1 00:00:04,510 --> 00:00:10,030 Welcome to this special summer episode of Translating COVID 19. 2 00:00:10,030 --> 00:00:16,380 I am maternally allow me research fellow at the Queens College University of Oxford. 3 00:00:16,380 --> 00:00:27,900 Today, I am thrilled to introduce a wonderful guest, Kirsten Oster Zeglaitis, Louise Fox, professor of English at Rice University in Houston, Texas. 4 00:00:27,900 --> 00:00:32,430 Welcome Kirsten, and thank you for being here. Thank you. 5 00:00:32,430 --> 00:00:40,650 I'm delighted to be here. Kirsten is a media scholar, health researcher and technology analyst, 6 00:00:40,650 --> 00:00:48,330 as well as the founder and director of the Rice Medical Humanities Programme and the Medical Futures Lab. 7 00:00:48,330 --> 00:00:58,050 Kirsten is the author of numerous publications, including two outstanding books Medical Visions Producing the Patient through film, 8 00:00:58,050 --> 00:01:03,990 television and Imaging Technologies and Cinematic Prophylaxis. 9 00:01:03,990 --> 00:01:10,230 Globalisation and contagion in the discourse world has at the moment. 10 00:01:10,230 --> 00:01:20,580 Kirsten He's also working on a third book project entitled Quantified, hence learning from patient stories in the age of Big Data. 11 00:01:20,580 --> 00:01:30,480 I am incredibly fascinated and deeply inspired by Kirsten's ability to translate figures and data into meaningful stories, 12 00:01:30,480 --> 00:01:35,430 and I really could not see how not to talk to you today. 13 00:01:35,430 --> 00:01:42,840 So in this brief conversation, I would like to touch upon some of the paradoxes that you have explored in your volume. 14 00:01:42,840 --> 00:01:49,590 Cinematic Prophylaxis published by University Press in 2005. 15 00:01:49,590 --> 00:01:56,130 This book examines images of contagion through the lens of 20th-century film history. 16 00:01:56,130 --> 00:02:02,970 It charts, and I quote the changes and the alarming continuities in popular understandings 17 00:02:02,970 --> 00:02:08,400 of the connexion between pathologize bodies and the global spread of disease, 18 00:02:08,400 --> 00:02:17,390 unquote. Does marking a turning point in the fields of visual culture, public health and medical humanities alike? 19 00:02:17,390 --> 00:02:21,620 So if I could choose a word to describe the ambitious scope of this volume, 20 00:02:21,620 --> 00:02:29,360 I would probably pick the adjective visionary as one that does justice to the book's historical death, 21 00:02:29,360 --> 00:02:33,620 prophetic undertones and theoretical achievements. 22 00:02:33,620 --> 00:02:44,030 So now, given the invisible nature of bacteria and viruses, the visual cinematic lens that constitutes a paradox in its own right. 23 00:02:44,030 --> 00:02:48,260 Could you tell us a bit more about the chosen topic and methodology? 24 00:02:48,260 --> 00:02:59,300 And to what extent do you think is visual culture and not to medium to representative one prefers to translate the invisibility of contagion? 25 00:02:59,300 --> 00:03:04,670 Sure. And thank you so much for that lovely introduction. That was very nice. 26 00:03:04,670 --> 00:03:10,410 The book came about as a result of a couple of key influences. 27 00:03:10,410 --> 00:03:20,810 So before I started grad school, I had taken a couple of years off between finishing undergrad and starting. 28 00:03:20,810 --> 00:03:27,800 And during one of those years I worked as a research assistant in a Department of Public Health, 29 00:03:27,800 --> 00:03:36,620 and there I met a bunch of epidemiologists and I was really fascinated by the way they were. 30 00:03:36,620 --> 00:03:43,580 They were really storytellers, like when you started talking with them, they didn't throw out lots of numbers at you. 31 00:03:43,580 --> 00:03:55,460 They told stories of how they essentially kind of traced pathways backwards in time and space to figure out the origins of a particular phenomenon. 32 00:03:55,460 --> 00:04:00,560 Usually, you know, either a disease outbreak or maybe the source of a chronic disease or something, 33 00:04:00,560 --> 00:04:04,970 and then they would kind of walk you through how it evolved over time. 34 00:04:04,970 --> 00:04:10,370 So it became clear to me that they they were working with data and stories in a very integrated way, 35 00:04:10,370 --> 00:04:16,620 even though we don't really talk about or they don't really talk about what they do in terms of narrative per se. 36 00:04:16,620 --> 00:04:27,380 But from my perspective, that was clear. But this was also in the early 90s when HIV aids was a really huge global concern. 37 00:04:27,380 --> 00:04:38,300 People were talking about it all the time and but I was planning on going to grad school to study cinema and media, and I loved watching old movies. 38 00:04:38,300 --> 00:04:43,850 And I remember seeing the Andromeda Strain, which the original movie. 39 00:04:43,850 --> 00:04:52,850 It's been remade into TV shows and other movies, but the original version, which was made in the 70s watching it at that moment, 40 00:04:52,850 --> 00:05:01,100 it seemed like it was about AIDS, but it obviously wasn't because it was made decades before the AIDS pandemic, 41 00:05:01,100 --> 00:05:08,390 and this kind of led me on this path where I started wondering how is it that we have 42 00:05:08,390 --> 00:05:15,260 the same kinds of representational techniques for different kinds of disease outbreaks? 43 00:05:15,260 --> 00:05:20,780 And what does that mean about the role of representation in the way that we think about disease? 44 00:05:20,780 --> 00:05:28,430 So this this kind of led me into the research that became the book cinematic prophylaxis. 45 00:05:28,430 --> 00:05:38,990 And one of the things I started doing, I became very curious as to whether representations that were made by people in the health sciences, 46 00:05:38,990 --> 00:05:41,390 like in public health or in medicine, 47 00:05:41,390 --> 00:05:50,210 whether they also had any commonalities or whether this was maybe just a Hollywood thing, if it was just a Hollywood thing, I might have imagined. 48 00:05:50,210 --> 00:05:56,300 Well, genres depend on repetition rate with slight variations over time, et cetera. 49 00:05:56,300 --> 00:06:00,410 But then I started wondering, Well, is this genre, you know, just across domains? 50 00:06:00,410 --> 00:06:02,930 Is it also perhaps in public health? 51 00:06:02,930 --> 00:06:11,330 And I started doing research on health films to see how they told stories and the kinds of things that they represented. 52 00:06:11,330 --> 00:06:17,870 And the thing that I started noticing that made it really clear to me the role 53 00:06:17,870 --> 00:06:24,920 the unique role of visual media and visual culture was that there was this. 54 00:06:24,920 --> 00:06:30,830 It really came through in films about contagion, because what you started seeing, 55 00:06:30,830 --> 00:06:40,190 what I started seeing was that even in films going back to the 1920s, the filmmakers, which sometimes included the U.S. Public Health Service, 56 00:06:40,190 --> 00:06:50,300 were trying to teach people to imagine that they could see invisible contagions with their naked eyes, even though of course they couldn't, 57 00:06:50,300 --> 00:07:01,130 so that they could kind of internalise the places or people or actions that could be the source of contagion. 58 00:07:01,130 --> 00:07:08,030 And it was very clear from even way back then that this was kind of a central preoccupation. 59 00:07:08,030 --> 00:07:11,840 You have to. And this is a problem. Of course, this with us right now. 60 00:07:11,840 --> 00:07:22,410 If only we could see. Viruses with our naked eye would be very easy to know what was a dangerous place and what was not 61 00:07:22,410 --> 00:07:29,400 right and when we needed to take extra precautions and when we didn't and all these sorts of things. 62 00:07:29,400 --> 00:07:41,910 So the thing is cinema, you know, moving images, I should say more generally has this ability through special effects to show us things, you know, 63 00:07:41,910 --> 00:07:46,770 whether it's like cartoons, animations or whether it's more elaborate special effects, 64 00:07:46,770 --> 00:07:50,070 which over time became computer generated and that kind of thing. 65 00:07:50,070 --> 00:07:58,530 They can show us things that look like we can actually see them with our eyes because on the screen we can. 66 00:07:58,530 --> 00:08:04,080 And that then allows us to imagine that we can see those things in the world. 67 00:08:04,080 --> 00:08:12,510 So there's something very particular there, and it also really requires motion like movement through space and time. 68 00:08:12,510 --> 00:08:18,990 Right. Because contagion is not a static thing, it only occurs in space and time. 69 00:08:18,990 --> 00:08:28,320 So you put those things together. The moving image occurs through space and time and can visualise things that we can't see with our naked eye, 70 00:08:28,320 --> 00:08:35,160 including blowing things up or speeding things up or slowing things down and all of those kinds of things. 71 00:08:35,160 --> 00:08:39,510 That makes it really a privileged medium that you can't. 72 00:08:39,510 --> 00:08:51,240 You can describe that in words, but you make the kind of to make the invisible seem real in a material sense. 73 00:08:51,240 --> 00:08:58,230 You need a kind of visual form that will allow you to manifest in that way. 74 00:08:58,230 --> 00:09:02,310 Yes. Thank you so much, Kristen. When I was, you were talking. 75 00:09:02,310 --> 00:09:14,260 I was particularly struck by the idea of the moving image as something that is transferred and happens across space and time, 76 00:09:14,260 --> 00:09:20,550 and it is a peculiarity that is inherent to translation as well. 77 00:09:20,550 --> 00:09:30,090 Mm-Hmm. And I was wondering, to what extent can we think of the process of visualisation as a process of translation? 78 00:09:30,090 --> 00:09:43,020 Or are we going too far in allowing translation, the possibility of translation, you know, to to call the two too many meanings of it. 79 00:09:43,020 --> 00:09:53,280 Would you think about it? Oh, I think the translation is a perfect term for that, especially when we're talking about, um, 80 00:09:53,280 --> 00:10:04,830 about creating visualisations of something that has a status in the world of quote unquote objective fact. 81 00:10:04,830 --> 00:10:15,630 Right? So when you think about, um, public health communications, for example, they are supposed to be, 82 00:10:15,630 --> 00:10:20,940 you know, from the point of view of public health experts, science based. 83 00:10:20,940 --> 00:10:28,170 OK. And so, you know, we can talk about the extent to which the discourse of objectivity is itself constructed. 84 00:10:28,170 --> 00:10:33,030 But nonetheless, the idea is that there is a fact. 85 00:10:33,030 --> 00:10:37,140 There's a scientific fact in the world that has been proven, 86 00:10:37,140 --> 00:10:44,970 or at least a hypothesis that is pretty strong that needs to be then communicated to the general public. 87 00:10:44,970 --> 00:10:52,620 And this is widely recognised in science communication as a challenge because scientists communicate in a language 88 00:10:52,620 --> 00:11:00,570 amongst themselves that's very different from the overall mode of discourse in in public or in popular culture. 89 00:11:00,570 --> 00:11:15,090 And so the question there always is, OK, how do you translate complex information that has many nuances to it and that has many caveats, 90 00:11:15,090 --> 00:11:26,780 even perhaps into a form that the general public can not only understand but can remember and can act on? 91 00:11:26,780 --> 00:11:35,870 So for all of these things, there's there's been a lot of research about the way that we. 92 00:11:35,870 --> 00:11:47,050 Need to think about the the visual dimensions and the narrative dimensions of this kind of work because. 93 00:11:47,050 --> 00:11:55,720 We know, though, this hasn't fully been embraced worldwide, I would say, and by all communicators. 94 00:11:55,720 --> 00:12:04,150 But researchers know that having a scientist stand up and present a lecture with all of the relevant 95 00:12:04,150 --> 00:12:10,240 data to the general public is not a good way to communicate information to the general public, 96 00:12:10,240 --> 00:12:16,780 right? We also know there's really interesting research out there about how much more effective 97 00:12:16,780 --> 00:12:24,310 fiction can be than non-fiction in communicating scientific information health information. 98 00:12:24,310 --> 00:12:31,420 Some research has even looked at the role of fictional characters on popular television shows, for example, like Grey's Anatomy, 99 00:12:31,420 --> 00:12:40,930 those kinds of shows, and as well as soap operas and that sort of thing because viewers feel that they already know and trust those figures. 100 00:12:40,930 --> 00:12:51,790 And then they receive the information that is presented as part of a narrative rather than as a set of items that have to be memorised in some way. 101 00:12:51,790 --> 00:13:06,550 So this brings in the question of trust and the extent to which forms of representation do or do not reach us in a way that we find convincing. 102 00:13:06,550 --> 00:13:15,400 And to a large extent, that sense of an image being convincing has to do with a sense of trust in it, 103 00:13:15,400 --> 00:13:23,500 but which itself is a very complex and very culturally specific concept that is not at all universal. 104 00:13:23,500 --> 00:13:29,350 So there are many layers to that to to kind of pull apart and dissect. 105 00:13:29,350 --> 00:13:41,410 But the extent to which there's kind of a layering of how information is being presented by whom in what format that all really 106 00:13:41,410 --> 00:13:52,360 plays into the the extent to which we can make good sense of public health or medical communications or representations. 107 00:13:52,360 --> 00:14:01,360 Thank you, Kirsten. Yes. And Hal, you have explained that right now, contagion poses a series of translation problems. 108 00:14:01,360 --> 00:14:08,380 And at the same time, however, it also confronts us with questions of containment and surveillance, 109 00:14:08,380 --> 00:14:18,130 which seem to be at odds with the translational dimension of economics, politics and culture in today's society. 110 00:14:18,130 --> 00:14:25,810 Could you give us some examples, perhaps, of the ways in which modern cinema has negotiated the tension between globalisation 111 00:14:25,810 --> 00:14:31,390 on the one hand and the control of national boundaries on the others? 112 00:14:31,390 --> 00:14:36,520 And what is the connexion, if any, between contagion and conspiracy? 113 00:14:36,520 --> 00:14:43,030 And how is this connexion unfolding in the current geopolitical discourses? 114 00:14:43,030 --> 00:14:47,080 Yes, thank you that this is a really interesting question, 115 00:14:47,080 --> 00:14:57,040 because national boundaries have have been a central preoccupation of contagion media for a very long time. 116 00:14:57,040 --> 00:15:07,180 And the idea that we can that we can construct boundaries, whether it's around a community, 117 00:15:07,180 --> 00:15:15,430 a village, a kingdom or a continent or an island or a nation, 118 00:15:15,430 --> 00:15:28,930 and thereby keep the healthy people in and keep the infected people out, that that is a very old idea that has come through contagion media. 119 00:15:28,930 --> 00:15:39,790 The challenge and I would answer this now more in relation to contagion media rather than contagion cinema, per se. 120 00:15:39,790 --> 00:15:48,040 The the challenge is partly that the ways that we access and share information, of course, 121 00:15:48,040 --> 00:15:53,770 now are completely networked and do not respect national boundaries of any kind, 122 00:15:53,770 --> 00:16:02,440 except in cases where the flow of certain forms of information are blocked by by state powers, for example. 123 00:16:02,440 --> 00:16:14,110 But by and large, the international flow of information and ideas is it defines the ways that we access information and images now. 124 00:16:14,110 --> 00:16:18,070 So that includes cinema as well as everything else. 125 00:16:18,070 --> 00:16:25,270 But but one of the things this means is that when we think about image based media, 126 00:16:25,270 --> 00:16:34,390 actually most people in the world access information through video forms rather than through text. 127 00:16:34,390 --> 00:16:40,450 So that still is a very prominent and prevalent way that information circulates. 128 00:16:40,450 --> 00:16:48,580 But those videos, unlike the public health films of that I wrote about in cinematic prophylaxis, 129 00:16:48,580 --> 00:16:55,480 the videos that people get their information from which could be on YouTube or Facebook or any place, 130 00:16:55,480 --> 00:17:01,630 they're not necessarily vetted by some centralised authority. 131 00:17:01,630 --> 00:17:18,490 They're not necessarily science driven, and they are capable of spreading ideas, including conspiracy theories, 132 00:17:18,490 --> 00:17:26,800 in ways that actually really challenge the kinds of information that previously organisations like 133 00:17:26,800 --> 00:17:32,350 the W.H.O. had conveyed through films like the films I wrote about in Cinematic Prophylaxis. 134 00:17:32,350 --> 00:17:40,990 So in the 50s, the W.H.O. couldn't make a film about a disease outbreak and send it out all over the world, 135 00:17:40,990 --> 00:17:49,240 and there wouldn't be a lot of competing narratives or visualisations that would be the representation. 136 00:17:49,240 --> 00:17:56,320 And that allowed those kinds of representations a kind of authority that they 137 00:17:56,320 --> 00:18:00,520 just don't have anymore because they're competing with all these other videos, 138 00:18:00,520 --> 00:18:04,840 including conspiracy theories. So actually, you know, 139 00:18:04,840 --> 00:18:16,180 I wrote a paper that was published just earlier this summer that I had written a couple of years ago about Zika virus and conspiracy videos. 140 00:18:16,180 --> 00:18:23,980 And it was really interesting to me to reflect on that piece now because as I looked it over, 141 00:18:23,980 --> 00:18:34,570 I thought that I could go through and replace Zika with COVID, and almost the exact same argument would would hold. 142 00:18:34,570 --> 00:18:39,400 And the argument of that paper was that. 143 00:18:39,400 --> 00:18:48,340 One of the reasons that conspiracy theories, especially as conveyed through visual media, through moving images. 144 00:18:48,340 --> 00:19:02,470 One of the reasons that they posed such a challenge now in relation to contagion disease outbreaks is that those films actually exploit 145 00:19:02,470 --> 00:19:13,560 representational techniques that are much more persuasive than the media produced by science driven organisations like the W.H.O., 146 00:19:13,560 --> 00:19:18,610 where other kinds of health, health departments or health ministries around the world. 147 00:19:18,610 --> 00:19:31,100 So. In that paper, I looked at two different videos, which were the most widely circulated on Facebook in a particular month of time, it was, I think, 148 00:19:31,100 --> 00:19:39,080 June of leading up to the the Olympics in in Brazil when Zika virus was really 149 00:19:39,080 --> 00:19:46,970 raging and and the the one video that was considered to be sort of legitimate. 150 00:19:46,970 --> 00:19:56,000 It was a press conference and it went on for an hour and it was unedited and it was just scientists sitting at tables presenting facts. 151 00:19:56,000 --> 00:20:02,510 The other one, which was a conspiracy VIDEO It was, I think, six or eight minutes long. 152 00:20:02,510 --> 00:20:06,440 It had music. It was highly edited. 153 00:20:06,440 --> 00:20:21,140 It had big words in colours with sort of graphics around them and images visual images to complement the argumentation 154 00:20:21,140 --> 00:20:30,860 and the whole thing built an argument step by step that didn't make any sense from a scientific point of view. 155 00:20:30,860 --> 00:20:36,830 But rhetorically was incredibly persuasive and most of all was very emotional. 156 00:20:36,830 --> 00:20:44,480 And I think that here this is where this is a dimension of visual representation and more generally 157 00:20:44,480 --> 00:20:50,990 representation of contagion that is extremely important to consider is the role of emotion. 158 00:20:50,990 --> 00:21:03,140 Because when we think about contagion, it's something that it's very hard to treat rationally. 159 00:21:03,140 --> 00:21:08,990 It's something that by definition feels threatening. 160 00:21:08,990 --> 00:21:14,360 Right, so that's already a type of emotional response on some level. 161 00:21:14,360 --> 00:21:27,230 And so the combination of a contagious disease outbreak and a conspiracy theory, really it really amplifies that reliance on emotion, 162 00:21:27,230 --> 00:21:34,460 emotional argumentation in a way that when you compare that to how an organisation like the W.H.O. or the CDC, 163 00:21:34,460 --> 00:21:41,610 how they communicate it falls completely flat. Yes. 164 00:21:41,610 --> 00:21:51,420 Yes, I totally agree with you, contagion, in a sense, enhances that gap between science and vision and evidence. 165 00:21:51,420 --> 00:21:57,360 And on the other hand, the irrationality of what you cannot see and therefore you cannot know. 166 00:21:57,360 --> 00:22:08,910 So yes, thank you. Thank you so much for the illuminating. These mysterious, in a sense way in which we access information and process them. 167 00:22:08,910 --> 00:22:19,160 Mm-Hmm. Yes, and talking about health data more broadly, since he also touched up on this issue, 168 00:22:19,160 --> 00:22:27,380 and as I said, you are working on a project that deal with this topic. 169 00:22:27,380 --> 00:22:32,840 There is a final paradox I would like to discuss with you and to propose to you. 170 00:22:32,840 --> 00:22:37,730 And the paradox that deals with inherently qualitative cultural. 171 00:22:37,730 --> 00:22:44,810 And then we had the narrative nature of quantitative data about health and disease. 172 00:22:44,810 --> 00:22:49,760 In a sense, we can say we are made not just those cells, but those stories. 173 00:22:49,760 --> 00:23:00,710 So what do you think is that meaningful story that the current infection rate recovered cases and that stores are telling us, 174 00:23:00,710 --> 00:23:09,080 how can we translate the language of statistics into relevant language that can help us articulate, 175 00:23:09,080 --> 00:23:15,870 comprehend and perhaps even overcome the coronavirus crisis? 176 00:23:15,870 --> 00:23:24,390 Yes, this this this is the question that preoccupies me right now more than ever, not only because I'm working on a book about this, 177 00:23:24,390 --> 00:23:33,060 about the relation between data and stories, but also because in looking at the contagion media of the COVID outbreak, 178 00:23:33,060 --> 00:23:42,150 it is so apparent how data driven the visualisations are, 179 00:23:42,150 --> 00:23:50,250 which isn't always the same as how as the sort of policy based responses I've been 180 00:23:50,250 --> 00:23:57,300 very struck in the current outbreak by how popular the COVID dashboards are, 181 00:23:57,300 --> 00:23:59,370 the COVID dashboards in the maps. 182 00:23:59,370 --> 00:24:10,740 And this is partly to do with certain technical affordances of the internet and of other open access software for mapping that are 183 00:24:10,740 --> 00:24:21,810 available now that hadn't really been available to quite the same degree for other large outbreaks around the world in recent years. 184 00:24:21,810 --> 00:24:34,800 So I find it really interesting that there are so many COVID maps and so many data visualisations to the extent that this phrase flatten the curve, 185 00:24:34,800 --> 00:24:44,370 right? It's a it's a ubiquitous phrase which only references a data visualisation like it actually doesn't mean anything else in the world. 186 00:24:44,370 --> 00:24:48,180 That curve is a statistical model. Right. 187 00:24:48,180 --> 00:24:53,490 There is there's no curve out there in the world that we're, you know, that's that's three dimensional that we're going to flatten. 188 00:24:53,490 --> 00:24:55,720 Yeah, we're all talking about flattening the curve. Right. 189 00:24:55,720 --> 00:25:06,150 And and so I'm really struck by the the juxtaposition of that preoccupation on the one hand. 190 00:25:06,150 --> 00:25:10,500 And then on the other hand, and especially in the United States, 191 00:25:10,500 --> 00:25:21,030 the absence of images of the people actually suffering from the disease, especially in hospitals. 192 00:25:21,030 --> 00:25:30,930 And this is partly due to restrictions on who can go in the hospitals, partly for safety, partly for privacy. 193 00:25:30,930 --> 00:25:43,920 But also there have been very few images circulating of the total numbers of deaths and the numbers of disabilities, and even more than that. 194 00:25:43,920 --> 00:25:55,410 I was really. Dismayed by how long it took for people, for the discussion of the racial health disparities, 195 00:25:55,410 --> 00:26:02,160 especially in the U.S., to finally become a really central part of the discussion. 196 00:26:02,160 --> 00:26:10,980 And to me, when you think about this question of what are the stories that the data are telling 197 00:26:10,980 --> 00:26:18,060 us or which stories could we pull out that would make a meaningful difference? 198 00:26:18,060 --> 00:26:32,670 I think that in the U.S., most states were not actually recording racial race and ethnicity data as they were recording infections and deaths. 199 00:26:32,670 --> 00:26:38,430 And once that started to become apparent that in fact, 200 00:26:38,430 --> 00:26:51,420 you could track severity of outbreaks in relation to racial and ethnic lack of access to not just health care, 201 00:26:51,420 --> 00:26:58,740 but also to high paying jobs that would allow them to not be in public so much 202 00:26:58,740 --> 00:27:05,400 and other resources that could help protect these communities from exposures. 203 00:27:05,400 --> 00:27:15,550 It starts to actually tell a story about who is vulnerable and why. 204 00:27:15,550 --> 00:27:26,680 That becomes a bigger story when you start to recognise that, in fact, in this outbreak and in every outbreak, 205 00:27:26,680 --> 00:27:35,840 we, the general public are really only as safe and healthy as the most vulnerable amongst us. 206 00:27:35,840 --> 00:27:46,530 So. The story becomes different when you start to see that there are certain parts of the curve right that needs to 207 00:27:46,530 --> 00:27:58,680 be flattened that are invisible by design at certain times and then hyper visible also by design at other times. 208 00:27:58,680 --> 00:28:14,570 So what I mean is that the extent to which racial communities, racialized communities were suffering from COVID was not evident early on. 209 00:28:14,570 --> 00:28:17,660 And as it became evident then, 210 00:28:17,660 --> 00:28:35,690 that narrative was politicised in such a way that those communities were from the point of view of certain politicians blamed for their own illness. 211 00:28:35,690 --> 00:28:44,870 Which brings us back to a long history of racialized contagion, which I which I talk about in cinematic prophylaxis. 212 00:28:44,870 --> 00:28:51,770 And there are there are some different features to the way that that has played out in COVID. 213 00:28:51,770 --> 00:28:59,180 But I think that one of the things that we're seeing now is that there's kind of a growing 214 00:28:59,180 --> 00:29:09,830 recognition that in order to truly establish policies that will help us get beyond this outbreak, 215 00:29:09,830 --> 00:29:21,560 we have to actually give respect and care to the communities that are usually not respected and cared for. 216 00:29:21,560 --> 00:29:25,130 Otherwise, this will never end. This will never end. 217 00:29:25,130 --> 00:29:34,490 So that really then it kind of flips a certain element of contagion media that has been with us for a very long time, 218 00:29:34,490 --> 00:29:45,200 which has tended to treat racialized bodies as these external others that threaten the nation and that are carriers of disease. 219 00:29:45,200 --> 00:29:52,040 And that should be kept out to keep the internal, pure and clean and healthy. 220 00:29:52,040 --> 00:29:59,480 That's like a very old rhetoric of disease and contagion that has been visualised in many public health films. 221 00:29:59,480 --> 00:30:04,190 And and also was part of this in in a different kind of racialisation, 222 00:30:04,190 --> 00:30:13,010 which was xenophobia in in relation to people from China, people from Asian countries in general. 223 00:30:13,010 --> 00:30:16,430 So that's another kind of piece of this whole story. 224 00:30:16,430 --> 00:30:22,820 But I think that in the current moment, you know, looking at this and again, I'm talking about the U.S. situation, 225 00:30:22,820 --> 00:30:31,250 largely because it this has certainly played out differently in different parts of the world. 226 00:30:31,250 --> 00:30:41,690 So I think that in the case of the United States telling the stories that actually are hidden by the statistics, 227 00:30:41,690 --> 00:30:52,220 specifically the questions of who are the most vulnerable and why it sheds a light on society and what is valued in that society. 228 00:30:52,220 --> 00:31:07,010 But then. Gives us some, some possible ways to respond to the pandemic, which force social acknowledgement of things that are usually hidden. 229 00:31:07,010 --> 00:31:14,450 So I think here too, you know, the the framing of kind of visibility and and invisibility and the extent to 230 00:31:14,450 --> 00:31:21,650 which translation of different forms can illuminate things that you can't see. 231 00:31:21,650 --> 00:31:26,390 So the statistics don't tell us the stories of who suffers and why. 232 00:31:26,390 --> 00:31:33,020 But really digging into them and seeing who is actually suffering and what 233 00:31:33,020 --> 00:31:40,550 and why they are in that position in the first place shows us a path forward. 234 00:31:40,550 --> 00:31:46,430 Whether or not there is a social and political will to take it is a different question. 235 00:31:46,430 --> 00:31:54,800 But I think that's one of the things that telling the stories that are embedded in the data can do for us. 236 00:31:54,800 --> 00:32:03,020 But it's also one of the things that the preoccupation with data visualisations hides, because that doesn't put a face on it, 237 00:32:03,020 --> 00:32:15,610 and it doesn't show us the kind of disproportionate pain and suffering that has existed across our society as a whole. 238 00:32:15,610 --> 00:32:26,650 Yes. Thank you, Kirsten, because this reflection really sheds light on doing a sense of the cultural dimension of science because in a sense, 239 00:32:26,650 --> 00:32:35,200 figures in that do not exist in a vacuum. They're always interpreted, created and presented. 240 00:32:35,200 --> 00:32:44,890 Yes, and those in a sense also illuminates the core of translation as an entity, a concept, 241 00:32:44,890 --> 00:32:56,170 a reality that lie lies in between the transfers in space and time questions of trust, 242 00:32:56,170 --> 00:33:07,600 but also the attitude we have towards otherness and foreignness and what and who cannot be seen. 243 00:33:07,600 --> 00:33:13,810 So thank you so much for your tremendous contribution to this series. 244 00:33:13,810 --> 00:33:20,140 And thank you for illuminating some of the paradoxes in which we are living today 245 00:33:20,140 --> 00:33:27,700 and for showing us ways of visualising the invisible bio cultural pass or contagion. 246 00:33:27,700 --> 00:33:34,450 And as always, thank you everyone for listening. Thank you so much, it's been my pleasure. 247 00:33:34,450 --> 00:33:36,896 Thank you.