifications or the “Global South,” can be profoundly misleading—some high-income countries invest less in research proportional to their GDP than others with low incomes, and political shocks can collapse a country’s research capacity more quickly than any dataset can measure.

As members of the ALBA Network—a global community committed to promoting DEI in brain sciences—we have examined these gaps closely. To address these gaps, we advocate that the field needs a more holistic approach to defining underrepresentation in global neuroscience. We propose a broader definition that incorporates well-documented barriers to scientific participation—including the cumulative disadvantages faced by LGBTQIA+ professionals; visa restrictions and mobility limitations that restrict international collaboration; the invisible burden of family care that disproportionately falls on women; forced displacement; being the first person in the family to attend university; English fluency as a non-native language; and working in countries with chronically underfunded research infrastructure.

What happens when one applies this definition in practice? Since 2024, we have used this definition in awarding ALBA prizes, asking candidates to indicate which barriers apply to their situation and to contextualize their achievements in light of these circumstances. This change has revealed new information about the profile of candidates that could have been completely overlooked by standard definitions.

Over the three cycles of the award, the most frequently selected barriers were: being a woman, being the first in the family to attend university, not having English as a native language, or having a lower socioeconomic background. Holders of passports with travel restrictions appeared in 24% of applications for our travel grants over the three cycles—a notably higher number than among conference nominations.

The representation of researchers working in countries with chronically low investment in research and development increased from 35% in 2024 to 47% in subsequent cycles, challenging the assumption that research excellence only exists in environments with abundant resources. And displaced researchers, who are facing forced migration due to conflict or political instability, appeared at low but non-zero levels throughout the period.

Perhaps the most instructive methodological changes came from refinements introduced between cycles. In 2024, we grouped women and LGBTQIA+ candidates into a single category—one of the most frequently selected. When disaggregated from 2025, LGBTQIA+ identification dropped dramatically across all award categories, indicating that the previous aggregation had obscured differences within the combined category.

Our definition of underrepresentation was designed to be globally inclusive, but this carries the risk of losing the precision needed to target resources where they are most needed. There is also a more subtle problem: many researchers do not recognize themselves as underrepresented, even when they face documented disadvantages—particularly women, who, despite well-known structural barriers, often do not identify with this label.

Cultural stigma and privacy concerns further inhibit self-reporting among LGBTQIA+ neuroscientists, which means that even well-designed forms may underestimate this number.

The category of “non-native English speakers” illustrates a similar complexity. For Latin American researchers, it represents a concrete barrier—to produce science in a language that is not their own; in regions where English was imposed by colonialism, however, researchers may see it as less of a barrier.