Speak Data, page 3
Secondly, the treatment doesn’t have the same effect on everyone. There are contingencies. So instead of asking whether Advil is effective, we want to ask: For whom is it effective? When is it effective? This question of when and for whom allows us to look at the data and say: This is real, but only under certain circumstances. Now we need to know how widespread those circumstances are. This is real for some people. What are the commonalities of those people?
The last lesson from medicine is that what’s effective evolves over time. The problems we’re trying to treat can change. We need to update our evidence and ask: What are the best available data on any given question or for solving a given problem? Is there a reason why what was true ten, twenty, thirty years ago may not apply today? I would still rather base my opinions on strong evidence that’s old than no evidence at all, but we need to keep an eye on how things evolve as our contexts change.
Exactly. What’s the context? What are the nuances? Data is a snapshot in time. Tomorrow, or in a month, things might be different. Especially when we see data represented in a very definite and defined way, we assume it has absolute power to always represent a situation. This became a problem during the pandemic, of course.
I think the biggest pandemic takeaway regarding the role of data is that experts and public officials did a remarkably terrible job communicating about uncertainty and contingency. I should have known it was going to happen. Chapter 8 in my book Think Again, which I wrote before the pandemic, was about how you don’t lose trust when you say, “More research needs to be done,” or “Here are the initial conclusions, but there are conditions under which they may not hold,” or “Here is what our initial trials suggest. Once we’ve done more trials, we’ll update our conclusions.” And let people know what that process looks like and how the scientific research is not only done, but accumulated.
This is probably the most useful thing I’ve said to a friend of mine who is very skeptical about vaccines after three-plus years of debate. He would say to me, “One study says this and one study says the opposite!” My response is that you shouldn’t weigh both sides equally. You should weigh strong evidence more heavily than weak evidence.
We need to be much more nuanced in how we communicate. We need to clarify where there’s uncertainty. We need to highlight where there are contingencies. We need to be as open about what we don’t know as about what we do know. One of the things we saw during COVID-19 is that source credibility dominates message credibility. People will believe a weak argument from someone they trust much more readily than a strong argument from someone they don’t trust. One of the ways you become a trusted source is by very clearly admitting your uncertainty, showing intellectual humility, and expressing doubt where appropriate. I hope we don’t have to keep relearning that lesson over and over again.
What’s your personal definition of data?
Data are information gathered through systematic and rigorous observation.
We love that you say data are. To us as well, data is plural.
A datum, or a data point, is one piece of information. Data are the collections of those observations.
To change the subject slightly, you’ve spoken in the past about the relative power of data versus stories to influence people and change minds. This is also something we think a lot about in our work. When do you think a really powerful statistic is appropriate, versus when a human story is going to be more effective? And when can they be combined?
It’s a false dichotomy to say they can’t be combined. My point of view on the responsible use of stories is that we should start with the data and then find stories that illuminate the data.
Stories are often more effective at evoking emotion. They allow us to distance ourselves from our own perspectives a bit. In addition to immersing ourselves in the narrative, they immerse us in a character. We get transported into stories, and we tend to experience them more than we evaluate them. Sometimes that can make people less rigorous in scrutinizing data, and that becomes a problem when the stories aren’t guided by data.
The more surprising data are, the more likely they are to capture attention. If you have data that challenge people’s intuition, you’re much more likely to pique their curiosity. But you have to be careful, because, as the sociologist Murray Davis wrote in his classic paper “That’s Interesting!,” people are intrigued when you challenge their weakly held intuitions, whereas they get defensive when you question their strongly held intuitions. So there’s nuance there.2
From a visual perspective, we try to anchor stories in more aggregated data, but then disaggregate them by pulling out a couple of data points that can explain the context. By doing this in a narrative way, it can become more accessible, like a plot of a book. That’s really fascinating.
Another way to tell a story about data is to start with what people would expect, then lead them to overturning their assumptions. People often find that journey revealing and enlightening, and it can become an emotional arc.
Yet another thing I’ve learned is to present a surprising result and then ask people how they would explain it. It opens their minds quite a bit: they generate reasons they find persuasive, and thus become active participants in the dialogue. Instead of preaching your view or prosecuting theirs, you engage them in the process of thinking like a scientist and generating hypotheses. I quite enjoy that.
NOTES
1 Adam Grant, “‘You Can’t Say That!’: How to Argue, Better,” The Guardian, July 30, 2022, https://www.theguardian.com/lifeandstyle/2022/jul/30/you-cant-say-that-how-to-argue-better.
2 Murray S. Davis, “That’s Interesting!: Towards a Phenomenology of Sociology and a Sociology of Phenomenology,” Philosophy of the Social Sciences 1, no. 4 (December 1971): 309–44.
Andy Marra
Andrea “Andy” Hong Marra is a civil rights activist and CEO of Advocates for Trans Equality, a national nonprofit fighting for the legal and political rights of trans people in the United States. At A4TE, Andy oversees a team of lawyers, policy experts, and community organizers dedicated to ensuring that all people in US society are treated equally. A4TE also produces the US Trans Survey, the largest survey of trans people, by trans people, in the United States. A longtime leader in the LGBTQ+ movement, Andy is one of the country’s most salient voices on civil rights today. In this conversation, Andy discusses the role of data in advocacy work; the pros and cons of categorization; and why visibility does not necessarily lead to acceptance.
What has been the impact of data and databased evidence on the LGBTQ+ movement?
It’s a good question. I think it’s worth naming up front that the trans rights movement and the broader LGBTQ+ rights movement have made progress at breakneck speed in comparison to the vast majority of other social justice movements in the United States. In a little more than fifty years, we have seen marriage equality, nondiscrimination protections for LGBTQ+ folks in the workplace, and a number of other protections, including access to trans health care and making sure that LGBTQ+ young people are treated well in schools and have access to resources and support. We can point to several moments and markers that demonstrate how quickly the LGBTQ+ and trans rights movements have made progress.
For the broader LGBTQ+ rights movement, data collection has been incredibly important—a leading factor in making the case for policy and legal protections for trans people. In 1990, President George H. W. Bush signed the Hate Crime Statistics Act, which required the FBI to collect data on sexual orientation as it pertains to hate violence in the country. That opened the door for activists to be able to say, “Now you can’t deny that we exist. You have data that actually demonstrates that we exist. And not only do we exist, but we are disproportionately targets for hate violence in this country.”
You’re counting something that was never counted before.
Right. Data collection is incredibly important in that respect, and is an increasingly important subject more broadly among LGBTQ+ policy advocates. That said, the reality that we are currently living in and grappling with is that visibility does not translate into acceptance. We’ve seen cultural markers of progress with, say, celebrities like Laverne Cox on the small and big screens. We’ve seen more and more LGBTQ+ or trans-specific storylines in entertainment. There are issues being talked about openly in the news in a way that we have never seen before. But that visibility doesn’t necessarily serve as an indicator of acceptance. We are also witnessing an incredible amount of scrutiny and demonization of trans people across the country.1
I think this has a lot to do with marriage equality, meaning marriage for same-sex couples in this country. Those who oppose equality and justice learned a lot from the marriage equality movement, in which LGBTQ+ activists told very personal stories of loving, committed couples who simply wanted to be treated like everybody else. Instead of changing minds by talking about the thousands of rights that were being denied them, it was the stories about everyday folks next door who want to be able to get married and live lives very similar to their neighbors in their own communities. That is what moved this country toward unprecedented acceptance of marriage equality across the political spectrum, across faith and religion. To this day, overwhelming majorities support marriage equality.
The problem is that opponents to LGBTQ+ rights learned about what we call “hearts and minds” work—the changing-of-narratives work and the culture work—that they were woefully behind on. Today, opponents to trans rights use almost the same playbook that LGBTQ+ activists used to advance marriage equality. They are using stories. They are finding spokespeople from different identities, from different backgrounds, to propagate a narrative of vitriol and demonization. They are also using junk science to enable state legislatures to pass bills intended to criminalize various aspects of our lives. This has become the centerpiece of many political conversations in this country. As a result, trans people have become the latest scary monster. Trans people are now having to say, “We’re not monsters. We’re just everyday people like you.”
When you say data, how would you define that?
Data serves as a language. It’s a common language for a diverse number of stakeholders to consume and understand.
So much of this relates to how we define identity as individuals, as a culture, as a government, and then how we communicate that sense of identity to others. For better or for worse, that’s usually through a binary categorization: You are X or you are Y. What are the pros and cons of categorizations of this type?
Categorization is a helpful tool to indicate a person’s identity. It doesn’t tell the full story, but rather serves as a quick reference point or marker to give context to a person’s lived experience. And it tells us who they are in a legal context. To be legally recognized as your gender identity is incredibly important for trans people. It says, “Hey, this is who I am and how I identify, and here is a state-sanctioned document that demonstrates that.” Many people don’t ever give it much thought. But think about providing identification with your debit or credit card at the grocery store, or filling out an employment form, or filling out an intake form when you go to a medical facility. If a person encountering your identification sees your gender marker not aligning with how you are presenting to the world, it can create uncomfortable and even discriminatory conditions for you, or, worse, put you at actual risk of violence.
Also, when we say trans people, that encompasses a number of gender identities—for instance folks who are nonbinary. We are seeing more and more people come out and identify as nonbinary: Either they do not identify within the gender spectrum at all, or they identify with one or more aspects of identities within it. As a result, we’re seeing increasing numbers of states and jurisdictions honoring and recognizing those gender identities. The federal government and states across the country are introducing the X marker on government identification to honor folks who are either nonbinary or folks who do not identify as either male or female. We are making progress on the legal and political fronts to make sure we’re recognizing the full spectrum of folks who may or may not identify within the gender binary.
This pertains to even something like your US passport. Many people don’t think much of their passport, but it is a government ID and it allows you to leave and enter the country. People aren’t able to freely move around the world unless they have a passport. If a trans person travels to another country where the climate is more conservative or hostile, and a government official there deems the gender marker on their passport as not corresponding with their gender identity, it puts them at a greater risk.
Again, categorization is just a starting point. It is almost the first part or the preface to a much larger story to tell. When we look at something like government identification and see “male” or “female,” we think that’s a checkmark and the end-all be-all. But who I am is more than just what’s on my government identification.
Right. There’s two aspects here. There’s the legal aspect, which obviously has a lot of important implications for health and safety, government services, and more. But then there’s the more personal aspect, when one can say, “My government sees me how I see myself.” Which feels incredibly powerful and gratifying for anyone.
Data helps us make the case for advancing legal and policy protections in a number of areas. Take the Youth Risk Behavior Survey, a national survey distributed across the country to students and schools. It asks a number of questions to better understand the school and student experience. It wasn’t until approximately ten years ago that the survey started to include questions explicitly about gender identity so as to encompass the experiences of trans students, which in turn demonstrated that trans students are at greater risk of being harassed or bullied in school settings.
We’ve had to fight for the progress we’ve had, and to make the case stronger, we’ve often collected our own bodies of research. I think the US Trans Survey, which our organization produces, is a great example. It is the country’s largest body of research on the trans experience, and one of the top cited. We frequently refer to the US Trans Survey in amicus briefs and in actual lawsuits. I would say it is a hallmark body of research for the trans rights movement.
The US Trans Survey is also a survey about trans people created by trans people. Why is that important?
There is real utility for data—not just data collected by government agencies but also research that originates from the community itself. It’s not a body of research that I would say is owned by any one organization; rather it is a reflection of the entirety of the trans rights movement. And what makes this research so compelling and visionary is that it asks a diverse array of questions about not just the identity of trans people, but also how identity impacts a multitude of aspects of their lives—everything from health insurance to experiences of accessing medical care, applying for a job, going to school and walking down the hallway there. This research is the collective reflection of the trans experience in this country. The latest report secured almost one hundred thousand respondents, so it is a massive dataset. And we expect to be releasing more specialized reports from it.
But really, it legitimizes the trans experience. And it also, I think, encourages and inspires and challenges researchers across fields to further diversify, and drill down, in their own practices.
You said before that visibility does not necessarily lead to acceptance. How can we use data to build both visibility and acceptance for trans people? Do we need to think about data in a different way?
I’ve talked a lot about quantitative data, but qualitative data is incredibly important to the equation for social change and progress. The story behind data is always the starting point for me. But what is missing from the equation is the vehicle and the infrastructure to communicate that story effectively. So, yes, we have the stories, but are we reaching people in the right ways? And if not, how can we adapt so as to create the kind of impact we want?
We have made exceptional gains when it comes to data and technology, but I see a need for progressive movements broadly to grapple with how we apply these latest developments, including things like generative AI, to our work. A heightened segmentation or hyper-understanding of who your audience is and how to reach them is the secret sauce for having cultural impact, making a cultural or social change. We have the stories. We just need to figure out the best way to reach the people.
NOTES
1 “Youth Risk Behavior Surveillance System (YRBSS),” US Centers for Disease Control and Prevention, https://www.cdc.gov/yrbs/index.html.
2
Making Meaning: Data and Communication
Making Meaning
On an unassuming winter day, in an unassuming conference room in downtown Chicago, the end of the world is being counted down. Welcome to the reading of the Doomsday Clock, presented annually without fail since 1947 by the Bulletin of the Atomic Scientists. The clock itself isn’t much to look at—a rudimentary drawing of four dots and two lines—but its simplicity is deceiving. Like any good abstraction, it communicates a whole range of ideas with both powerful immediacy and ruthless efficiency.
Every year, the Bulletin convenes a panel of expert scientists and analysts to determine the clock’s movement. They make their determination based on a range of statistical indicators—data—which measure our world. Are we moving closer to global annihilation? The clock moves forward toward proverbial midnight; time is running out. Or, alternatively, are things improving and humanity has managed to work toward solving our most pernicious problems? The clock moves backward, away from midnight; for now, we’ve bought ourselves a bit more time. When the Bulletin began this ritual, on the eve of the Cold War, they set the clock at seven minutes to midnight. A lot has happened in the world since. As of 2024, the clock stands at 90 seconds to midnight.1
The last lesson from medicine is that what’s effective evolves over time. The problems we’re trying to treat can change. We need to update our evidence and ask: What are the best available data on any given question or for solving a given problem? Is there a reason why what was true ten, twenty, thirty years ago may not apply today? I would still rather base my opinions on strong evidence that’s old than no evidence at all, but we need to keep an eye on how things evolve as our contexts change.
Exactly. What’s the context? What are the nuances? Data is a snapshot in time. Tomorrow, or in a month, things might be different. Especially when we see data represented in a very definite and defined way, we assume it has absolute power to always represent a situation. This became a problem during the pandemic, of course.
I think the biggest pandemic takeaway regarding the role of data is that experts and public officials did a remarkably terrible job communicating about uncertainty and contingency. I should have known it was going to happen. Chapter 8 in my book Think Again, which I wrote before the pandemic, was about how you don’t lose trust when you say, “More research needs to be done,” or “Here are the initial conclusions, but there are conditions under which they may not hold,” or “Here is what our initial trials suggest. Once we’ve done more trials, we’ll update our conclusions.” And let people know what that process looks like and how the scientific research is not only done, but accumulated.
This is probably the most useful thing I’ve said to a friend of mine who is very skeptical about vaccines after three-plus years of debate. He would say to me, “One study says this and one study says the opposite!” My response is that you shouldn’t weigh both sides equally. You should weigh strong evidence more heavily than weak evidence.
We need to be much more nuanced in how we communicate. We need to clarify where there’s uncertainty. We need to highlight where there are contingencies. We need to be as open about what we don’t know as about what we do know. One of the things we saw during COVID-19 is that source credibility dominates message credibility. People will believe a weak argument from someone they trust much more readily than a strong argument from someone they don’t trust. One of the ways you become a trusted source is by very clearly admitting your uncertainty, showing intellectual humility, and expressing doubt where appropriate. I hope we don’t have to keep relearning that lesson over and over again.
What’s your personal definition of data?
Data are information gathered through systematic and rigorous observation.
We love that you say data are. To us as well, data is plural.
A datum, or a data point, is one piece of information. Data are the collections of those observations.
To change the subject slightly, you’ve spoken in the past about the relative power of data versus stories to influence people and change minds. This is also something we think a lot about in our work. When do you think a really powerful statistic is appropriate, versus when a human story is going to be more effective? And when can they be combined?
It’s a false dichotomy to say they can’t be combined. My point of view on the responsible use of stories is that we should start with the data and then find stories that illuminate the data.
Stories are often more effective at evoking emotion. They allow us to distance ourselves from our own perspectives a bit. In addition to immersing ourselves in the narrative, they immerse us in a character. We get transported into stories, and we tend to experience them more than we evaluate them. Sometimes that can make people less rigorous in scrutinizing data, and that becomes a problem when the stories aren’t guided by data.
The more surprising data are, the more likely they are to capture attention. If you have data that challenge people’s intuition, you’re much more likely to pique their curiosity. But you have to be careful, because, as the sociologist Murray Davis wrote in his classic paper “That’s Interesting!,” people are intrigued when you challenge their weakly held intuitions, whereas they get defensive when you question their strongly held intuitions. So there’s nuance there.2
From a visual perspective, we try to anchor stories in more aggregated data, but then disaggregate them by pulling out a couple of data points that can explain the context. By doing this in a narrative way, it can become more accessible, like a plot of a book. That’s really fascinating.
Another way to tell a story about data is to start with what people would expect, then lead them to overturning their assumptions. People often find that journey revealing and enlightening, and it can become an emotional arc.
Yet another thing I’ve learned is to present a surprising result and then ask people how they would explain it. It opens their minds quite a bit: they generate reasons they find persuasive, and thus become active participants in the dialogue. Instead of preaching your view or prosecuting theirs, you engage them in the process of thinking like a scientist and generating hypotheses. I quite enjoy that.
NOTES
1 Adam Grant, “‘You Can’t Say That!’: How to Argue, Better,” The Guardian, July 30, 2022, https://www.theguardian.com/lifeandstyle/2022/jul/30/you-cant-say-that-how-to-argue-better.
2 Murray S. Davis, “That’s Interesting!: Towards a Phenomenology of Sociology and a Sociology of Phenomenology,” Philosophy of the Social Sciences 1, no. 4 (December 1971): 309–44.
Andy Marra
Andrea “Andy” Hong Marra is a civil rights activist and CEO of Advocates for Trans Equality, a national nonprofit fighting for the legal and political rights of trans people in the United States. At A4TE, Andy oversees a team of lawyers, policy experts, and community organizers dedicated to ensuring that all people in US society are treated equally. A4TE also produces the US Trans Survey, the largest survey of trans people, by trans people, in the United States. A longtime leader in the LGBTQ+ movement, Andy is one of the country’s most salient voices on civil rights today. In this conversation, Andy discusses the role of data in advocacy work; the pros and cons of categorization; and why visibility does not necessarily lead to acceptance.
What has been the impact of data and databased evidence on the LGBTQ+ movement?
It’s a good question. I think it’s worth naming up front that the trans rights movement and the broader LGBTQ+ rights movement have made progress at breakneck speed in comparison to the vast majority of other social justice movements in the United States. In a little more than fifty years, we have seen marriage equality, nondiscrimination protections for LGBTQ+ folks in the workplace, and a number of other protections, including access to trans health care and making sure that LGBTQ+ young people are treated well in schools and have access to resources and support. We can point to several moments and markers that demonstrate how quickly the LGBTQ+ and trans rights movements have made progress.
For the broader LGBTQ+ rights movement, data collection has been incredibly important—a leading factor in making the case for policy and legal protections for trans people. In 1990, President George H. W. Bush signed the Hate Crime Statistics Act, which required the FBI to collect data on sexual orientation as it pertains to hate violence in the country. That opened the door for activists to be able to say, “Now you can’t deny that we exist. You have data that actually demonstrates that we exist. And not only do we exist, but we are disproportionately targets for hate violence in this country.”
You’re counting something that was never counted before.
Right. Data collection is incredibly important in that respect, and is an increasingly important subject more broadly among LGBTQ+ policy advocates. That said, the reality that we are currently living in and grappling with is that visibility does not translate into acceptance. We’ve seen cultural markers of progress with, say, celebrities like Laverne Cox on the small and big screens. We’ve seen more and more LGBTQ+ or trans-specific storylines in entertainment. There are issues being talked about openly in the news in a way that we have never seen before. But that visibility doesn’t necessarily serve as an indicator of acceptance. We are also witnessing an incredible amount of scrutiny and demonization of trans people across the country.1
I think this has a lot to do with marriage equality, meaning marriage for same-sex couples in this country. Those who oppose equality and justice learned a lot from the marriage equality movement, in which LGBTQ+ activists told very personal stories of loving, committed couples who simply wanted to be treated like everybody else. Instead of changing minds by talking about the thousands of rights that were being denied them, it was the stories about everyday folks next door who want to be able to get married and live lives very similar to their neighbors in their own communities. That is what moved this country toward unprecedented acceptance of marriage equality across the political spectrum, across faith and religion. To this day, overwhelming majorities support marriage equality.
The problem is that opponents to LGBTQ+ rights learned about what we call “hearts and minds” work—the changing-of-narratives work and the culture work—that they were woefully behind on. Today, opponents to trans rights use almost the same playbook that LGBTQ+ activists used to advance marriage equality. They are using stories. They are finding spokespeople from different identities, from different backgrounds, to propagate a narrative of vitriol and demonization. They are also using junk science to enable state legislatures to pass bills intended to criminalize various aspects of our lives. This has become the centerpiece of many political conversations in this country. As a result, trans people have become the latest scary monster. Trans people are now having to say, “We’re not monsters. We’re just everyday people like you.”
When you say data, how would you define that?
Data serves as a language. It’s a common language for a diverse number of stakeholders to consume and understand.
So much of this relates to how we define identity as individuals, as a culture, as a government, and then how we communicate that sense of identity to others. For better or for worse, that’s usually through a binary categorization: You are X or you are Y. What are the pros and cons of categorizations of this type?
Categorization is a helpful tool to indicate a person’s identity. It doesn’t tell the full story, but rather serves as a quick reference point or marker to give context to a person’s lived experience. And it tells us who they are in a legal context. To be legally recognized as your gender identity is incredibly important for trans people. It says, “Hey, this is who I am and how I identify, and here is a state-sanctioned document that demonstrates that.” Many people don’t ever give it much thought. But think about providing identification with your debit or credit card at the grocery store, or filling out an employment form, or filling out an intake form when you go to a medical facility. If a person encountering your identification sees your gender marker not aligning with how you are presenting to the world, it can create uncomfortable and even discriminatory conditions for you, or, worse, put you at actual risk of violence.
Also, when we say trans people, that encompasses a number of gender identities—for instance folks who are nonbinary. We are seeing more and more people come out and identify as nonbinary: Either they do not identify within the gender spectrum at all, or they identify with one or more aspects of identities within it. As a result, we’re seeing increasing numbers of states and jurisdictions honoring and recognizing those gender identities. The federal government and states across the country are introducing the X marker on government identification to honor folks who are either nonbinary or folks who do not identify as either male or female. We are making progress on the legal and political fronts to make sure we’re recognizing the full spectrum of folks who may or may not identify within the gender binary.
This pertains to even something like your US passport. Many people don’t think much of their passport, but it is a government ID and it allows you to leave and enter the country. People aren’t able to freely move around the world unless they have a passport. If a trans person travels to another country where the climate is more conservative or hostile, and a government official there deems the gender marker on their passport as not corresponding with their gender identity, it puts them at a greater risk.
Again, categorization is just a starting point. It is almost the first part or the preface to a much larger story to tell. When we look at something like government identification and see “male” or “female,” we think that’s a checkmark and the end-all be-all. But who I am is more than just what’s on my government identification.
Right. There’s two aspects here. There’s the legal aspect, which obviously has a lot of important implications for health and safety, government services, and more. But then there’s the more personal aspect, when one can say, “My government sees me how I see myself.” Which feels incredibly powerful and gratifying for anyone.
Data helps us make the case for advancing legal and policy protections in a number of areas. Take the Youth Risk Behavior Survey, a national survey distributed across the country to students and schools. It asks a number of questions to better understand the school and student experience. It wasn’t until approximately ten years ago that the survey started to include questions explicitly about gender identity so as to encompass the experiences of trans students, which in turn demonstrated that trans students are at greater risk of being harassed or bullied in school settings.
We’ve had to fight for the progress we’ve had, and to make the case stronger, we’ve often collected our own bodies of research. I think the US Trans Survey, which our organization produces, is a great example. It is the country’s largest body of research on the trans experience, and one of the top cited. We frequently refer to the US Trans Survey in amicus briefs and in actual lawsuits. I would say it is a hallmark body of research for the trans rights movement.
The US Trans Survey is also a survey about trans people created by trans people. Why is that important?
There is real utility for data—not just data collected by government agencies but also research that originates from the community itself. It’s not a body of research that I would say is owned by any one organization; rather it is a reflection of the entirety of the trans rights movement. And what makes this research so compelling and visionary is that it asks a diverse array of questions about not just the identity of trans people, but also how identity impacts a multitude of aspects of their lives—everything from health insurance to experiences of accessing medical care, applying for a job, going to school and walking down the hallway there. This research is the collective reflection of the trans experience in this country. The latest report secured almost one hundred thousand respondents, so it is a massive dataset. And we expect to be releasing more specialized reports from it.
But really, it legitimizes the trans experience. And it also, I think, encourages and inspires and challenges researchers across fields to further diversify, and drill down, in their own practices.
You said before that visibility does not necessarily lead to acceptance. How can we use data to build both visibility and acceptance for trans people? Do we need to think about data in a different way?
I’ve talked a lot about quantitative data, but qualitative data is incredibly important to the equation for social change and progress. The story behind data is always the starting point for me. But what is missing from the equation is the vehicle and the infrastructure to communicate that story effectively. So, yes, we have the stories, but are we reaching people in the right ways? And if not, how can we adapt so as to create the kind of impact we want?
We have made exceptional gains when it comes to data and technology, but I see a need for progressive movements broadly to grapple with how we apply these latest developments, including things like generative AI, to our work. A heightened segmentation or hyper-understanding of who your audience is and how to reach them is the secret sauce for having cultural impact, making a cultural or social change. We have the stories. We just need to figure out the best way to reach the people.
NOTES
1 “Youth Risk Behavior Surveillance System (YRBSS),” US Centers for Disease Control and Prevention, https://www.cdc.gov/yrbs/index.html.
2
Making Meaning: Data and Communication
Making Meaning
On an unassuming winter day, in an unassuming conference room in downtown Chicago, the end of the world is being counted down. Welcome to the reading of the Doomsday Clock, presented annually without fail since 1947 by the Bulletin of the Atomic Scientists. The clock itself isn’t much to look at—a rudimentary drawing of four dots and two lines—but its simplicity is deceiving. Like any good abstraction, it communicates a whole range of ideas with both powerful immediacy and ruthless efficiency.
Every year, the Bulletin convenes a panel of expert scientists and analysts to determine the clock’s movement. They make their determination based on a range of statistical indicators—data—which measure our world. Are we moving closer to global annihilation? The clock moves forward toward proverbial midnight; time is running out. Or, alternatively, are things improving and humanity has managed to work toward solving our most pernicious problems? The clock moves backward, away from midnight; for now, we’ve bought ourselves a bit more time. When the Bulletin began this ritual, on the eve of the Cold War, they set the clock at seven minutes to midnight. A lot has happened in the world since. As of 2024, the clock stands at 90 seconds to midnight.1
