The influential book Invisible Women articulates some of the countless ways in which women are missing from the data we use to understand the world, including the testing of many drugs, consideration of how best to support refugees, and others. The book is powerful, because it shines a light into how, by missing women out, we (unintentionally) do harm.
This trans visibility day, we’ve been thinking about whether a similar book could be written for trans people, and have had to conclude that it could not. Trans people and their experiences are so missing from the datasets that shape social science that we cannot even begin to fully understand the extent of their absence, and how this affects their lives.
Trans identities are missing from our datasets, meaning that their experiences in a number of domains cannot be studied quantitatively. The way in which many of our datasets are constructed reinforces a cis-normative understanding of the world, where people are pushed into the false binary of describing themselves as either male or female. Even less desirably, their gender is often assumed by the person administering the dataset, or worse, lumped into the amorphous category of “other” – literally othering survey respondents with a trans or non-binary identity.