(In)Visi-BI-lity Taking Bi+ Data – and the Bi+ Community – from the Invisible to the Visible
Part 1: Background
In the U.S., people in the LGBTQIA+ (lesbian, gay, bisexual, transgender, queer, intersex, asexual, and additional identities) community regularly face discrimination. As a result of that discrimination, LGBTQIA+ people can experience disparities in many areas of life, including in their health (both physical and mental), and at work, school, and home (Mahowald). When collecting data that reveals these disparities, reports often separate out sexual/romantic orientation from gender identity, which makes sense: individuals may experience discrimination differently depending on various identities that they may hold, and trans and non-binary people often experience worse outcomes than cisgender people (James et al. 2-15). However, when looking at sexual orientation, reports often keep data on lesbian, gay, and bisexual+ people together, which makes it difficult to recognize that bi+ people’s experiences and outcomes are often different – and notably worse – than gay and lesbian people’s (Mirza; Movement Advancement Project i). The book Data Feminism states, “before collective oppression can be identified… the data must exist in the first place” (D’Ignazio and Klein 98). Not separating out data that is specifically about bi+ people keeps an important part of the anti-LGBTQIA+ discrimination story hidden and invisible. This data physicalization serves to make bi+ people's part of the story visible. As a note, for this data physicalization, bi+ (or bisexual+) is used as an umbrella term to encompass all non-monosexual identities, including bisexual, pansexual, queer, fluid, and more (Bisexual Resource Center, “Bi+ Info”).
Bi+ people make up a majority of the LGBTQIA+ community – exact numbers differ, but general estimates are that about half of the LGBTQIA+ community is bi+. According to research from the Human Rights Campaign Foundation, 52% of LGBTQIA+ youth (ages 13-17) are bi+, and 62% of adults (18 and over) are bi+ (“Bi+ Youth Report”). However, bi+ people are often rendered invisible. Bi+ people may be assumed to be gay or straight, depending on the gender of their partner(s), which can result in the erasure of their bi+ identity (Bisexual Resource Center, “Frequently Asked Questions”). Bi+ people can also face harmful stereotypes when they do come out, being told to “pick a side,” that it’s “just a phase,” or that they’re “doing this for attention.” This can mean that bi+ people don’t come out, come out to only a few trusted friends or family members, or are put in situations where they have to decide whether to come out over and over, only to be met with skepticism much of the time. No one should ever be forced to come out, but it is also harmful for anyone to feel forced to remain closeted because of bias or other external influences. Bi+ erasure is real and harmful, and can come from both within and outside of the LGBTQIA+ community (Human Rights Campaign Foundation, “Coming Out: Living Authentically as Bisexual+”). This makes it all the more important that we make visible the harms that bi+ erasure and biphobia can do.
Part 2: Artifact Development
As a bi+ person myself, and someone who has worked in bi+ advocacy previously, I knew that for this data physicalization project, I wanted to use bi+ data. The first thing I did was look for sources and make sure that some kind of project would be feasible with the data that was available. I had some data sources in mind from the start, and found others through careful searching. One thing that I quickly realized is that much of the data that does exist about bi+ people is disaggregated. I had to pull data from multiple sources and data sets, some of which themselves were pulling from multiple sources. I think that this experience speaks to the overall issues of data collection about the bi+ community (Mirza; Movement Advancement Project i, 1, 22). However, it was clear that although the data were scattered, a project would be possible.
As I was collecting data sets and sources, I was also thinking about how I would want to visualize and physicalize the data. As mentioned above, one theme that is prevalent in bi+ advocacy and in data about the bi+ community is visibility (or the lack thereof). This theme also appears throughout the book Data Feminism by D’Ignazio and Klein, including as part of a discussion of the benefits and drawbacks of both visibility and invisibility (109-111). On a personal level, I’ve also struggled with visibility as a bi person, and so I started to consider potential ways to physicalize this struggle through data. Was there a way to make data about bi+ people both invisible and visible, to reflect the struggle that many of us go through? Through this brainstorming process, I came up with the idea of creating scratch-off sheets.
As soon as I thought of scratch-off sheets, I loved the concept. It seemed to be the perfect way to both visualize and physicalize data about the bi+ community. The data start off as hidden beneath silver paint – just as a lot of bi+ people are rendered invisible. Then, someone interacts with the artifact by scratching off the paint. Through that action, the data point about the bi+ community is literally made visible. Once visible, it would be difficult to make the data point invisible again – just like it is hard for someone to forget data and facts about bi+ people once the person has become aware of them. The data points just need to be available in the first place. For all of these reasons, scratch-off sheets, created through a multi-modal type of making, were the ideal way to visually display this bi+ data.
Part 3: Preparation
After deciding how to physicalize the data overall, I then started thinking about what data points I wanted to include on the scratch-off sheets. I quickly decided to separate the data into two groups – data on bi+ youth, and data on bi+ adults. Generally speaking, youth can face unique challenges because of their age group, including struggles in school or with parents at home, and I felt it was important to include those challenges (Human Rights Campaign Foundation, “Bi+ Youth Report”). I was able to pull all of the youth-specific data from one source, the Human Rights Campaign Foundation’s “Bi+ Youth Report” from 2019. Data about bi+ adults was somewhat harder to piece together. The main source I used, the Movement Advancement Project’s “Invisible Majority” report from 2016, contained data from multiple sources, but did not have everything I was looking for. As a result, I also pulled some data points from several Human Rights Campaign sources. During the preparation phase, I made notes on what data points I might want to include in the physicalization, but did not make any firm decisions.
Next, I looked online for tutorials on how to create scratch-off cards at home. I drew inspiration from several different sets of instructions and used aspects of all of them to figure out how to create the cards (all included in the Works Cited section at the end of this website). I made a shopping list and headed to the craft store. I had initially thought about making large scratch off sheets, but when I was looking at supplies, I was worried about how well the posterboard would hold up and thought it was likely that it might get bent or torn, making it difficult for people to really interact well with the artifact. I felt like an unwieldy artifact would defeat the purpose of the physicalization, which is meant to be something that people can really engage with up close. Instead, I chose to get several smaller pieces of cardstock and some foam boards that I could attach the cardstock to, which would make the scratch-off sheets much easier to handle. Decision made, I purchased the supplies and returned home, excited to start working.
Part 4: Testing Process
I wanted to set up a dedicated space to create the artifacts in my apartment, so I chose to work at my kitchen island, because the lighting is best there. I used an old sheet to cover the area as a makeshift drop cloth, since I would be working with paint in the project, and I did not want to accidentally stain or damage anything.
Next, I ran some tests to help inform several decisions about making the artifact. Each data point would be written down on a piece of cardstock, which would then be cut out in a circle shape, covered with clear Con-Tact paper in preparation for being painted, and taped to another, full-size piece of cardstock. Using separate pieces of cardstock helps to differentiate each data point for both painting and scratching off the paint. So, the first thing I tested was the size of the circles on which to write the data points. I needed to balance several things: how many words to include so that each data point made sense; how big I needed to write for the data points to be readable; and how big the circles needed to be for the paint to be easily scratched off. I tested several different sizes of circles before choosing one to trace, using a mug from my kitchen.
Once I had chosen a size of circle, I realized that I was at another decision point. The size of the circle meant that I would only be able to fit five or six data points on one piece of cardstock, which was fewer than I had been hoping for. Eventually, I decided that instead of making one scratch-off sheet for bi+ youth and one for bi+ adults, I would make two for each age group, for a total of four scratch-off sheets. This meant that I would be able to easily include 10 facts for each age group, five on each card, and have them stay readable.
With the decision of the size of circle made, I went back through my data sets and chose the actual data points to include for each age group. As I went through the reports, I made decisions on how to rephrase and/or recalculate each data point, so that each one would be as readable and digestible as possible for those interacting with the data. I recorded each data point in a separate document to capture the language I wanted to use.
After that, I chose to do a full trial run and make one test sheet. I used one piece of cardstock and wrote a header across the top to test the available space, created one data point circle to see how big I would be able to write, taped the circle to the sheet so that I could test whether it would move, attached several pieces of Con-Tact paper and clear tape to the cardstock, and mixed up several versions of scratch-off paint (a mixture of acrylic paint and clear dish soap) to see which one would scratch off of which surface the most successfully. I applied the different mixtures of scratch-off paint in various degrees of thickness to the different clear surfaces and left them to dry overnight.
The next day, I studied each option to see which would need a second coat of paint to fully obscure the data point, then added the second coat where needed and waited for them to dry. Then, I tried scratching off each type of paint with a coin. Interestingly, I found that the surface which the paint came off of the most easily was clear tape, not Con-Tact paper. However, I was worried about how the tape would hold up in the longer term, and so chose to use the second-best option, Con-Tact paper with a thick coat of scratch-off paint (two parts silver acrylic paint/one part clear dish soap).
After completing the testing phase, I started in on the creation of the scratch-off sheets!
Part 5: Artifact Creation
First, I wrote out the titles of each scratch off sheet on each of the four pieces of cardstock, using a ruler and another piece of cardstock to make sure that the lettering was even on all four cards. Next, I created the circles with the data points. I traced each circle out on cardstock and cut each one out; then, I wrote out one data point on each circle - 10 about bi+ youth and 10 about bi+ adults - for a total of 20 data points.
After making all of the data point circles, I arranged them on each sheet, and then placed contact paper on the front of each circle to laminate it and secure it to the card stock. I cut the piece of Con-Tact paper for each circle to be slightly bigger, to make sure that the paint would not run off. I also added double-sided tape to the back of the circles to make sure they would not come loose during the scratch-off process. Finally, I stuck each data point circle to the correct card in the order that I had arranged them.
Next, I mixed up the scratch-off paint according to the formula that I had determined during the testing process, and painted over each data point circle. I let the paint dry completely overnight, and then touched up any spots where the pen showed through the next day.
Finally, I attached each scratch-off sheet to a foam board with double-sided tape, to ensure that it was stable and would not tear or move during the scratch-off process. I also created and printed QR codes for the data sets that were used for each sheet and taped them to the backs of the boards.
After the boards were complete, I moved on to making the tokens to actually do the scratch off. I had originally wanted to 3D print four tokens, two each in the bisexual (pink, purple, blue) and pansexual (pink, yellow, blue) flag colors. I designed the 3D tokens in Tinkercad. I had to get creative with the design in order to print the tokens in three separate sections, so that they could be in three different colors. To do this, I first created short cylinders in the program. Then, I used “hole” objects and the “combine” feature to cut the token into three pieces. I left short tabs where each token piece would need to join with the others, so that I would be able to glue them together.
When I went to print the token pieces, I realized that it would not be possible to 3D print in purple. Therefore, I pivoted my approach. I 3D printed enough token pieces in pink, yellow, and blue to create two pan flag tokens. I used hot glue to attach the pieces together and then used sandpaper to smooth away the rough edges that were left over from the 3D print and the glue. For the bi flag tokens, I laser cut three circles out of wood, and then used pink, purple, and blue tape to create the bi flag colors on the tokens. Although it was not what I envisioned at the beginning of the project, I ended up being glad that I could showcase even more kinds of maker technologies in the final artifact.
The only way to find out whether the final versions of the scratch off sheets worked was to try them. As documented in the videos below, I was able to use both types of tokens to scratch off two data points about bi+ youth and adults! A pan-tastic outcome!
Part 6: Conclusion and Takeaways
Throughout working on this project, I kept D’Ignazio and Klein’s idea of the paradox of exposure in mind. The authors define this as “the double bind that places those who stand to significantly gain from being counted in the most danger from that same counting (or classifying) act” (D’Ignazio and Klein 105). Having always felt that more visibility was good for the bi+ community, I appreciated the opportunity to stop and reconsider that belief. Would creating these scratch off sheets and bringing light to little known data and facts about bi+ people end up putting the community in more danger? We already experience biphobia and erasure from within and outside of the LGBTQ community, so would exposing the harms that that causes in the form of data points cause more damage?
In the end, I felt that it would not. If the data points were easily traceable back to individual people, I think I would feel differently. But overall, I think that given the erasure and invisibility of the bi+ community and data about us, visibility is an overall positive. We deserve to have our needs recognized and addressed. Making data about us visible is a positive first step in doing this and improving outcomes for the community. Without first knowing about the problems, we will not be able to fix them. Moreover, sharing data – bad and good – can be a way to bring the community together. As Data Feminism says, “quantitative data can be empowering” (D’Ignazio and Klein 98). Separating out bi+ data, dismantling harmful stereotypes, and learning more about the bi+ community overall opens up more opportunities for the future (D’Ignazio and Klein 123).
Finally, I feel that libraries, as community centers and spaces where everyone should be welcome, can play a unique and important role in helping to support the bi+ community. Libraries can create and host programming that is bi+ specific, such as for Bi+ Health Month in March or Bi+ Awareness Week in September. The more that we can educate the wider community, LGBTQIA+ and allies, about the challenges that the bi+ community faces, as well as our resiliency, the farther we will be along the path to full equality. The aim of this project has been to explain the disparities that bi+ people face and back those disparities up with data about their implications. I hope that this has helped to bring visi-BI-lity to the stories and experiences of the bi+ community.
Made by: M Roberts (they/them)
Disclaimer: I worked for the Human Rights Campaign from 2017-2021 and was involved in the creation of the “Bi+ Youth Report,” the “Coming Out: Living Authentically as Bisexual+” report, and the “Coming Out as Bisexual to your Doctor” guide.
Works Cited
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Bisexual Organizing Project. “Virtual Backgrounds.” Because Conference, 2023, https://www.becauseconference.org/virtual-backgrounds.html. Accessed 30 Oct. 2023.
Bisexual Resource Center. “Bi+ Info: What It Means to Be a B(ee).” Bisexual Resource Center, https://biresource.org/bi-info/. Accessed 30 Oct. 2023.
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D’Ignazio, Catherine, and Lauren F. Klein. Data Feminism. The MIT Press, 2020.
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Feinstein, Brian A., et al. “Disclosure, minority stress, and mental health among bisexual, pansexual, and queer (Bi+) adults: The roles of primary sexual identity and multiple sexual identity label use.” Psychology of Sexual Orientation and Gender Diversity, vol. 10, no. 2, June 2023, pp. 181–89. EBSCOhost, APA PsycArticles, https://login.libproxy.lib.unc.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=pdh&AN=2021-87921-001&site=ehost-live&scope=site. Accessed 30 Oct. 2023. DOI:10.1037/sgd0000532.
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