 Hi, you all, I'm here in Buenos Aires, Argentina. It's 4 PM right now. It's starting to get winter, and we are quarantined, as everyone, I think so. So what's this all about? I'm part of a group called Economía Feminista that we actually try to deal with economics from the feminism perspective. So what I want to show you is some really small projects that we did when I say small. I say that they were started small, and then they grew and get to different points. So the very, very first thing I want to say is that I am a cisgender male white dude. But in the group, I'm the only one, and the rest of them are all really great girls that are really awesome in their fields. And my field is nerdness and visualization, so that's why I'm talking to you guys. The rest of them are in different fields of economics and feminism, of course. So what I wanted to show you is this project that we started where we have these issues. We wanted to know what the outcome of the Congress, the law of free abortion, of choice, pro-choice. We wanted to know what the 257 deputies and 72 senators were going to vote. And of course, they didn't told us. So we are a really small group. We started thinking how we can do that if we don't have a high amount of money or humans to help God. But we did have a big community, our followers. And we have this moving topic, the legal abortion. So the very first thing we did was to make a spreadsheet, just a small spreadsheet where we put all the deputies, all the senators, and we started to see, that's why we call it portfolio, that's counting beans. So we started to see who we knew what they are going to vote and who we really know who was going to be voting against. The problem was that we are like seven or eight people working on this, and we didn't know all of the deputies of all of the provinces. Argentina, it's a federal country. So we started sharing the spreadsheet with friends and with friends of friends and with other people that we didn't even know. And all of them could be putting comments on it. So we didn't make a software. We didn't make something really strange or something really costy, we just shared a spreadsheet. We didn't have public data, sorry, we didn't allow to put things without source. So the data should be public. We didn't allow to put off the record voting, like I think this guy is going to put against or I think he's going to, no, you have to put a public source. You say, okay, this guy said in this media, this is the link, he says that. And the spreadsheet was open to comments. So we had like discussions like, wait, this, then this guy, this say that was going to vote against abortion and then he said he's going to go pro-choice. So those comments were tracked. The thing is that it was a simple spreadsheet, but it got so big and people started to share it and starting to use it as a source, like, wait, this is the voting, this is the polls. They even sent to our home, to my home, they sent a studio TV team, they shoot my screen. Like, it's kind of rare to say that, but they shoot the screen and put it live on TV, the screen from my computer. That's truly not the way we should do things, but this way it was working. So people was trusting more our simple spreadsheet than the real media. Actually, the media was trusting our spreadsheet. That's what you are seeing right now. This is kind of one of the biggest channels in Argentina. It's really ugly, you can tell, but it was trust that was important because people knew that all the data we had, all those voting numbers had a backup, a source, a public source. So that night where the Congress was debating these were a lot of people in the streets, really low connection or like, you know, 3G connection gets low when you have a lot of people. So we have, this is that night at 3 a.m. where people were freezing in the night and waiting for the Congress to give their votes. They were like 5,000 people logging in every hour. We have like 60,000 views that night. That's what's the local feel of that night. You have one side that is pro-choice and the other one that is against abortion and it was divided. And well, actually what ended happening was like, I want to share this video, it's awesome. So eventually, I don't know if you can hear, I don't think you can hear the songs, but people got really happy when the deputies approved the law. Eventually the senator didn't approve those so we don't have free abortion in Argentina. But the interesting thing about this project was all the data was open and the data started growing. We started adding the age of the deputies, the province where they were born, the family, how many kids they have if they are married or not. All the data started growing because people started adding that data, anyone. We just checked them, but they put comments and we added the comments to the spreadsheet. So eventually we started having like all kind of graphics to see if they were going to vote on pro-choice based on if they were like Catholic or not or they were practicing any religion. Then we have these kind of tangles of connection between all these dots here are the actual deputies and the connection between themselves. And you can see that you have like those two bubbles, ones that they are against and one they are pro and those connections are treated follow. So they follow themselves like in a bubble even if they are different parties. So eventually these other spin-offs that we have from this spreadsheet was for example this another project that was a way to call your deputies, your representative. You could treat them, you could call them, you can make a Facebook comment or whatever and like we were of course, we were all pro-choice but they could even use this tool if you were against abortion and you wanted to tell them to change their vote to get against it. So this tool was really interesting because you can even use it for other laws that were going to be passed. So the learnings about this was the content was really important. We didn't need something really innovative or awesome or nice, it was the content and the audience was trusting us more than trusting the media because they may have interests in these kind of things and they are so profound in their societies. And then if you can make something, other will. Like we wanted to make so many things with this data but we didn't have the resources but others did it. Others took the data and did other things and then all the collaborators that were adding information to the spreadsheet they just stick with us. They are making a lot of projects now. So other projects that we were building with the experience of this, one was really similar but was based on other, not only abortion but other gender issues like reproductive rights or pay gap or LGBT rights. So for the next election we did something really similar. We just made a form, a Google form, a really simple one where we asked what the position of every candidate on different subjects. How we shared that form with colleagues and followers and friends. So we started filling this information. Sometimes the politicians actually replied the form and other times we just Googled the information from all this. So we did this visualization so you can choose what deputies you wanted to vote. This also was crowdsourced in the same way of the other spreadsheet. Another thing that is not really based on spreadsheet but is based on a scrapping. We scrapped the page that the Argentine government had that is really poor in a way like it's really hard to interpret but it has a lot of data of prices of everything you can buy in a supermarket. What we did was scrap only the menstrual gene stuff for women or whoever menstruates. And we did this calculator to see how much anyone had to, how much money you need for having all these elements on your daily life, on your one year. So eventually this was really interesting because you could actually prove the pay gap because these are expenditures that we men, non menstruating men don't have. So that you have a pay gap demonstration right there for anyone that is not really believing that there is a pay gap. Another similar project, we have more governors called Carlos than women governors, gobernadoras. And we did also... This is your five minute warning. Thank you. So the funny thing about this, it was like we had to dig hard on different databases or not even databases but on media to find out who the governors were for the last 30 years because you don't have a database of that in the government or any official thing. So eventually we did these maps and the funny thing was this gift that you tried to click and get a women but you also always got Carlos probably. Then we... This is the governors of Argentina and see that you don't even have women for the 20 years ago. 10 years ago there were no women in charge of any province. And in the ministers of every province, it's a federal state so we have ministers, you can start finding out that as I was, you have the women only in human rights, education, health, social health. And then in security, economics, sports, like fuel, all those ministers, you don't have any women there. So it always has this kind of oh, this is a minister for women, not for men. Next thing was like a spin-off from this project with this account that stores and collects pictures of Argentinian politicians with not any women in the picture. That's the name of the mujeres en la foto. It's like the opposite of what's happening here. Another thing similar to this is Twitterbot that actually every day scraps all the main media like online version of the print media and gets the op-ed and gets if a women is signing the op-ed like the opinion columns. So what we got here is that we hardly get into the 25% every day but we also have some moments in the years that you have more women. We need few moments. Here we have abortion or the women march and then we have economic things that happen and then women get laid off and only men are speaking about economics. This is for the nerd audience. They are the Twitterbot. It's of course open source and has been replicated in like five countries already and it's really like nice. It's a gentle bot. It asks you if this name it's a female or male name. It has a database but sometimes it doesn't know so it asks you politely please and then it thanks you when you get to that. And here we have the same like words that are mostly in news that are signed by men and words that are usually in news piece signed by women. Again the same. Love, child's life education is for women. I'm doing the quarter marks. And in the other side for men it's like politics and the name of the president and economics and Trump and whatever. So I think this is it. I rushed but that's what we've been doing and all of our data is open and all of our projects are open to be replicated. Most of them are in Spanish but if you want to replicate anything in your language please reach out. I think I'm open to questions right now. I can't see you. I know I was muted. Thank you so much. And I think quite inspiring talk. And if I'd known you'd shared your screen on successfully on national TV I wouldn't have been so worried about getting ready for this talk. I thought it was fantastic. If anybody has a question then we've got time for a quick one. And I've got a quick question actually. I think it's fascinating like managing such an enormous spreadsheet as you're talking about the beginning of your talk. I was wondering if there were any kind of unusual related issues that you came up with that you might not have expected because I can imagine the sort of technical stuff that would have come up and from your side just managing the information but were there any behaviors that were strange to you? You mean like trolling the spreadsheet or something like that? Yeah, maybe like trolling or maybe like a non-negative thing that was just a difficult thing to manage. Well, we actually broke the thing because instead of sharing like the spreadsheets are made for sharing for a lot of people but there is a way to do that. You share it like as a web page but we didn't do that because we didn't know that so many people were going to get into it. So we share like when you share it to a colleague so it really broke. In a moment you couldn't enter anymore it gave you like a plain HTML. I know if there's some Google people working in Google and saw that the strengths of people getting into a spreadsheet I don't think like 65,000 people into a spreadsheet is really normal but like it was really interesting because people behaved greatly like it was not crude, not trolling not like I was astonished with that. It was really interesting. The downside was that I was sitting in this chair all that night like changing the data that came out. Actually some journalists treated to me like a DM asking me what was the next like what was the voting in that morning. I'm not a journalist like pretty known journalists were asking me that I know one but they didn't trust me because not me they trusted our spreadsheet because it was so crude founded so crude sources, sorry. Thank you. Absolutely fascinating, it was really good. I'm going to ask one more question from the audience. We'll have to be quite quick but it's from Valeria and it says do you have any collaboration with other countries? Yeah, we actually did. We replicated like this one are you still seeing my share screen? Yeah. This one the columnist has been replicated like five different countries in Latin America and this one about this one it's also been replicated and yeah, we are really open to collaborate with most Latin American because it's in Spanish it's really easy to replicate. Amazing. Okay, well maybe you could expand a little bit on that and share some links in the Q&A channel in Slack. Kathleen, thank you for your question as well. I decided to give Valeria a go given that you're going to be speaking later but Andres, I'm sure you'll be happy to answer that question later as well. So thank you very much.