Holes in the Data A representation of LGBTQ data
Despite all of the data that is collected about our lives, finding robust and reliable data on the LGBTQ community can be difficult. This is true for many minority groups in America as minority lives have not historically been the focus of research. Finding ways to capture better and more detailed data on marginalized groups is an important task that can lead to well-informed policy making and greater representation that is sorely missing in American life. There are many efforts to improve methods for collecting LGBTQ data with the hope of bettering the lives of LGBTQ Americans. As feminist geographer Joni Seager has stated, "what gets counted counts."
However, there are other data specialists that are concerned with the idea of organizations, companies, or governments collecting detailed information about the LGBTQ community. The greater the data collected on the LGBTQ community, the greater the risk that that information can be used for harm. It is important question the ways that LGBTQ data is collected and how it is used. Does it reinforce structures of power and oppression or disrupt them? Who is benefitting from this information? Some researchers like Lauren E Bridges embrace the ways that queerness evades capture and finds virtue in the “digital failure” queerness creates.
This project will hold these two approaches in tension with each other by displaying data on LGBTQ discrimination. Showing this data is necessary for raising awareness about the reality of LGBTQ lives in this country. At the same time, this project will highlight the fact that LGBTQ data and its collection has holes and, whether they are intentional or not, those holes might just be a good thing.
"Acts of counting and classification, especially as they relate to minoritized groups, must always balance harms and benefits. When data are collected about real people and their lives, risks ranging from exposure to violence are always present. But when deliberately considered, and when consent is obtained, counting can contribute to efforts to increase valuable and desired visibility." Catherine D'Ignazio and Lauren Klein in Data Feminism
"As predictive analytics, automated decision-systems, and artificial intelligence take on increasingly central roles in public governance, digital failure reveals how data itself is a flawed concept prone to political abuse and social engineering to protect the interests of the powerful, while keeping those marginalized over-surveilled and underrepresented." Lauren E Bridges in "Digital failure: Unbecoming the 'good' data subject through entropic, fugitive, and queer data"
The data I have represented comes from “The State of the LGBTQ Community in 2020”, a study done by the Center for American Progress in collaboration with NORC at the University of Chicago. It is considered by some as one of the most comprehensive surveys of LGBTQ lives and experiences to date. The data was collected from interviews with 1,528 self-identified LGBTQ adults from across the country. CAP advocates for better and more detailed collection of data on LGBTQ lives in order to better inform policies from the local to federal level. This survey provides critical insight into physical, mental, financial wellbeing, the frequency of discrimination experienced and where it occurs, as well as information regarding Covid-19 impacts on the LGBTQ community.
For the physicalization of this data I have knitted a mesh tank top, using different stitch patterns and colors to represent different elements of the data. I chose a mesh tank top as a queer item of clothing that plays with aspects of concealing and revealing, which reflect different approaches to collecting queer data. Each band of color represents a different point of data. The holes in the pattern symbolize the fact that there are gaps in LGBTQ data collection (what is unknown about LGBTQ lives captured by data) even as they reveal the body underneath. The mesh tank top also raises questions about what is appropriate. In certain settings this piece of clothing will be inappropriate, similar to how some might think that incomplete data about a community is something to be fixed. In other settings it can be seen as a celebratory expression of queer identity, like purposefully embracing the ways that queerness resists being measured by data. The knitting medium itself is representative of the ways that LGBTQ identities, relationships, and lives are not always “straight”-forward, but twist, knot, and kink in ways that can be at odds with society at large and are yet beautiful and practical.
To translate the selected data points from the table above into a knitting pattern, I decided to turn the percentages into "one out of x many" statements. For example, "35% of LGBTQ Americans have changed the way they dressed/mannerisms" became "About 1 out of 3 LGBTQ Americans..." This allowed me to more easily depict the data in the stitch charts. I used three kinds of stitches: knit, knit2together, and yarn over. K2tog is depicted by the upside down y symbol, and the yarn over by the circle. Together these two stitches make a gap in the row. The knitting pattern for the example became 1 out of every 3 stitches is a yo/K2tog combination. To the right are pictures of my planning and swatching. Below are close ups of each color's stitch chart with the statistic they represent.
Below are pictures from the knitting processing showing the bottom-up construction; the soaking and drying (blocking), which helps the fibers settle and makes the patterns more apparent, and the finished piece.
Bibilography
Bridges, Lauren E “Digital failure: Unbecoming the ‘good’ data subject through entropic, fugitive, and queer data.” Big Data & Society. January-June: 1-17, 2021.
D’Ignazio, Catherine and Lauren F. Klein. “Chapter 4: What Gets Counted Counts.” Data Feminism. MIT Press, 2020.
Guyan, Kevin. “Chapter 8: Fight back! Using queer data for action.” QueerData: Using Gender, Sex, and Sexuality Data for Action. London: Bloomsbury Academic, 2022.
Lesure, Ryan. “(Extra)ordinary Relationalities: Methodological Suggestions for Studing Queer Relationalities through the Prism of Memory, Sensation, and Affect.” Journal of Homosexuality. 29 July 2022. https://doi.org/10.1080/00918369.2022.2103872
Mahowald, Lindsay, Sharita Grubers, and John Halpin. “The State of the LGBTS Community in 2020: A National Public Opinion Study.” Center for American Progress. October 2020. www.americanprogress.org.
Medina, Caroline and Lindsay Mahowald. “Collectiong Data About LGBTQI+ and Other Sexual and Gender-Diverse Communities: Best Practices and Key Condiserations.” 24 May 2022. https://www.americanprogress.org/article/collecting-data-about-lgbtqi-and-other-sexual-and-gender-diverse-communities/.
Ruberg, Bonnie and Spencer Ruelos. “Data for queer lives: How LGBTQ gender and sexuality identities challenge norms of demographics.” Big Data & Society. January-June: 1-12. 2020.
Whittington, Charlie. “Invisible in data: The lack of LGBTQ data collection.” Georgetown Public Policy Review. http://gppreview.com/2018/07/17/invisible-data-lack-lgbtq-data-collection/