At the 2019 JDAI conference, Empact had the good fortune to attend a workshop facilitated by our friends at CCLP and PJI in which they raised a very important policy concern for us to consider: How will our commitment to youth justice reform guide our treatment of sexual orientation and gender identity/expression in our systems?
We were inspired by this topic not only because it furthers justice reform for some of our most vulnerable populations, but also has important implications for the data we collect. What do CCLP’s comments mean for how we capture, analyze and report on data?
What is SOGIE?
SOGIE is a newish acronym that stands for Sexual Orientation, Gender Identity and Expression. We find SOGIE useful because it helps us consider populations as a whole. Everyone has a sexual orientation, a gender identity and a gender expression. Since we want youth justice systems to work well for everyone they touch, we need to be thinking about (read: measuring and analyzing with data) how these systems treat SOGIE.
Not only does this allow us to better serve the kids in our systems who identify as LGBTQ, but — considering the ways that those with non-normative SOGIE experiences are harmed by our systems — it is an important step toward improving the functioning of those systems for everyone.
According to the information shared in the conference workshop, 20% of youth in detention centers identified as LGBQ/GNCT (gender nonconforming and transgender) as of 2018. That’s one in five of our kids! And what’s more, 85% of those youth are of color. That tells us two things:
- This issue needs to be identifiable in our data, and
- When we talk about race equity we should also talk about SOGIE equity.
So what does this mean for how we collect data?
As you may have noticed, there’s not a lot of room for SOGIE-related data collection in our current systems. The QRS (Quarterly Reporting Spreadsheet) is one example: It is one of the ways that many JDAI sites report on and analyze demographic data about the youth in our systems, and yet it does not ask us to track SOGIE data. Since we know that 20% of detained youth already identify as SOGIE minorities — despite LGBT people making up only 4.5% of the general population of the country as a whole — we need to play a little catch-up if we want to figure out how to reduce our impact on these communities.
Slate recently published a bracing article on the reasons why information technology has long been exclusionary toward nonbinary genders. It is a worthwhile read and does a great job describing the challenges in making (what may appear like simple) changes to our cumbersome, legacy systems. The author also points out how New York University makes a distinction between legal sex and gender identity and that it has developed a straightforward way for students to change both designations in the student information system. Is it possible for those of us in juvenile justice to adopt a similar approach to maintaining accurate data on our youth?
Another resource to consider is this piece from the UX Collective’s Medium publication in which the author suggests some best practices for collecting information on users’ gender identities. Although not all of it is applicable to our purposes, we liked their suggestion of allowing respondents to select identifiers from a limited list, as well as their caveats about what sort of options to offer here. And we also appreciated their suggestion to “give people a really good reason for asking.” In our case, that could be as simple as communicating our hope to better serve LGBTQ youth and reduce their numbers in detained populations.
Caution: SOGIE data can be difficult to anonymize
While we strongly believe that collecting and analyzing SOGIE data will be a crucial process for furthering justice reform for LGBTQ youth in particular, it’s important for us to do so in a way that does not increase the harm and vulnerability that these individuals are already facing.
As we have noted previously, protecting the privacy of the people in our systems is a key responsibility of data stewards like ourselves. And as data theorist Catherine D’Ignazio points out, “Because the sample sizes will be so small, [trans and gender nonconforming] individuals may possibly be identified even within otherwise large data sets … This can pose risks of repercussion, either in the form of personal shame for people who have hidden their gender identity or even discrimination, violence and imprisonment depending on the context and community where they live.”
Creating ways to measure our impact on these groups should not come at the expense of their safety and privacy.
Jason Melchi is the owner of Empact Solutions, a purpose-driven consulting group focused on developing data capacity for social service organizations in order to improve outcomes for youth, families and communities. He can be reached at firstname.lastname@example.org.
Isabel Carter and Kim Cataldo contributed to this column.
This post originally appeared on JDAIconnect.org.