Gender representation can be more inclusive, even in outdated systems

Can large organizations like universities make their technology more gender inclusive, even when constrained by outdated systems?

A new study by Simon Fraser University gender, sexuality, and women’s studies professor Megh Marathe and their research assistant, University of Illinois Urbana-Champaign PhD student Drew Kirks-Cler, suggests that meaningful inclusion goes beyond what users see on the surface. It requires addressing the underlying systems that still limit how gender is recorded and reported.

Many large organizations like universities, hospitals, social media platforms and government agencies still rely on technical frameworks and reporting requirements that recognize only binary gender categories. As a result, even systems that appear inclusive to users may simplify or translate gender data into binary categories when it is processed and reported. 

Marathe and Kirks-Cler interviewed 23 trans and gender-diverse students and staff at a public university. While most study participants understood the constraints of institutional systems, the researchers wanted to identify what matters most when fully inclusive systems are not yet possible.

A key priority that emerged was agency. Participants emphasized the importance of having a say in how their gender is recorded, transparency about how that information is used, and control over how it is grouped or simplified when necessary. They would like to see realistic improvements within existing constraints. 

The study also found that meaningful inclusion requires coordination between what users see and how systems operate in the back-end. While some participants valued inclusive user-facing interfaces that reduced day-to-day harm, many emphasized the importance of accurate representation in back-end systems that shape reporting and decision-making.

As one of the first studies to develop a trans-informed approach to inclusive organizational systems, this work offers practical guidance for marginalized communities, decision makers and IT practitioners, that is relevant across sectors. It supports Marathe’s broader research which focuses on improving inclusion in the tools and practices used by professionals to make decisions that affect people’s lives. 

The study, Representation on Our Terms: How Trans and Gender Diverse People Prioritize Inclusivity in University Information Systems, was presented at the 2026 CHI Conference on Human Factors in Computing Systems, the top venue in human–computer interaction.

We spoke with Professor Marathe about their research.

Your research highlights the limitations of outdated institutional systems. What are the consequences of inaccurate gender reporting or what some describe as “performative” or “surface-level” inclusivity?

Surface-level inclusivity refers to systems that appear inclusive to users, such as by offering diverse gender options in forms, but still reduce those identities to binary categories when data is stored, processed, or reported in back-end databases and system components.

Surface-level inclusivity has both immediate and longer-term consequences. At the individual level, it can lead to misgendering, discomfort and disengagement with institutional systems. Participants in our study described avoiding or ignoring systems that did not reflect their identities.  

At an organizational level, surface-level inclusivity can produce inaccurate or misleading data in back-end systems. Since this data is commonly used for decision-making and resource allocation, these inaccuracies can misrepresent communities, reinforce institutional blind spots, and contribute to policies that exclude the very groups organizations intend to support.

What are the biggest barriers institutions face when trying to move beyond binary systems, and which of these challenges are actually solvable?

Institutions face three main barriers: regulatory requirements, technical constraints and resource limitations. For example, universities are often required to report gender data using binary categories for compliance purposes, which limits how inclusive systems can be. 

There are also technical challenges. Many organizational systems are long-lived, interconnected and difficult to modify. Changing back-end databases or data pipelines can require significant time and coordination across teams. 

Constraints like federal reporting requirements are difficult for individual institutions to change. However, others are more tractable. With sufficient planning, dedicated resources and collaboration with software vendors, organizations can begin to address technical barriers over time.

In addition, our findings show that even within existing constraints, meaningful improvements are possible. For example, organizations can improve transparency, give users more control over how their data is shared, and reduce unnecessary collection or exposure of gender data.

You describe the concept of pragmatic inclusivity in your work. What does that look like in practice, and how can organizations apply it?

Pragmatic inclusivity means recognizing that ideal solutions may not always be immediately feasible and focusing on what can be improved within existing systems to reduce harm. 

In practice, this can involve a staged or layered approach. For example, organizations can be transparent about the limitations of their approach while implementing short-term changes like allowing chosen names and pronouns. In addition, organizations can share a longer-term roadmap that outlines how systems will improve over time, including how data is stored and reported. Participants in our study appreciated when systems clearly explained why certain categories were used, why more inclusive options were not yet possible, and what improvements to expect and when.

Finally, pragmatic inclusivity emphasizes user agency: giving people control over how their information is represented, grouped and shared wherever possible. Rather than a one-time fix, this approach treats inclusion as an ongoing process that balances community needs with institutional constraints.

What did participants say makes them feel genuinely respected, even within constrained systems?

Participants consistently emphasized three things: accuracy, agency and transparency.

First, accurate representation, especially in back-end systems, was critical. Many participants said it was more important for their information to be correct in places they could not see or control, because that data shapes how they are represented to others.

Second, agency mattered. Participants wanted a say in how their identities were recorded, grouped and simplified for reporting.

Third, transparency helped build trust. Participants appreciated knowing why data was being collected, how it would be used, and what trade-offs were being made in the process.

Even in constrained systems, these elements signaled respect by showing that institutions had thought carefully about the impact of their design choices. 

How can universities build trust with trans and gender-diverse users when compromises are unavoidable?

Trust comes from openness, accountability and meaningful user input.

First, universities can be transparent about constraints. Rather than presenting systems as fully inclusive when they are not, institutions should communicate where limitations exist and why.

Second, trust is built over time. Participants valued seeing a clear commitment to ongoing improvement, even if changes were incremental. Demonstrating that inclusion is an active priority rather than a one-time fix was key to establishing credibility.

Finally, universities can involve affected communities in decision-making. Providing trans and gender diverse communities with insight and input into which aspects of inclusion to prioritize and when can help mitigate harm when compromises are necessary.

For more:

• Representation on Our Terms presentation from CHI ’26

• Megh Marathe uses research and teaching to advocate for inclusive technology