 Let's get ready for the first main session of this workshop. I am so excited of introducing our keynote speaker. So our keynote speaker today is Jess Wade. She's a physicist at Bay Zed Imperial College London. And more specifically, she works on material science. She does a lot of very cool stuff. And actually Jess is also very active on promoting gender equality in STEM, science, technology, engineering, and mathematics, and especially through Wikipedia. Jess has written as of today almost 1,000 biographies of women scientists. And thanks to her engagement, Jess has won a number of awards of all sorts of institutions from scientific institutions to the honorable mention for the best Wikipedia of the year in 2018, Natus Moore, most influential people in science. And she was awarded a British... I'm sorry, stop now. Sorry, come on, come on. You're joking, and then stop you from joking, can't I? So, yes. Yes, you can, you can. But just to tell you how amazing you are. And her, so, oops, sorry. This is, okay. Sorry, so basically today she's gonna tell us a bit about her research, her work in promoting gender equality and also how we can all help to promote gender equality across in science. And so, Jess, over to you. Sorry for the long list of awards, but it's just really amazing. It's too embarrassing. It's like my mom. Okay, I'm gonna start. I cannot... Okay, you've got to stop sharing now, as soon as she's telling me off. All right, so also everyone, apologies, because I made this quite quickly because everything's changing so rapidly. So let's go play from start. Does that have it on full screen forever? Yeah, okay, so I'm gonna tell you a little bit about the research that I do. What I think Wikipedia is really important now, particularly now, and then the work that I've been doing on Wikipedia and how I think that we can work together. If anything's unclear, you can find me on Twitter or send me an email. I will try and speak slowly, but accidentally, I sometimes speak quite fast when I get excited. So if I'm doing that, you can just start shaking or shouting or ping me or send something to tell me to slow down. So this is where I work. Well, not at the moment, obviously, but it's right in the middle of London. And I work in the physics department, which is kind of in the top left of this corner. And this is Imperial College London. And it's a pretty sensational place to work, which you can see from this image around us. We have kind of Hyde Park. We have the Science Museum. We have the Natural History Museum. We have the Victoria and Albert Museum. And then over in the physics department, as Miriam kindly mentioned in the introduction, I'm looking at new materials for electronic devices. And particularly these materials are carbon-based materials. They're called organic semiconductors. We can dissolve them in solvents and make these beautiful semiconducting inks and then print them and create really, really beautiful crystal structures. And what we can do, something's coming up in more. Cool, yeah, let's see. Oh yeah, sorry. I'm gonna stop that from distracting me. What's amazing about these materials is that they have the electronic properties of things like silicon. So they're semiconductors, but the processing properties of carbon. So they're really, really easy to work with. We can dissolve them, we can print them. We can print them onto huge sheets and we can create kind of flexible devices. What we're particularly interested about in my research group is a type of a branch of semiconductors, a particular area of them, which are chiral. And chiralities are really fascinating topic in loads and loads of different aspects of science. Chiral objects exist as non-superimposable mirror images of one another. So you have a left-handed and a right-handed version, just like your hands, just like shells, just like some subatomic particles, but particularly I'm interested in molecular structures that can be left and right-handed. And what we're finding out is how we can work with those in electronic devices. So how we can use those to manipulate the properties of light, what a chiral molecule will do when it interacts with light or what kind of light it would emit, how they behave in magnetic fields is also appearing to be super interesting. And then what we're looking at increasingly now is how they can be used to manipulate electron spin. So not only the spin of a photon, but also the spin of an electron. And there's a whole range of different things that are really, really exciting when you start to think about chirality in research. And if anyone wants to talk about that offline after this workshop, I'm really happy to do so. So now why I think Wikipedia is really important in the pandemic and why I think it's so important that we're all here and here working together. I think as a physicist, I've been feeling completely useless since probably mid-February, mid-March. My whole family are medical doctors. They're all doing really, really important things. My brother's a junior doctor actually at a really busy hospital in London. On Sunday, my dad turned 70 and we went over to have a socially distanced birthday. My brother to be able to say happy birthday to him, which I think is so cute. But I've just been feeling like there's not a huge amount that we can do. But actually, I think Wikipedia is probably more important than ever before during this pandemic. There are so many ways that researchers like you, students like you, academics can contribute to making the world a better place through the internet and by staying at home. And I thought I'd just start on that because I think it's really, really crucial. I don't know if you all saw it, but if you didn't, you should check this out. It was a beautiful article that was in Wired actually in kind of early February about how Wikipedia is the last best place on the internet. And I really liked this quotation saying it was built on love. And I think even more than that, the kind of data science, the research that you guys are doing, the analysis that we get from Wikipedia is something that's so fueled by kind of very personal questions and interests and interactions. It's something that's really, really incredible for you as a researcher and also for the general public to see. I urge you to all go and read this article. I think it's really, really beautiful. But I think Wikipedia is important in a whole bunch of different ways. One is on how we interact with the general public through this ongoing pandemic. One is particularly on education. We spoke about it a little bit in my breakout room before, but lots of us work in universities and the whole notion of teaching and learning has changed, but not only in universities has it changed. Also for, if any of you have parents or friends with small children, everyone's having to homeschool now. And that's very, very different than learning in person and the resources are very, very different. I think that the pandemic too gives a whole bunch of opportunities for academics who are thinking about contributing to Wikipedia. Probably lots of the students who are here are thinking lots of online classes have changed. For me, as a physicist, we can't get into our research labs now so we can't do all of that aspect of our science. So how can we keep contributing? And I put this bullet point on kind of hastily when I was thinking about it, but I think for people coming back and looking at content that was generated during this time, you know, when people come to research the pandemic later on, when historians come to look back, Wikipedia is gonna be a really important place for them to go through for information. So it's such a cool time to be starting off and thinking about this, thinking about working on Wikipedia and the project. There's actually been quite a few articles about how important Wikipedia is already. And again, I'd encourage you to go and read these, particularly on kind of tackling misinformation and the way that Wikipedia has been incredible at pulling in medical researchers and epidemiologists and health researchers. And I'm happy to send you all of these slides or all of these links to the articles later on so you don't have to look them up. But I was thinking about particular ways. So one I think thinking about the spread of misinformation is really, really important. And particularly because Wikipedia is non-partisan. And what we're seeing now in the UK and the US all over the world is the kind of huge polarization and politicization of pandemic-related news content and stories. And I think something about Wikipedia that is particularly incredible is that everyone comes to it. No matter where you are, no matter what political party you support or subscribe to, everyone goes to Wikipedia for that information. So I think that is incredibly important, keeping it neutral, but also recognizing that when you write or edit or capture data from Wikipedia, you're capturing it based on everyone. And that's really, really different to any other platform that I can think about. It's not an echo chamber basically. Something that I think is really interesting about this pandemic and I've been reading a lot about it as I write more for Wikipedia about researchers who work on coronavirus related science is that this is the first real pandemic when people have pre-printed more than ever before when people have put their academic papers up before they've gone out for peer review. And as a result of that, journalists are publishing news articles based on pre-printed science and that's a really, really interesting difference for the public in how they interpret newspaper articles about science because usually it's gone through a rigorous peer review process before it gets out into the hands of the public. But also it's completely changing how science is done because people are working together so much faster than ever before. And I think Wikipedia has a role in kind of synthesizing that and explaining that. Also you can create and edit the pages about coronavirus related topics or researchers. There was an article in, I think this is obviously the New York Times from the way that the headline is written a couple of weeks ago that looked at all of the kind of top researchers working on coronavirus research and unsurprisingly, well actually surprisingly given that a number of women that I found out about all of the experts they quoted were men. So if you have any capacity to be able to write about women researchers who are working on coronavirus related topics right now it's a really, really great time because everyone is looking for these pages. Another thing I think is really crucial is thinking about how we get offline content to school students. This was an article from New York, one from LA and one looking at UK school students. And this is all in the last couple of weeks. So this is all since we've moved all of homeschooling to all of schooling even to online. And it was particularly looking at the demographics of students that aren't engaging with the contents that the content that their schools are putting out. And I think something that we can start to do as Wikipedia as researchers and editors is to start thinking about how we can get more school related content online and accessible offline. I can click through these quite fast but I'll send them all to you. But I think something that you as researchers could come up with is ways that schools can keep using Wikipedia as projects, as research projects as some way that we can think about shifting to online delivery of education. And I've been speaking to a whole bunch of teachers around the UK about how we can probably work more together as people who are passionate about Wikipedia, passionate about open knowledge, and also school students who have a little bit more time on their hands and potentially some capacity to access the internet. Oh, and it can be related to data, you know, a huge number, I like when I do this and my hand kind of vanishes into the London skyline, a huge number of school teachers, particularly trying to integrate more between kind of history and research and also data and computer science. And I think that wiki data and all of the opportunities we have now with a huge amount of data being generated is really phenomenal actually. Particularly as one fifth of the world, if not more than that, this was early April when I got this statisticer now on lockdown. And again, thinking about access to online content. And as I mentioned before, it really emphasised that I think it needs to be representative. I think we need to make sure that we're documenting all of the different scientists from the Northern Hemisphere, from the Global South, from more economically developed and less economically developed countries. The final one I think is for researchers. I don't know if you've all read this blog on Medium. It was by one of the Wikimedia Foundation research team. It's actually really, really beautiful. If you haven't, I'd go and look at it, but it's particularly looking at how Wikipedia has changed in the past couple of months, particularly with knowledge related to the coronavirus and how it's increased. And I think we all have this capacity now to better support our colleagues and our student friends with how we can make use of all of this data, how we can share all this data, how we can pull it all from the internet. You know, Wikipedia is phenomenal, not only because we have this opportunity to speak to so many people, but we can learn so much about what they're interested in and what they're clicking through when they go online. And I think it presents opportunities for people who are interested in finding out how they can engage because they might have a little bit more time. So now I'm gonna particularly think about, I'm gonna kind of try and switch now and talk a little bit about the project that I've been doing before coming back to thinking about things we could do together as research collaboration ideas. So I've been working, as Miriam mentioned in the introduction, on new ways that we can try and think about improving gender balance in science, particularly in physics. So I work in a physics department, I studied physics at university as an undergraduate, I did my PhD in physics, and we've always had a really big under-representation of women, under-representation of women and of people of color. And as with so many countries all over the world, this has been recognized as an issue for 10, 20, 30 years. And we see it at high school, we don't have the right representation of women, we see it when we get to undergraduate level and we see it at postgraduate and then at professor level. And we've tried, all over the world, we've tried various education initiatives to try and improve the representation of women in science. And actually for the US, you can get data on it, they spend about $3 billion a year on education initiatives, about a third of that is towards gender diversity. So they're spending a huge, huge amount of money on initiatives to try and improve the representation or the recognition of women in science. And the most fascinating and frustrating thing is nothing seems to have changed that much. So if you pull up data on kind of statistics of who studied what and when they studied what, the number of women studying physics, the number of women graduating in physics hasn't changed for, you know, since the 1980s, 1990s. And so I've been starting to think for kind of probably the past couple of, you know, three, four, five years since I started doing my PhD about ways that we can actually meaningfully better represent and celebrate women scientists and also create an opportunity for people to learn about these incredible women, these amazing people of color in a context of something that's important to them. And I think that's why Wikipedia has been so phenomenal in that. So it's amazing as a platform because you have people who come on it to read about a particular topic. You have people who come on it because they're interested in, you know, a particular river that's near their house or a particular football team that they support. And then they start clicking through all of the different links and find themselves on this phenomenal woman, man, cousin of color, whatever it is that reminds them very much of them. You know, it's someone who reminds them of their story. It's someone who connects with them. It's a page that they kind of chance upon. You arrive at it sneakily. You don't get put this information right in your face. You're on Wikipedia because you're fascinated and you're interested in something and then you learn about something else. Actually, just like that game we played in the introduction where you shared your favorite fact from Wikipedia, I think that's a really incredible way that you see all of these people are there and that they're just like you. So in 2017, I read this amazing book by a science writer called Angela Saini and it's called Inferior, the True Power of Women in the Science that Shows It. And Angela is, she works in London. She was an engineer and then became a science writer. And in writing this book, she looked at all of these historical science studies that had been set up to try and show that men and women were different. So all of these studies that show, you know, women have different hobbies to men, women are more interested in caring responsibilities and all of these different things and showed how biased all of these science studies were. So how the impact of the scientists who are leading the studies, how they impacted the data they collected in the way that it was interpreted. And she looked kind of throughout history all over the world at these phenomenal women who were kind of standing up and saying, this isn't right, this isn't fair. You know, in the early 1900s, there was a lot of voices in the UK, particularly who were trying to get women not to be able to go to university, to be able to vote, to be able to own property. And there were all of these women standing up. And I think Angela puts together this really, really incredible introduction to how biased science has been and how that's impacted women's status in society. Actually, her book that followed Inferior was called Superior. And it looked at particularly this same concept that related to academic racism. And again, I'm happy to talk to you about those great books later on. But kind of briefly after I read, shortly after I read Inferior, I met a phenomenal woman called Alice White and this is a picture of Alice. And she is a Wikimedian in residence at the Wellcome Collection. And she is a historian of science actually by training. So she has a degree in studying the history of psychiatry. But she particularly taught me about Wikipedia as this incredible platform, as I mentioned before, as a way of communicating with a huge number of people, as a way of teaching people about different topics that are important and you know a lot about, that you're an expert in. And she also taught me just how important it was in schools. And I hadn't really ever thought about it before, but now I've been working on this for the past couple of years. I've been thinking about it all of the time. So Wikipedia is used all of the times in classrooms, you know, whether it's online or offline, people are using Wikipedia when they're learning, you know, it's used in universities, it's used in pub quizzes, it's used all of the time. Something I hadn't realised before everyone started wanting me to talk about Wikipedia with them was how often Wikipedia is used by journalists. And actually I've met a whole bunch of people since doing this project at the BBC and all of that, who go to Wikipedia first, not only to brush up before they start doing a particular topic, not only in their preparation before they go on air, but also to find experts to talk on a particular thing. So actually having representation on Wikipedia impacts what's on the mainstream media, impacts what's on the news, it impacts what gets on, you know, the front page of the Guardian. And I think I hadn't sort of, I hadn't made that connection so like since I started doing this project. Let me see if I can come back. It also impacts science. This is another fascinating research article from a couple of years ago. And again, I encourage you to read it. But it was a professor at MIT who set a Wikipedia assignment to members of his class. And then it was to write particular Wikipedia pages for topics in chemistry. So kind of niche areas of chemistry that didn't have Wikipedia pages. And then tracked how often those topics appeared in scientific literature. So how often they were being written about in peer-reviewed science journals and found that you could assign one in 300 words in these peer-reviewed papers to them appearing in Wikipedia. So it completely changed the way that science was evolving, them having a Wikipedia page. And as I mentioned in the introduction, and Miriam mentioned, I work in this kind of emerging area of new materials. And actually so often in that, I want to know about a particular technique or a particular type of material or kind of a brief history on why people have used a particular experiment. And Wikipedia is certainly the first place you'd go to before you go to a peer-reviewed area of research. So I think actually as science becomes more interdisciplinary, as everyone wants to become an epidemiologist, as all of these things are changing so much, having Wikipedia pages on particular topics is so, so crucial. So not only important in academic learning in the kind of formal school sense, but also in how it's changing our research, you know, as we all become more interdisciplinary, Wikipedia is becoming even more important in those academic circles. And I hadn't really appreciated too how much it informs everything that we don't see. So these kind of ways I think are things that are obvious to us. You know, I go to Wikipedia, I search for a word, the page comes up. But what we don't know is when we ask Syria a question or when we ask Amazon Alexa a question or when we ask our Google Homer question, is that all of the information that these home assistants are getting is also from Wikipedia. So if we have a huge amount of bias content on Wikipedia, if we don't have enough pages about women, about people of color, about people from the global south on Wikipedia, then whenever you ask a question to your Siri, that's going to be biased too. And I think this is something that's much, much more subtle and something that really means we have this kind of responsibility as Wikipedians to make sure that everything on there is neutral and up-to-date and correct. And sometimes you can see it. So if you do a Google image search for famous physicist, this is what comes up. You get a nice wall of old famous physicists, probably many who worked with or at EPFL. But I think that something that we have to remember is that this is because of the content that we've put onto Wikipedia, right? This isn't because Google is biased or the Google image search engine is biased. This is because there aren't enough Wikipedia pages about women physicists who get enough clicks, who get enough people going to that page directed to that traffic, and also because they have an image on the page. So I think what we need to do is work with Wikicommons. We have to work with libraries and archivists to be able to get this content, but also make sure it's on there and linked to appropriately so people can start to see it. So this is old data now and something I think that we could start doing a lot more as a Wikipedia research community is collecting more information on the people who edit. But there's kind of talk that between about 10 and 20% of Wikipedia editors are women. So we know we have a really, really big lap in the representation of women editors. This may have changed now. This is quite old data. And I think something that we could all do is better collect that data and understand it. But we do know that on English-speaking Wikipedia, which is probably, I mean, it is the biggest Wikipedia language, the biggest language Wikipedia. Only 18.3% of Wikipedia biographies are about women. I think what's fascinating is this is very similar to the representation of women on banknotes or the representation of women in statues in the UK. But I think this is really terrible, right? Particularly because we know now how much is informing so many different aspects because we know how it's informing all of our home assistants because we know how it's changing all of the stuff that we hear about in high school and in journalism. If we only have a representation on Wikipedia that's less than a fifth of those biographies are about women, then I think that we should feel pretty badly. So as Miriam said, since I read Inferior, actually since the beginning of 2018, I've been writing these Wikipedia pages every day for women, for people of color, for LGBTQ plus scientists and researchers. I'm nearly a thousand, which is the most exciting thing. Although I was kind of hoping I could celebrate it in a really big way and now I'll just be celebrating it in my house. So it's probably by editing Wikipedia. I'll tell you about a few of them because I think they're really fascinating and then come up with some ways that I think we can be clever and work together and I'll go quickly because I know you have a tight schedule. So this is a phenomenal woman called Gladys West. And I learned about Gladys West in probably 2018 kind of a black history month in America. And she was an American mathematician who started working for the government. So she started working for the US government, particularly on the early programming for GPS. So she was doing all of the kind of early mathematical calculations to get the satellites up for GPS so that we can all use satellite navigation. And when I made this page about Gladys West, there was so little about her. It was kind of one of those beautiful Wikipedia kind of collaborative growth. Everything happened. Everything happened on this page. She had very little information. All I could find was this tiny document that was all redacted, all of this kind of secret government information as you can imagine. And then after I made this page, she was nominated for the BBC Top 100 Women. And again, coming back to the way that data is important because you can track all of the page views. You can see as soon as she gets nominated for BBC 100 Women, the kind of page views go crazy. Everyone starts clicking on Gladys West page to see it. And then she was inducted into the US Air Force Hall of Fame, which means that now we have all of these incredible free images of Gladys West because the US government make all of their images freely available for Wiki Commons, which is just kind of staggering. The other amazing thing is that she's nearly 90 and she's just finished her PhD by distance learning, which is just so cool. So even when you start writing this page about someone and you think, okay, that's it. She's nearly 90. We're gonna keep adding a little bit more as we learn about her. She does so much more, which makes the page grow even more. I just think it's incredible. Another amazing story was this researcher that I'm sure you'll remember, but Katie Bowman who's a computer scientist and physicist who was at, she's now at Caltech and she was at MIT when she did the programming, but she was one of the software developers who put together the code that first created this first direct image of a black hole. And this was one of those amazing stories of Wiki editors worldwide collaborating because there's very little information about Katie Bowman again. I made this page when I got home from work. So it was, I got home at about six. I made the page by the end when I'd finished having dinner. By the time that I finished editing, it had been translated into about 15 languages. Now I think it's in nearly 30 languages, but that night alone, it was viewed over 300,000 times, which is staggering, right? Just everyone was clicking on and learning about this, which I just think is amazing. And she was also in the BBC Top 100 Women. One more, which is just an amazing story. And then I promise, oh no, I have to show you a few more, but I'll be quick. This is Elizabeth Sudmayer. She's just, it's just staggering actually. So Elizabeth Sudmayer studied English in kind of the early 1930s. And she then went off to work for the Central Intelligence Group that became the CIA. So she was one of the early pioneers who set up the CIA in the US. So kind of the security and spying organization. And not only did she do that, but she was really involved with campaigning for women to be better recognized and to be better paid. And this was the time when women weren't doing these kind of jobs, right? So she was there. She was not only doing that job, she was also changing the whole way they supported women. And this one's kind of incredible. She led a whole panel called the Petticoat Panel, which was looking at the gender pay gap in the CIA. Imagine that now. So the amazing thing about this story was, I watched a little video about her on the CIA, which is why I put this webpage up. I'm on a Zoom call with a million people on it, but I'm not supposed to be talking. Okay, got it. And then I got this email from a guy called Michael who said, by the way, I'm Elizabeth Sudmayer's second cousin and I read this page and it says that it's been created by you. So this was about a day after I'd made this page, which was quite staggering. And then after that, we had a whole long conversation. It turns out he makes movies and he wanted to make a movie about Elizabeth Sudmayer and the Wikipedia page made it really great to be able to make this movie about her, which I just think is so cool. So it starts off as something where you just write a page or you put some data up or you put some image on Wiki Commons and then it becomes something that's so, so much more. So Wikipedia is incredible for that. I've also been focusing a lot more recently, as you can imagine, on all of the incredible women who are involved with the coronavirus research efforts, including Kizmekia, who's one of the top researchers that the NIH who's leading vaccine development. This page is also amazing. She was featured on all of their American news channels and also the BBC. And then this got about 45,000 views in about two hours the other day, whenever I was starting to click on. And the amazing thing about these two pages too, Kizmekia is in the US, Sarah Gilbert's in the UK, was both times my dad's come and told me about them and he's like, they already have a Wikipedia page and I've made their Wikipedia page, which is just so fantastic. Alison McGeer is working on looking at aerosols, particularly in how coronavirus might be transferred and translated in aerosols. And then Paula Reed is the incredible American journalist who's really held health government to account on how they respond to coronavirus. So all of these amazing stories are coming out. And I think the incredible thing is to keep those conversations growing and keep growing. I'm gonna go quickly now because I don't wanna take up more of your time. Let me just see what's happened to my... Oh, oh no, too much. So since the beginning of my editing, I've really enjoyed teaching other editors how to take part in Wikipedia projects, how to stay involved. We've had editathons for a whole bunch of different activities. So writing profiles about women scientists, about black and minority ethnic scientists. We've done Wikipedia editathons two years in a row now for LGBTQ plus science day, which happens annually and internationally. And it's just been incredible. I went to Brazil, we did a big Wikipedia editathon in translating pages into Portuguese. And that was just kind of staggering, all of these young people who really, really rely on Wikipedia, you know, much more than their textbooks because they're difficult to get and not up to date. People really use it in places that you could never imagine. And all of these different editathons with learned societies. So really, if you're a student listening and you're thinking about ways that you can get involved with Wikipedia, one way would be through your library, one way would be through your student society or your chapter of a particular learned society, but also work with people. All of these different conferences and professional bodies want something to do like Wikipedia. And it's a really, really great way for you to support them as well as them to support you. I'm not gonna keep talking. I have too many examples. The most amazing thing is the editing Wikipedia costs absolutely no money. So you can engage all of these people all over the world. You can do all of these amazing things with data. You can have a really, really incredibly inspiring time learning and you've not spent anything. Maybe you have to spend a bit of money to get a good enough laptop so it doesn't die every two minutes when you try and write, but you don't have to spend a huge amount. So now finally, I wanted to put one thing just a couple of slides on how I think we can all work together more. There's been some really beautiful examples recently, particularly about how capturing small, not obvious amounts of data has resulted in the public learning so much more. One, that was a very skeptical and vague point that I just made, but I wanna give two examples of it. One was in February last year. This was two US researchers. I don't know if anyone saw it, but again, I'll send you the papers that they looked at. It was two US researchers who set their undergraduates a project of looking in 10,000 academic articles at all of the acknowledgement sections in those articles. And they realized that the same group of four women were being recognized all of the time cited in all of these different acknowledgement section. And they actually had some huge impact on some part of the way that you do kind of computational genetics. So some program that they created was used in a huge amount even to this day is still used. And the papers that they wrote about creating this software have been cited tens of thousands of times, but the women were kind of held within the acknowledgement sections. They weren't properly recognized. And this researcher set, this is an assignment to our students and they started to see the same women's names being coming up again and again and again. And again, I think this is something that from a research perspective you could completely run with. You know, it won't just be in computational genetics that this will be happening. It'll be in lots of different areas. And anyway, it turns out that at least one of these women went on to have an amazing second career, not in genetics, but in educational research. But you kind of see how actually not only writing these pages for Wikipedia, but also doing research to identify who should be written about for Wikipedia is also something that's really, really great to do. Actually, there's a project on at the moment run by the Science History Institute and there's a great article about it on Massive Sciences website. But looking to try and identify these women, these five women researchers who are in this picture of one of the early academics who was involved with diabetes research in the US. And this is again, something where I think data and research and access to archives and libraries would be really, really incredible. So I'm gonna end with a whole page of bullet point suggestions and then take any questions. I think there's a huge amount of information that would be really great to get on editors. So what kind of people are editing where they are, but particularly for new editors. So this is something that I've been thinking about. I mean, I know Wikimedia thinks about it a lot, but we have all of these great editor funds. We have all of these incredibly inspiring opportunities to work with each other. And then sometimes editors don't stay. You know, all of the editor funds I'd run, I'd say 90% of the people who can't show up are women and yet they don't keep editing. So how can we keep them engaging and what interaction are they having on Wikipedia that makes them not wanna stay? And that's something that I think is a community that we should try and find some answers for. Particularly about the content that comes up on Wikipedia. So we can talk about this at length later on, but I think thinking about which pages are more likely to be nominated for deletion. So why pages get deleted? How people talk about pages that should be deleted? What's the differences between pages about women, about people of color? How can we try and understand from that data who's particularly being included or excluded from Wikipedia? Again, looking at who is missing. So what kind of topics are coming up and not available on Wikipedia? And again, to work, you know, librarians are incredibly crucial for this effort. So are these phenomenal Wikimedians in residence, local Wikipedia chapters. All of this I think is really, really important. So I think one area on understanding editors and another area on trying to improve our content. And the final one, I can't even remember what I cut now, but it will make sense. Oh yeah, this one I think is great. It'd be super nice to know how people land on a particular Wikipedia page. So what do they click through before they get to Wikipedia that lets us end up at a page about Gladys West, at a page about Kuzmetia Corbett? How often are they just Googling their name? How often do they start on a page about virology or whatever and then end up there? And also how much time are people spending reading them? I mean, it's so nice when you're training new editors and you can say, this page has been viewed 45,000 times, but also it'd be super nice if you could say, and everyone stays on that page for 20 minutes an hour because it's so fascinating. So I think that would all be really nice data to have. And when I spoke to Miriam yesterday, I was acutely aware I didn't wanna not connect with you and say that there's ways that we can work with each other. So I came up with a whole bunch of different suggestions. So in light of that and having spoken for too long, thank you so much for having me and for clicking in and joining this conversation. And if you have anything, you can send me an email or find me on Twitter. And yeah, and obviously like everyone else around a lot now. So just find me and ask any questions. So thank you. I'll stop sharing now. Thank you so much, Jess. Yeah, I'm clapping. I'm clapping for Jess. So Isaac, if you're around, Isaac, another researcher at the Wikimedia Foundation is handling the Q and A queue. So Isaac, if you're around, I'll let you go through that. Yep. Thanks Miriam. And thanks, Jess. Thanks to Jess, yes. So yeah, just a quick reminder, I'm taking questions from the chat. So if you have more, just add them. The first question comes from Andrew Eels and says there's specific research focus is studying misinformation as it relates to politics and public discourse. And the way we speak about it, misinformation seems to have a connotation of intent to mislead. Would you personally consider journalists publishing unvetted research as misinformation? Or do you think it's more an attempt to disseminate information as rapidly as possible, perhaps overlooking the long range consequences? Without being as probably informed as someone who's spent years studying this area, I definitely think in this situation, it's the latter case. So I don't think it's people deliberately trying to spread misinformation, but I think everyone is talking about this, everyone is thinking about things at the moment related to it. And people wanna have that big scoop as quickly as possible and people wanna get that out so that people will click and link to their newspaper article or whatever. So I think we probably need to take more care over the way that we report scientific research, but that also comes with us as researchers doing a bit more public engagement to talk about the way that scientific research is done and also published. Because if I went, you know, even though I come from a family of medical doctors, if I went to them and spoke about preprints, they'd have no idea what that was. So I think that we need to not only do the part of working with journalists, but also do that part of talking about what we do as scientists. And yeah, to the chat, I will definitely send the slides. I'll send them as soon as I put them on Google Drive. Thank you. The next one, I think this is again coming from kind of the start of your presentation. Hussam-Adin Turkey asks, so there's alt metrics like Wikipedia page views and Google search engine queries are playing a main function in predicting disease outbreaks. This has been known for a while since Zika and Ebola epidemics. Is there any work to use Wikipedia analytics statistics to predict epidemiological evolution of epidemics like COVID-19? I definitely don't think I'm the best person in this discussion to answer that, but I'm sure that there are some really, really big projects that are looking at it in the pages that I've been writing so far for researchers who are working on coronavirus. I'm amazed by how many of them are more the kind of mathematical computational predicting side of epidemiology and public health. And actually some of the most cool projects at the moment looking at how we can better contact trace in hospitals, out of hospitals, how we can understand how these viruses spread. And I think that all of those data science related and related to information that it's capturing from our mobile phones, from the ways that we engage online. So I'm sure that there is a huge amount of research, but I'm definitely not the best person to answer that. Sorry. No worries. Oh, Mayor, you are up next if you'd like to ask your question. I'm just going to intervene. We have, we're a little bit late, that's fine, but maybe let's try to keep another five to seven minutes for a question, because after the workshop. Sure, I mean, everyone I can take questions later on too. You can just send me an email. I realize I spoke for too long and I feel guilty. No, no, no, and it's absolutely fine. We were late earlier than when you started to talk. So that's fine. Just for everyone that's for the interest of time, let's just limit the Q&A to another five to seven minutes. So I'll try to keep my question short, even though that's maybe hard. My question touches to how Wikipedia encodes bias. So how Wikipedia's policies maintain bias in their attempt to kind of keep high editorial standards. I mean, things like notability, because notability on a lot of times will revert to kind of academic standards, or will we create academic standards, especially in professional fields? And I think there is on Wikipedia an overlap between scienceism and the gender bias. So I just want to hear your opinion on encoded bias and encoded bias within Wikipedia's own form of encyclopediasm, for example. Yeah, I mean, I completely agree, and I actually didn't talk about it, but obviously the notability criteria on Wikipedia generally reflect the notability criteria within academia. So the way that we celebrate and think about who's an important professor basically fulfills the Wikipedia notability criteria. So it's who's published a huge amount of news, got a massive grant, all of these different things are significant for whether you get a Wikipedia page. I think the difference is how it gets covered. And women, I often find when I'm writing about them, they'll have the big research grant, they'll have won the big prize, they might be president of a particular society, but actually they don't get coverage outside of their own institution or the professional body. So I think in that sense, the Wikipedia notability criteria are fine, but the way that we talk about these people is completely different. So you saw it in the case of Donna Strickland, the first woman in a long time to win the Nobel Prize for Physics, and she had had a Wikipedia page written about her. It was decided that she didn't fulfill the notability criteria, and the reason for that is because no published, no newspaper site, no journalist had reported any of the research that she had done in a really big way, or written that she was president of the Optical Society of America, so a kind of very big optic society. So I think actually, whilst I think that Wikipedia does make this by, it exaggerates the bias, right? Because if you're not spoken about in the media, you're not on Wikipedia, but if you're not on Wikipedia, you're not spoken about in the media, I think that university press offices and journalists need to do a better job at finding these experts to profile them, to write about their achievements so that then Wikipedia editors can put them on Wikipedia and keep backing that all up, because the hard time I have is finding enough independent sources that confirm all of the claims that these scientists are saying that they can do. So I think that we actually need, Wikipedia has a set of criteria that has to be maintained, and I think that that's important, but actually we need the wider world to start recognizing these people's achievements so that we can document them on Wikipedia. So for now, I honestly think some Wikipedia editors get angry enough already that you're writing about women, let alone proposing you're gonna change the notability criteria to write about more women. So for now, I think that we should focus more on trying to make sure that women and people of color and all of these different marginalized groups are better represented in the news so that we can better cite them on Wikipedia. Sorry, Miriam, that was a very long answer. All right, we've got three more questions. I think we can get through them. First up is Benjamin. So I was just wondering, obviously we want to vase this proportion, but until that occurs, how can we communicate with the media in order to change the way that they behave? So I think that often, and when I've spoken to an analyst about this, they will go to a university or a particular research group for a comment, and some of them are super engaged with the same efforts that we're talking about here. So some of them often try and find a women expert to be able to get her insight so that they can quote a woman. But sometimes the people don't want to be quoted. They say that they're not the real expert. They should go and ask the man who lives next door. You know, there's a big confidence issue, not only in the journalist, but also in the women researcher to make sure that she wants to be commented. So I think we all need to do more as a research community to make sure that people have the confidence to be able to respond to these particular areas and to make sure, and this is very, very niche comment, but you find the right area researcher for a particular comment to give you a really important key. If you're asking a question about something, you want to find exactly the right researcher to be able to answer that. And I think often researchers will answer questions broadly about a field without being a technical expert in it, and we need to get away from that. We need to go towards people, journalists, finding out where these people are and going to ask them to answer a particular question that I realized I didn't. I think that we, as activists, as people in an online space, whether it's on social media, whether it's helping journalists through emails and suggestions like that, do have an opportunity to make recommendations. We have an opportunity to nominate people for awards, to nominate people for fellowships, something that I've been doing a lot since writing these Wikipedia pages is writing a whole bunch more nominations for prizes for people who I realize are incredible and haven't had the recognition that they deserve. And I think if we keep doing that, then they'll get up to having some kind of visibility that means eventually journalists will go to them. But yeah, it takes a lot of nudging and a lot of, you know, if you know anyone who edits a scientific journal or a newspaper, then to just keep bugging them about profiling these people, that's kind of what I've spent two years doing now. So I think I have a whole database of people who are quite open to suggestions, but just keep writing about them and keep talking about them and then eventually other people start listening. Next, Christina asked from the chat, how do you choose the scientist to write about next? Do you know or use automatic methods that help in making the choice? So I, no, nothing as automatic as it should be. I have at the moment me and my friend, Mariam Zaringalam, who's a AAA science policy fellow in DC. We have a whole Google sheet of all the women we know who are working on coronavirus related topics that we keep adding to every day when we wake up and look at Twitter. We just add all the cool women researchers we've seen. So that feels incredibly old fashioned. Sometimes I just end up spending all of my evening on university websites or who's just been made a fellow of the NAS or the AAAS or a TED fellow because they're usually quite good and diverse, but really it could be a lot more automated. The problem that I've had comes back to the question before about notability improving sources that sometimes even from all of these automated generated things or people who've made suggestions and email me, they are absolutely staggering phenomenal women but it's really hard to prove they're as notable as you know they are. So I've been trying a lot more to make sure that I can do that before I write the page which is disappointing, but yeah, it could be more automated. But yeah, I think maybe this is too many or we've got one more question. We've got one more and hopefully maybe it's a quick one. Lotoic asks, you mentioned how Wikipedia content informs journalism, research, artificial intelligence and probably much more. Do you have insights to what extent that effect is mostly English Wikipedia and what the added effect is also having whether it's available in other languages too? Yeah, I think probably, I mean it's probably mainly true in English speaking Wikipedia because A, it's so big and B, journalists trust it and rely on it a lot. I don't know the differences and certain there'll be other communities and probably people in this workshop who know more about that than I do. But I think having the, you know, you saw it and you see it in lots of the different profiles, the amazing groups that with you women in red and all of these other groups that come together to mass edit pages about women in different topics, translating or writing about pages in different languages is obviously a really important way to get that knowledge into a whole different area of the world. And I do think probably journalists rely on it increasingly more, but probably not as much as in the UK or the US or English speaking Wikipedia, but I don't feel like I'm educated enough to give a proper answer on that. So sorry. Okay, bye everyone. My time is up. You can find me on Twitter or on email. Goodbye. Thank you so much, Jess. Thank you very much for being with us. Thank you very much, Isaac for taking the question. Thank you to you all who asked the question. I think