Rhea Boyd MD, MPH is a pediatrician, public health advocate, and scholar who writes and teaches on the relationship between structural racism, inequity and health. She has a particular focus on the child and public health impacts of harmful policing practices and policies. She serves as the Chief Medical Officer of San Diego 211 and the Director of Equity and Justice for The California Children’s Trust.
Dr. Boyd graduated cum laude with a B.A. in Africana Studies and Health from the University of Notre Dame. She earned a M.D. at Vanderbilt University School of Medicine and completed her pediatric residency at University of California, San Francisco. In 2017, Dr. Boyd graduated from
the Commonwealth Fund Mongan Minority Health Policy Fellowship at Harvard University’s School of Public Health, earning an M.P.H.
Rhea and I talk not only talk about the content of her work, but also her approach to writing about these topics, especially in public health and medical journals. We also talk about disinformation, and the push to distrust facts and science.
Rhea Boyd et al, Health Affairs, On Racism: A New Standard For Publishing On Racial Health Inequities
Rhea Boyd et al, New England Journal of Medicine, Stolen Breaths
Rhea Boyd, The Lancet, Despair doesn’t kill, defending whiteness does
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Welcome back to the PolicyViz podcast. I’m your host, Jon Schwabish. On this week’s episode of the show, I’m really excited to chat with Rhea Boyd, who is a doctor, a pediatrician, a public health advocate, and most importantly, for our discussion, a scholar who writes about and teaches on the relationship between structural racism, inequity in health. And we spend a bunch of time talking about her writing style, because I think it’s an interesting approach to writing about race and racism to an academic community, which, as I’m sure everybody who listens to this podcast knows, can be a little jargon filled and a little hard to wade through. But she has done some incredible writing on these very hard issues for that academic community. And we also talk about the importance of thinking about the data that we use and the data that we visualize and how that may contribute to racism, structural racism, institutional racism, and the culture in which we live. So I hope you’ll enjoy this week’s episode of the podcast. It is a little bit different than some previous episodes, but it’s a fascinating conversation, and I hope you’ll enjoy it. So here’s my discussion with Rhea Boyd.
Jon Schwabish: Hi Rhea. Welcome to the show. So great to have you.
Rhea Boyd: Hey Jon, thank you for having me. I’m excited to be here.
JS: I am very excited to chat with you. We’ve got a lot to talk about. You’ve been doing some amazing work. I have only become aware of your work in the last year plus or so, and then spending most of my time just flipping back and back and just keep reading everything you’ve written. So I’m really excited to chat with you. I thought we would start by just having you maybe introduce yourself to folks who are not familiar with your work.
RB: Sure. My name is Rhea Boyd. I’m a pediatrician, a public health advocate, and a scholar who writes and teaches about the impacts of racism and inequity on health.
JS: So there’s a couple of articles I want to talk about. There’s one that you wrote in the New England Journal of Medicine and one you wrote in Health Affairs, and several others you’ve written in more, I’d say, popular sort of standard news media. But the pieces you’ve written in the Journal of Medicine and Health Affairs are, I think, unique for those styles of publishing. They are academic at their core I think, but not the way you’ve written them. So can you maybe start talking, just talk about maybe your work, how you work on the intersection of racism and inequity and equality and health, and then we can maybe talk about the style that you write and try to communicate to this kind of particular academic style audience, but you don’t do it in sort of academic kind of jargon riddled way.
RB: Thanks for saying that. So a quarter of my work is just trying to lay out for people the building blocks, and then the threads that kind of link building blocks. So if some of those building blocks are material resources or access to free space or all of the structures that kind of make up our lived experience, what are the threads that connect those structures such that certain people live longer than other people. And the threads that I tend to talk through or the frames or analytics that I tend to use center on racism, white supremacy, and inequality to understand why certain folks have access to certain resources and other folks don’t, and the ultimate impact that that differential access makes for people’s kind of life chances. Because I’m trying to connect building blocks for people, I often conceptualize my writing as a teacher, and it’s also a part of the way that I learn better when I’m thinking through what are those building blocks and how are they associated with each other, what’s their relationship to each other. It helps me to write that down, and then usually in my writing process, I write it down, and then I say it out loud to myself to see, like, does that make sense. And then, the more, I think writing it, maybe it’s just a practice by which I kind of learn it, like, my brain grasps it and then I got it, and then I can move on to the next thing that I want to learn and think through. So it’s a way that I learned, and so then it becomes a way also that I teach other people. So I’m glad to know that you found it an approachable way of writing because it, I think, for me, it’s an approachable way for me to learn something and to teach it to somebody else.
JS: Right. Well, it’s interesting, because at least in these two instances, they’re very academic publications and yet, I found them, you know, I’m not in the medical field, the biology field. So like, if I was going to read the New England Journal of Medicine, I expect to go into it not really understanding anything, but the style of the writing is such that it could have been a blogpost almost anywhere. But you are steeped in this literature and in this area, so when you write in that way, you’re thinking about this different audience, like, how do you put yourself in that framework or in that mindset that I’m not going to write like an academic today, I’m going to write for an academic publication, but I’m going to write for a broader audience?
RB: This is a really interesting question, because I don’t necessarily approach it in that way. And I would offer it to any trainees or students listening or maybe people who are already further along in their career, but want to start writing more, I would offer to them my approach, which is, I try to write in my clearest voice, and that is my goal for every piece that I put out. And this is a harder thing to copy, but there’s something just inside me that knows when it’s there, like, something clicks, and I know that I’ve got it, like, this is my clearest articulation of that idea, and so I’m going to submit it or I’m going to offer this. And then I do that, whether I’m writing for my own blog, I started writing as a blogger, or, for honestly, New England Journal or Pediatrics or the Lancet or the Nation, or other lay media sources. I wrote a piece for NBC News last year. I write them all through that same voice; and there are a few differences, to be honest, I think, maybe more when I write for a lay audience, they appreciate more stories than is required for academic writing. But at the same time, I start all of my academic pieces with a historical grounding, like, I’m going to write about a topic and this is why it matters to me, and this is an actual human who lived and their experience, and now we’re going to talk about the topic. So I tend to also use stories, not invented stories, but actual true historical narratives to also shape all of my academic writing.
JS: Right. So I want to talk about the content of your work, and specifically, some of the things that you mentioned in this Health Affairs article that I’ll link to in the show notes, but you talk about, specifically for researchers, things that they should do around race and racism, that they should define race in the design of their study, which I assume extends to how they talk about it in the actual paper or report, you talk about naming racism. And I’m just curious, maybe you could just explain for listeners, those two concepts when it comes to researchers about defining and naming race and racism, what they should keep in mind, because I think while this piece is for Health Affairs, which tends to be more of an academic literature, I think people in the data visualization field and in the data field need to be thinking along the same lines, about the words that we use and the labels that we use, in any of the graphs and any of the visuals that we’re creating.
RB: Yeah, absolutely. I mean, part of the impetus for writing that article on Health Affairs is because the benchmark or what is acceptable for writing around racial health inequities is just so much lower than any other scientific inquiry, like, all of a sudden, it just is totally acceptable to have, in medical journals, in like, the actual canon that we rely on as our evidence base for clinical practice, to not define the primary variable we’re studying. You always have to define it, you have to tell people the boundaries around what you’re studying and what it means to the study. And so then, when you don’t do that for race, in particular, when you use that as a variable, when you study racial groups and you don’t say how you understand race, you don’t contextualize it, and how you were using that variable, the implicit assumption is that race is then a biologic entity in this study. The difference between racial groups is innate, and if there’s a health difference that’s found between racial groups, then that must be from a genetic difference or a biologic difference between these two groups instead of a social difference. And so the importance of defining it as a variable is, one, just to meet the basic standards of research; and then, two, to make it clear to readers of your research how you understand that race is socially constructed, it’s made up and not a reflection of somebody’s ancestry or somebody’s genetic makeup. And so then, once you define race as a variable, it’s important to then name racism as a potential cause for any racial health inequities you find. It’s important to explore racism because, essentially, racism is what gives us race, this process by which we’re trying to create a hierarchy in society by racial groups, and then to distribute resources based on that hierarchy by racial groups reinforces the idea that certain racial groups are superior and inferior. And so, you have to name racism as one of the drivers for racial health inequities, because it also describes the ways that we remake and reinforce the notion of race and racial hierarchy in society, because it’s that hierarchy that then leads to the resource inequities that then lead to that health inequities.
RB: And then the thing that I add after I say we should name racism is always that, once you name it, you also then have to identify the mechanism by which you think it’s working in your particular study, to lead to that disparate health outcome. It’s critical to name the mechanism, I think we’re at a window now where finally people, post the murder of George Floyd, like, finally, editors and reviewers are asking people who write about racial health inequities to say something about racism in their discussion section or in their work. So now people will use the word racism, like, this may be due to racism. But that in and of itself is wholly insufficient. What we really need to actually move towards interventions is to know, okay, it was racism, but how was it functioning? Was it functioning through residential segregation? Was it functioning through discrimination and the direct effects of discrimination on certain hormonal pathways that might increase risk for toxic stress or raise one’s allostatic load, like, what are the mechanisms? These things have been studied, they have terms, they have whole basis in the literature, they have whole fields that have been written about different mechanisms by which racism could work. So then tell us one that you think as researchers that might be operative there so that people can better understand those connections. So the goal was to say, hey, we’re doing a really terrible job actually, and we’re letting a lot of stuff fly that’s actually not good science, and so we need to raise our game.
JS: Yeah. So why do you think it is that this field has not discussed race and racism – I mean, in the economics field that I’m familiar with, I can tell you why I think it’s not discussed there, none of them are good reasons – but why has this field of biology and medical journals, why is that discussion not been had? Is it just because the people who are conducting the research tend to be white men?
RB: This is [inaudible 00:12:29] but I think maybe the simplest way to say why we don’t talk about it is white supremacy, and maybe to your point, more directly, also, white patriarchy. What I mean by white supremacy is because predominantly white men and white folks in general have the power over journals, they will be editors and chiefs of major academic medical journals, they will be the entire editorial staff, they sometimes will be the vast majority of authors who have accepted publications, because white folks control the process by which we understand the medical evidence base, like, then the medical evidence base for centuries preferenced the opinions of white folks. And it’s important to acknowledge that there was a time when we continued to kind of grapple with and [inaudible 00:13:21] this time, where people actually argued that races are like genetically distinct beings, like different races are not both the same type of humans, and that some are superior and some are inferior just by virtue of their race, and that is genetic, and it’s innate. And then some would even argue that God wanted it that way, and so, that is kind of the history of how we have come to think about, that’s a brief and very crude history of how we’ve come to think about race in medicine that people use race as a way to support honestly, like, political and social relations at the time, like, early in medicine, probably we’re talking the 17th, 18th century, post-slavery, like, during slavery.
At the same time that society was saying, is it right that we should have certain people be enslaved, is there something deeply inhumane about this practice and undemocratic about this practice in this fledgling democracy, at the same time that we were having those conversations, people who were pro-slavery turned to the sciences to say, help us back up with the perception of objectivity in science, the fact that we enslave a group of human beings. And science was more than willing to oblige and not just oblige to completely profit off of slavery, both because of the experimentation on enslaved bodies, but also because doctors then would work for plantation owners and actually do the exams and try to test the fitness, quote-unquote, of enslaved folks to determine their worth in the slave market. And so medicine was deeply entrenched, and science was then deeply entrenched in this political and social kind of tension at the time, and science took a side, the side that promoted their own kind of wealth and social standing as doctors. And so, that’s the history from which we now have to question that science back then to say, actually, there is no evidence that races identify genetically distinct groups, there’s zero evidence of that.
And so, if there’s no evidence of that, then we have to acknowledge that the incentives, the political and social incentives of making those claims at that time shaped what people then called science, and that was bad science. And we still see remnants of that now, and so, I’ll say, I know this maybe a complicated subject for folks, but when I say white supremacy is the reason we don’t do this is both because of that history, and because even now we find ourselves in those same debates – those same debates about his race genetic, and how should we talk about race and racial health inequities. In either ways, that kind of ignore racism as a main driver, which then leads to question whether or not it’s genetic, or that offer an alternate hypothesis, it’s not racism, it’s poverty; it’s not racism, it’s the individual choices of certain patients who happen to be predominantly black or brown or from a certain immigrant group. Right? Even when people offer those alternative hypotheses, if you don’t engage with racism, you missed the fact that there’s these political and social processes happening that are dictating these outcomes. You’re still getting it essentially wrong, and you’re still being shaped by the tensions of your time.
JS: So I wonder about the intersection between the culture of a research team or, more broadly, just an organization, the intersection of the culture of that organization and the analysis that’s performed. So do you have thoughts on how that interacts – I mean, I think the basic way that I’ve heard people talking about this is if we have a diverse workforce, our work is going to be, is going to better reflects in different communities. For me, if I’m doing research on an accumulation of wealth among low income, black headed households, just because I work with someone who identifies as black doesn’t mean that they’re going to be able to help me with that study. Like, that to me seems like not quite the right way to think about it. But having thought about this intersection between the culture of, you had mentioned a research group, which is what sort of spurred my thought on this, the intersection of a research group which might be primarily men or primarily white men, and the analysis that’s performed and how when you have a different type of group or different sort of cultural norms that it affects the analysis that someone does.
RB: Gosh, this is, we’re really getting into it, Jon. I mean, these are really complicated questions.
JS: Yeah, I thought we were just going to talk about graphs, but this is much more interesting, and much more important.
RB: It is. I mean, okay, so let’s tease this out, because, first we’ll take they are predominantly white researcher group. The problem is that historically, obviously, I use that historical example, to talk about how we kind of came to have folks who are predominantly white, be in these positions of power that then served their economic and political and social interests. But now, when we think about predominantly white folks who are in positions of power, I think it’s critical that we use that same frame, that it’s not just that you’re white, it’s that because you’re white, you have a certain positionality in society, in a society that has been based on white supremacy, on the dominance of white, the white racial group. And so, that positionality in society means you benefit from the ways that we look away from racism and the other forces that keep you in that positionality. And so, if you benefit from that tangibly, materially, you live longer because of it, then you may be less willing to then be critical of or analyze the ways that racism is the reason that you have that positionality or racism is the reason, in your research findings, you see these differences between racial groups where white folks tend to fare better. I think, to then talk then about black research groups or research groups of color, it does not necessarily mean that a researcher of color will then hold a certain analysis when it comes to certain racial groups.
RB: That’s not necessarily true in any means, and nobody should just assume that. And I think, right now, how we talk about diversity in this very symbolic way, like, just having black folks around that make organizations less racist, it’s just, it’s untrue, and it’s really disappointing. It’s disappointing because it’s so untrue, and there are so many people whose lives depend on us getting this right, and we’re just hanging our hats on these symbolic changes. So those symbolic changes are, to a certain extent, completely symbolic, and yet, it’s also critical to recognize that historically, black folks as a population have held some of the sharpest analysis of racism and white supremacy our society has; I’d say black folks have and indigenous populations have, they know how systems work, they know how systems harm people, they know how structural racism works to benefit white folks above other groups, they know the business practices that undergird structural racism and they call it out all the time. And yet, we often dismiss the ways they call it out. We dismiss it because we say it’s not evidence based. That’s just your personal experience and not representative of a larger, more generalized group. Or we dismiss it because we say you didn’t write that in an academic voice, right, you didn’t say that to us in a way that we understand you’re not using the language and the jargon and the terms that we’re used to, so that can’t be true. Or we dismiss it because we say, that’s ridiculous, like, I actually think we live in a post racial society. I mean, remember that post Obama, when people were pretending racism was just over, who were the people who said that sounds ridiculous? Black folks were. Who were the people that said Trump was a white supremacist? Black folks were. And we called them ridiculous, and we said what they said was hyperbole. We said, you’re going too far. So what if he disavowed the head of the KKK? So what if he said there’s good people on both sides of racial terrorism? It doesn’t mean anything. We diagnosed it.
And so I think that’s to say that we also have to acknowledge that there have been folks who have been trying to say and do this work for centuries, and we have silenced then. And so, part of inviting folks of color into the academy is not just because their mere presence means we are progressing, it’s because we have needed to listen and pay attention to the sharp and absolutely right on analysis that they have held, that we have excluded from our own discussions, that we’ve excluded from our medical journals, that we’ve just excluded from our canon.
JS: Right. So then turning back to your recommendations to what researchers and journals should do to help define race and name racism and call these issues out, I wonder, do you feel like researchers and authors should be more upfront about their lived experiences, and that that should be part of a standard research study that the authors should have to say, this is who I am, and this is how I identify and this is my background, and sort of like taking that step further, like, does that bog down the sciences that make the science better, are there other ways, like, do people need to write positionality statements, in addition to their financial disclosure statements? Like, how do we get the research to move forward, because I think a lot of what you’ve already highlighted is that people need to be more aware and attuned to these issues, and maybe forcing them to write these things down is a step in that direction? I don’t know if it is, but I’m just wondering what are the mechanisms that the academic, the research communities can put in place to force people to take these steps.
RB: This is another great question. You’re almost dumping me today, because these are not questions that I typically think through, but I’ll tell you…
JS: And I totally like, I sent you three questions and we’re not even, like, even talking about the things I wrote down.
RB: I love it, I mean, these are important topics. I’m so glad you’re asking these really rich questions. My first impression is kind of absolutely not, like, I would hate it as a writer to have to write a lived experience statement, and I would hate it because already, and I even shared this before when we were talking about how white supremacy has shaped academic publications, but one way it does that is that there is part of like how white supremacy affects society and this assumption that black folks are inferior, where, if black folks, in particular, and I use black folks as an example, because I identify as black, is that for black folks to ask for something, for you to try to be a part of something that you then have to be vulnerable, you then have to open up something about your private life and display to other people’s the way that you’ve been harmed and injured personally by racism, even if your research is about a different topic or a different population. And even if it’s about folks that are just like you, I mean, I just think it reinforces this notion of subservience that is really a problem. And it’s something that I’ve honestly grappled with in my own writing, when I talked about how I always start with a narrative, I have been challenging myself to not shape those narratives around a white racial framing, which is to not offer a narrative that has shock and awe about violence against black bodies. Although I want people to pay attention to the violence that has happened against black bodies, that also kind of works in this perverse kind of paradoxical way where the more that you present that violence about black bodies, people then become – it’s almost like voyeurism for people. We become obsessed with looking at black people suffering instead of other acknowledgments of the fullness of black humanity.
And so, I think, trying to write outside of the white racial frame means we also don’t want to ensnare authors inside that racial frame when they present their work to us, by telling us their suffering before we can accept that they have the expertise needed to write on this topic. I think the ways that reviewers and editors and other important people in the journal are making process, the ways that they can determine whether an author is up to the task is through that author’s methods and through the analysis that that author offers. If they don’t define how they’re using race, if they don’t name racism and identify the mechanisms by which it works, or if they don’t use methods that actually interrogate racism as a cause of racial health inequities, then they’re not ready to publish on racial health inequities. Like, how many more people are just going to try to make entire careers off of describing racial health inequities? We know it exists. We’ve known it’s existed for centuries. That is no longer novel. What would be novel at this point is for people to be required to actually help us understand how those inequities came to exist by testing different hypotheses that center racism and white supremacy and power relations and colonialism and indigenous dispossession, that actually center historically contingent processes that have shifted resources and shifted power in our country that then results in different surgical outcomes or different infant mortality outcomes. That would be incredibly sophisticated work that journals should be privileging and preferencing.
JS: Right. I want to round this out by maybe turning back towards the core of this podcast, which is on data and data visualization, and this conversation has been amazing, but I wanted to turn it back a little bit because you just mentioned researchers in their methods and in their models and in their experimental design, and I’m curious about how you think researchers should approach and think about the data that they use. And again, I come from an economics background, where it’s often the case where I go to the Census Bureau and download the data, so I’m not collecting my own data. But I’m curious about how, specifically in your field, how you think researchers and authors and whomever should approach the careful consideration of the white supremacy structure in our data infrastructure.
RB: Gosh, what a huge question, I mean, maybe I should [inaudible 00:29:36]
JS: I thought I gave you an easy question to end it.
RB: I know. [inaudible 00:29:40]. I think, first, maybe I should have preferenced whole discussion by saying the type of scholar that I am. So I am not a primary researcher, like, I’m not an epidemiologist, I don’t work at a lab bench, I make arguments towards theory about the relationships between these different structural kind of factors and health outcomes. So I say that because I will offer an opinion here, but it is certainly just an opinion, and I know there are researchers who can cite actual statistical methods that you can be mindful of as well, and I welcome their input here. I think, from my vantage point, when I think about kind of how white supremacy shapes our data infrastructure, I think about the ways, kind of the passive ways that our healthcare system now contributes to this growing data surveillance apparatus in our country. And what I mean by that is now when you come to the doctor, everything that goes into your electronic medical record is essentially queryable, like, another doctor or can, or anybody, a researcher can go through an IRB process, get their Institutional Review Board to approve it, and without any kind of additional consents. As long as they kind of do the appropriate privacy checks and deidentify the data, much of your own information can be used to any end, to ends you have no idea about, to ends you may object to or that maybe you like, but that you’re not actively a participant in determining. I think that has a lot of problems to it, one, that we’re just collecting so much information about people that people have no idea we know about them; two, that then we share that information, sometimes across other government agencies that might have real tangible impacts in people’s lives, like affecting their immigration status as the last administration threatened to do through public charge; or affecting their basic freedoms as sometimes happens when law enforcement becomes aware of, for example, pregnant or gestating persons urine drug screen; there are ways in which the information that we collect in our healthcare infrastructure can actually be used to hurt other people.
And right now, I think we’re at a time where we’re saying, the more we know about people, the better, like, let’s just collect more information and more data and then make decisions only based on data. And then we’ll call those evidence based, and we’ll say that’s the highest standard for making clinical decisions, and all the while we’re ignoring the fact that, gosh, we’re really creating a pretty invasive infrastructure that can be used and has already been used to harm already marginalized groups. Like, should we ask more questions about where the data that we use comes from, and the people that the data is developed from, the ways that we are all kind of abstracted into data points, should we ask more questions about how much power that individual and all of us should have over that level of extraction? None of us are just a simple randomization of our…
JS: Yeah, one or zero, yeah.
RB: Yeah, exactly. So well said, none of us are a one or a zero, we are so much more than that. And that’s how we’re making decisions about humans right now, but I just think it can be used to reinforce racial subjugation. And in that way, I think part of our data gathering infrastructure and the data surveillance infrastructure that healthcare is a part of can reinforce white supremacy in kind of scary ways.
JS: Yeah, absolutely. Well, I think we have strayed far enough from our talking points that we were going to talk about to, what was just a fascinating conversation. Rhea, thanks so much for coming on the show. It’s been really great chatting with you.
RB: Thank you so much for having me. I hope, I mean, these are not what I knew that we were going to talk about at all. But these are really interesting, these are questions that I’m also going to sit with, and I’ll just say that to other people, like, I sit with these things too. Please don’t think that I know all of the answers. If anything, I’m just incredibly curious about the answers. And as I come to understand things, I share them, but I am also on a learning journey to do these exact same things better as well.
JS: Yeah, well, maybe we’ll talk for a couple more minutes. But it’s interesting because the data visualization field, there’s a lot of power behind creating a visual that people will see and be attracted to as things fly by on their Twitter feed or in reports. And so, it’s a very powerful place to be working, and people in this field also have expertise and knowledge in how to work with data and how to communicate. And so, personally, for me, I think the data visualization field needs to be approaching a lot of the topics that you’ve written about and talked about today, in a similar way, because by ignoring and not mentioning race and racism in our work, we are failing to oppose these forces that need to be opposed, especially in what we’ve seen over the last several years.
RB: A million percent, I mean, even the question – I think one of the questions maybe that sits at the core of data visualization, and I say this as somebody who does not work on data visualization at all, but to me, one of the questions that sits at the core of data visualization is like, how do you capture data in an image for folks. And to me, that’s a question about interpretation, like, how do you turn that into something else that we can also accept as telling us a central truth or giving you the gist of the story. And I think when you talk about that interpretive move from one form of data to a different way of displaying that form of data, I think it also opens up a question and a conversation about, like, how we think about the uses of data in general, and are there other ways and other types of information that we could preference to also visualize, like, how can we visualize people’s narratives, how can we visualize oral traditions, how can we visualize things that aren’t based on massive datasets that we now prioritize as the highest standard of data, are there ways to honor the truth that individuals hold or that groups have held the wisdom that certain traditions have held that don’t come through the forms of data that often get visualized; and are there ways to then visualize those stories too, so that they’re also honored through the ways that we consume information right now on our cell phones, on Twitter, on social media and things like that.
JS: Yeah, absolutely. Okay, now we can close up. So thank you again for coming on the show, it’s been great chatting with you.
RB: Oh yeah, of course, thanks Jon.
And thanks to everyone for tuning in to this week’s episode of the show. I hope you enjoyed it. I hope you learned something. And I hope you will take a racial equitable awareness and lens to your own work, whether it be research, whether it be the next graph or chart that you create, whatever it is, I hope you take that perspective. And I hope you’ll take a look at some of Rhea’s writing, which I think is just incredible and really interesting, as we think about creating a better world. So until next time, this has been the PolicyViz podcast. Thanks so much for listening.
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