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Section 5.3 Visualizing the Data

Motivating Ideas.

In this section I will...
  • Learners will investigate the supposed neutrality of Data.
  • Learners will be able to formulate questions based on available data and extract the data needed to make informed and justified claims.
  • Learners will be able to storytell through visualization and be able to evaluate what an author is trying to say when they choose a visualization.
There has been a dramatic rise in anti transgender legislation being proposed and being passed across the US. These bills have very real and horrible effects on people’s lives. How do we conceptualize how overwhelming these numbers are? How do we make sure that we are still humanizing the data as we work with it? Youtuber Lindsay Ellis refers to this as the vulgarity of numbers in her video essay "The unforgivable sin of Ms. Rachel"
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www.youtube.com/watch?v=QwpanShgOp4ampt=1s
. One tool we can learn in this chapter is to explore the numbers from different numerical lenses. We can also explore how people gather and talk about data on transgender individuals.

Subsection 5.3.1 Looking at Data about Anti-transgender legislation (making sense of the numbers we see)

There are many ways people choose to represent data. We use visuals to quickly communicate ideas to others. From bargraphs and tables, scatterplots, maps, to infographics and more we can tell a story about a population or problem.

Activity 1.

In this activity, we will consider data on bills that impact transgender and gender-diverse people across the United States from Trans Legislation Tracker
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translegislation.com/
. Trans Legislation Tracker is an independent research organization tracking bills that impact trans and gender-diverse people across the United States. The link we are using goes to 2025 data.
Begin by going to the Trans Legislation Tracker above.
  1. What is the first thing you notice?
  2. Scroll down to the graph displaying the number of anti-transgender bills that were considered versus the number that were passed. What are your initial thoughts on the way this data is presented?
  3. Now, scroll down to the section that displays the types of bills that are being proposed. What different pieces of information are you able to gather from this section? Try to name at least two.
  4. For the map-based visualization of anti-transgender bills, select one or more states. What do you notice across the different states you selected? Feel free to comment on the data and information itself or also on the way it is displayed.
  5. Navigate to the β€œPrevious Years” tab on the navigation bar. Select a past year and compare your findings.

Subsection 5.3.2 Reading the Story from Data

Many places document data about anti-transgender legislation that are introduced, however the questions they ask differ. In this section, we will explore what stories are highlighted through different datasets.

Activity 2.

In this activity we’ll use data sets created by the ACLU to help us see what questions we wondered in the preactivity we can answer as well as become comfortable with exploring data sets using spreadsheets. The ACLU (American Civil Liberties Union) has tracked anti-LGBTQ bills in the U.S. State Legislature in years 2023
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www.aclu.org/legislative-attacks-on-lgbtq-rights-2023
, 2024
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www.aclu.org/legislative-attacks-on-lgbtq-rights-2024
, and 2025
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www.aclu.org/legislative-attacks-on-lgbtq-rights-2025
.
  1. What does this data tell us?
    1. Download the CSVs of this data (there is a link to do so at the bottom of the table).
    2. Review the dataset. What do you notice? What is interesting about this data?
    3. Choose a state. How many bills were defeated in that state? How many bills were passed into law? Are there issues that are more likely to be defeated? Are there issues that are more likely to be passed into law?
    4. Compare what your group discovered to what other groups discovered about their states. What do you wonder?
    5. Use the data to try to explore your questions that you wondered in the preactivity or what you are wondering now.
  2. Graphs and charts are a powerful way to explore data. Using data from your state, create a graph to revisualize the data. For example, you can explore the status of the bills or the issues of the bills.
  3. What is missing from this data?
  4. What stories are told by the sites, vs what stories are your visuals telling us.
  5. What are the other ways this story could be told?
The numbers on the translegislation
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translegislation.com/
tracker are really large and it can be difficult to fathom or be hard to grapple with. Number sense and exploration allow us to get a better understanding of the information. For example, we can answer what proportion of anti transgender legislation is passing. But without other numbers to compare this to, it can still be difficult to understand the scale at which these bills are being created.

Subsection 5.3.3 Data Provenance and Sovereignty

Our lived experiences shape how we perceive the world around us and what becomes important to us when we do anything from watching a movie, reading headlines, or as you did before, reading data.

Activity 3.

In this activity we will look at some other sources of data about the transgender community. The United States Transgender Survey
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transequality.org/sites/default/files/2025-06/USTS_2022Health%26WellbeingReport_WEB.pdf
was conducted in 2022 by the National Center for Transgender Equality (NCTE), an organization which advocates for transgender and gender-nonconforming people. Read through the report and reflect on the following questions:
  1. When you read the study, are there things that you don’t understand or have questions about? Are there terms that you don’t recognize? What information about the transgender community do we need to know as background to understand this study?
  2. Think about the ways that you’ve seen transgender and gender non-conforming people portrayed in media - books, tv shows, movies, news, or on the web. How do our lived experiences and media consumption shape our expectations about those basic data? How do these experiences shape our reading of data?
  3. Fairness and Accuracy in Reporting (FAIR) released a study on the portrayal of transgender rights issues in the New York Times
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    fair.org/home/nyt-less-interested-than-ever-in-trans-perspectives-on-trans-issues/
    . Read through the study. How do you think this is related to your answer to the previous question? How could this affect the way that people think about transgender rights and anti-transgender rights legislation?

Activity 4.

You’ve now seen some data on anti-transgender legislation and some data on transgender rights collected by the NCTE. In this activity, we’ll look at data collected about the transgender community from other sources.
  1. The Pew Research Center is a well-respected nonpartisan think tank. In 2025 they released a study about attitudes toward transgender rights in the United States
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    www.pewresearch.org/short-reads/2025/02/26/americans-have-grown-more-supportive-of-restrictions-for-trans-people-in-recent-years/
    . Read through this study. What stories does this data tell us?
  2. The Williams Institute at the University of California, Los Angeles studies sex and gender issues in public policy. In 2022 they released a study on the makeup and concerns of the transgender population in the United States
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    williamsinstitute.law.ucla.edu/wp-content/uploads/Trans-Pop-Update-Jun-2022.pdf
    . Read through this study. What stories does the data tell us?
  3. How do the stories from these studies differ? How are they the same?
  4. Think about your own lived experiences around these issues. How did this impact how you read and interpreted the data?
  5. Think about the data you saw in the previous section and the data in this section. How did the story you read from those studies differ from what you read today?
  6. Data is a valuable tool for understanding complicated issues and helping us make decisions. When we look at data about people, though, we always need to remember the people behind the data.
    1. When we collect survey data, the researchers choose which questions they ask. How can the questions we choose erase people’s identities?
    2. How can we collect data about vulnerable people in a way that is ethical?
There are principles we can hold to in order to avoid problems the PewResearch and NYT have perpetuated. For example, when we work with gathering data on communities we could model after what Indigenous communities have created around their data: the CARE Principles for Indigenous Data Governance in mind (Global Indigenous Data Alliance (2022)).

Definition 5.3.1. Data Provenance.

Data provenance is the story of how the data was collected and for what purpose.

Definition 5.3.2. Data Sovereignty.

Data sovereignty means that data generated within a country’s borders is governed by that nation’s laws and regulatory frameworks; this ensures local control over data access, storage, and usage.

Exercises Exercises

  1. Reflection
    1. How does our lived experience change how we read data. Look back at what you first thought on these issues, how does that reflect on your lived experience. What has changed?
    2. Read Care Principles for Indigenous Data Governance
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      static1.squarespace.com/static/5d3799de845604000199cd24/t/6397b1aff7a6fb54defdf687/1670885815820/dsj-1158_carroll.pdf
      . Where did these principles come from and in what ways were these principles ignored by Pew Research and NYT?