When I received a passport more adequately reflecting my identity, I felt at peace. But since then, I have repeatedly encountered databases in institutions as well as universities across Europe that did not account for this. Next to issues around legal requirements for accurate data that I couldn’t fulfil (even in countries where non-binary genders are not recognised), this situation further leads to misrepresentation in data gained from these forms. Hence, there are two reasons arguing for databases capturing gender beyond a binary of women and men: 1) making databases accessible to everyone regardless of gender, and 2) gaining accurate insights into gendered dynamics of, e.g., hiring politics and representation.
The way we have built many of our databases at this time leads to issues on updating as they are cementing social norms that have rapidly changed in recent years. through an extensive auto ethnography and analysis of existing database infrastructures, I identified the following recommendations when it comes to modelling data in databases. First, I suggest to protect gendered information. Gender should be understood as a personal, individual and potentially fluid aspect of a person’s identity that should not necessarily be easily disclosed across infrastructures.
Second, I encourage decision-makers to minimize gendered data for a similar reason. If we conceptualise gender as personal and private, the information should only be disclosed on a need-to-know basis. To do so now, will, thirdly, mean to refactor many of the existing databases to account for the flexible, changing and open aspects of gender and get away from a Boolean only representation. Ultimately, we should also reconsider how fixed we model personal characteristics of individuals, despite how much we assume that we know all of the potential values a certain characteristic can take.
Fourth, in an attempt to propagate this understanding forward, we will also have toeducate upcoming developers better on gender so that they are able to model gender adequately, if at all. And this also will entail updating existing textbooks to counteract the persistent reification of a gender binary as a default as well as constructing databases in ways that allow for value flexibility and lightweight changes of categorical data.
Yes, non-binary and/or intersex people are a minority. But if we keep on building our infrastructures only oriented on majorities, we keep on narrowing our definitions of what it means to be human and cause more and more harm to more and more people. And we exclude people from institutions of knowledge productions not due to their talent, but because of their bodies. But if we acknowledge that good research can come from all kinds of diverse populations, we also need to account for them in our infrastructures. This can then include not just those with the privilege of gaining legal recognition, but also acknowledge that legal categories might not provide sufficient options for them to bring their whole selves to their work. And the emotional toll on having to misrepresent oneself or seeing oneself misrepresented persistently has an impact on productivity and wellbeing.
Dr. Katta Spiel is an FWF Hertha-Firnberg scholar at the HCI Group of TU Wien (Vienna University of Technology), where they work on topics surrounding Critical Access in Embodied Computing.
Katta’s presentation on this theme at our Task Force Human Resources meeting on 26 January 2023 can be viewed here (Members-only access, password can be created here).