1 00:00:00,680 --> 00:00:03,680 Speaker 1: You and Me Both is a production of I Heart Radio. 2 00:00:04,960 --> 00:00:08,600 Speaker 1: Do I hope that in your spare time you hung 3 00:00:08,680 --> 00:00:12,440 Speaker 1: around in sweats? Yes? I do? Well, Yeah I am, 4 00:00:12,480 --> 00:00:15,440 Speaker 1: I am okay, But yeah, I thought it was so 5 00:00:15,880 --> 00:00:18,760 Speaker 1: appropriate and you made more of an effort than I've 6 00:00:18,760 --> 00:00:21,520 Speaker 1: ever seen any money necessarily make in those situations, and 7 00:00:21,560 --> 00:00:26,239 Speaker 1: I really appreciated it. I'm Hillary Clinton, and this is 8 00:00:26,480 --> 00:00:29,120 Speaker 1: You and Me Both, where I get into some of 9 00:00:29,160 --> 00:00:33,720 Speaker 1: today's biggest questions with people I admire. On today's episode, 10 00:00:33,760 --> 00:00:37,600 Speaker 1: we're talking about the American Dream. What exactly do we 11 00:00:37,720 --> 00:00:41,200 Speaker 1: mean when we say that? And is it still possible 12 00:00:41,280 --> 00:00:44,640 Speaker 1: to achieve? You know, I think the American dream is 13 00:00:44,680 --> 00:00:47,800 Speaker 1: still achievable, but I think we have our eyes wide 14 00:00:47,840 --> 00:00:51,200 Speaker 1: open about how hard it is for so many people. 15 00:00:51,600 --> 00:00:54,720 Speaker 1: There are all kinds of obstacles that have to be 16 00:00:54,840 --> 00:00:58,600 Speaker 1: overcommon individual lives. And I'm interested not only in that, 17 00:00:58,720 --> 00:01:00,920 Speaker 1: but also what do we need to do to change 18 00:01:00,920 --> 00:01:04,440 Speaker 1: our economy and our society and our culture and our 19 00:01:04,520 --> 00:01:08,000 Speaker 1: mindset to make sure more people have a chance to 20 00:01:08,080 --> 00:01:12,640 Speaker 1: fulfill whatever they think is their American Dream. So I'm 21 00:01:12,680 --> 00:01:16,520 Speaker 1: talking to three people today. Lorella pray Lee is a 22 00:01:16,560 --> 00:01:20,720 Speaker 1: former dreamer. She's an advocate for immigrants and low income 23 00:01:20,760 --> 00:01:26,200 Speaker 1: Americans and has an amazing story. Raj Chetty is an 24 00:01:26,200 --> 00:01:30,200 Speaker 1: economist who studies opportunity. In other words, how do we 25 00:01:30,560 --> 00:01:34,160 Speaker 1: help more people fulfill their dreams? What needs to be 26 00:01:34,200 --> 00:01:43,320 Speaker 1: done to make that happen? But first, Tan France Now 27 00:01:43,400 --> 00:01:47,800 Speaker 1: you Know. Tan is the fashion expert on Netflix's Queer Eye, 28 00:01:48,080 --> 00:01:51,600 Speaker 1: which was rebooted in Team You Know. It's a really 29 00:01:51,720 --> 00:01:56,200 Speaker 1: fun and heartwarming show. In each episode, Tan and the 30 00:01:56,240 --> 00:01:59,520 Speaker 1: rest of the Fab five team hit the road to 31 00:01:59,600 --> 00:02:03,240 Speaker 1: spend time with someone who is pursuing their dream or 32 00:02:03,520 --> 00:02:05,760 Speaker 1: just trying to get by, and to give them a 33 00:02:05,760 --> 00:02:09,840 Speaker 1: little boost. This show has made Tan a household name. 34 00:02:10,200 --> 00:02:13,800 Speaker 1: He's one of the first openly gay South Asian and 35 00:02:14,000 --> 00:02:17,960 Speaker 1: Muslim men on TV in the United States, and as 36 00:02:18,040 --> 00:02:22,440 Speaker 1: you'll hear, he is completely charming. He lives in Salt 37 00:02:22,560 --> 00:02:26,040 Speaker 1: Lake City, Utah, with his husband Rob and their two kids. 38 00:02:26,560 --> 00:02:31,000 Speaker 1: He's author of the memoir Naturally Tan, I love that title. 39 00:02:31,600 --> 00:02:34,440 Speaker 1: There were so many reasons why I wanted to talk 40 00:02:34,480 --> 00:02:38,200 Speaker 1: to him about the American dream. He recently became a 41 00:02:38,320 --> 00:02:42,520 Speaker 1: US citizen, and because he spends so much time helping 42 00:02:42,560 --> 00:02:45,000 Speaker 1: people live their own dreams, he has some pretty good 43 00:02:45,000 --> 00:02:48,200 Speaker 1: insight into what it takes to, you know, have the 44 00:02:48,240 --> 00:02:52,240 Speaker 1: American dream in the twenty one century. You know, let 45 00:02:52,240 --> 00:02:55,959 Speaker 1: me start by congratulating you, because I know you became 46 00:02:56,000 --> 00:02:59,840 Speaker 1: a US citizen this past June. I should what did 47 00:02:59,840 --> 00:03:03,680 Speaker 1: that feel like? You know, I don't think I've still 48 00:03:03,760 --> 00:03:07,000 Speaker 1: quite possessed it. I've been working on this for so long. 49 00:03:07,120 --> 00:03:09,840 Speaker 1: I wanted to be an American citizen pretty much my 50 00:03:09,880 --> 00:03:11,920 Speaker 1: whole life. Since I was a little boy and I 51 00:03:11,919 --> 00:03:14,560 Speaker 1: was sat there watching American TV. I dreamt of this, 52 00:03:15,120 --> 00:03:18,400 Speaker 1: and so the moment that it happened, I was so 53 00:03:18,520 --> 00:03:21,560 Speaker 1: overcome with emotion that all I could do was eat 54 00:03:21,639 --> 00:03:23,760 Speaker 1: donuts because that was the most American thing I could 55 00:03:23,800 --> 00:03:25,960 Speaker 1: think of. I went to the donut shop down the 56 00:03:26,000 --> 00:03:28,600 Speaker 1: street and eight donuts, and that was my version of 57 00:03:28,600 --> 00:03:32,000 Speaker 1: being a true American. Well, I think that's a very 58 00:03:32,040 --> 00:03:36,680 Speaker 1: American response, you know, to the emotion of the you know, 59 00:03:36,760 --> 00:03:40,080 Speaker 1: of the minute. Um, Where were you actually sworn in 60 00:03:40,080 --> 00:03:42,040 Speaker 1: in Salt Lake City, Utah, which is where I live 61 00:03:42,160 --> 00:03:44,200 Speaker 1: right now. Well, now, explain how you went from New 62 00:03:44,240 --> 00:03:47,040 Speaker 1: York to Salt Lake What was that connection? Well? I 63 00:03:47,200 --> 00:03:50,480 Speaker 1: never heard of Utah, and quite honestly, when I tell 64 00:03:50,560 --> 00:03:52,520 Speaker 1: my friends and family in England, they have no idea 65 00:03:52,560 --> 00:03:55,200 Speaker 1: where it might be on the map. And so I 66 00:03:55,240 --> 00:03:57,640 Speaker 1: was living in New York. I had a housemate who 67 00:03:57,720 --> 00:04:01,200 Speaker 1: was from Salt Lake City, Utah, and he suggested that 68 00:04:01,240 --> 00:04:03,480 Speaker 1: I go and visit. And I had no idea what 69 00:04:03,520 --> 00:04:05,560 Speaker 1: it might be like, what it might look like. It 70 00:04:05,680 --> 00:04:09,280 Speaker 1: sounded very country, and I was surprised to see that 71 00:04:09,280 --> 00:04:11,960 Speaker 1: they have a proper city, and I fell in love 72 00:04:12,400 --> 00:04:15,200 Speaker 1: with the city pretty much immediately. Within an hour, I 73 00:04:15,240 --> 00:04:17,840 Speaker 1: decided I was going to make this my home. Was 74 00:04:17,880 --> 00:04:22,400 Speaker 1: there something about Salt Lake that you felt connected to 75 00:04:22,960 --> 00:04:26,600 Speaker 1: because of your you know, growing up in different cultures 76 00:04:26,680 --> 00:04:30,080 Speaker 1: and different countries. You grew up in Britain, your parents 77 00:04:30,160 --> 00:04:34,440 Speaker 1: or immigrants from Pakistan, you were raised Muslim. How did 78 00:04:34,760 --> 00:04:38,000 Speaker 1: it come to be that going to Salt Lake, well 79 00:04:38,040 --> 00:04:42,159 Speaker 1: known as a beautiful cosmopolitan city but also the home 80 00:04:42,240 --> 00:04:46,000 Speaker 1: of the Church of Jesus Christ of Latter day Saints, 81 00:04:46,040 --> 00:04:50,240 Speaker 1: became the magnet for you. I don't know how honest 82 00:04:50,920 --> 00:04:53,000 Speaker 1: you would like me to be. If it spent to 83 00:04:53,040 --> 00:04:54,920 Speaker 1: be light hospital, I'm going to give you my deep, 84 00:04:54,960 --> 00:04:59,039 Speaker 1: deep Okay, So my honest, honest answer is this, so 85 00:04:59,400 --> 00:05:01,839 Speaker 1: you sin that I was a child of immigrants. I am. 86 00:05:01,920 --> 00:05:07,400 Speaker 1: My parents came from Pakistan and Kashmir, India, respectively, and 87 00:05:07,520 --> 00:05:10,240 Speaker 1: I was raised in the UK. And I don't know 88 00:05:10,960 --> 00:05:13,719 Speaker 1: what experience you have with the South Asian community in 89 00:05:13,720 --> 00:05:16,760 Speaker 1: the UK, but we are kind of seen as second 90 00:05:16,839 --> 00:05:20,760 Speaker 1: lass citizens in that you wouldn't really take us home 91 00:05:20,839 --> 00:05:22,800 Speaker 1: to meet your parents. If you were to date us, 92 00:05:23,240 --> 00:05:26,839 Speaker 1: it wouldn't We would be the undesirable dating community. And 93 00:05:26,880 --> 00:05:28,479 Speaker 1: that was definitely the case when I was a kid, 94 00:05:29,040 --> 00:05:32,200 Speaker 1: and especially after nine eleven and I was seven team 95 00:05:32,240 --> 00:05:36,680 Speaker 1: and nine eleven happened. And so when I came to Utah, 96 00:05:36,839 --> 00:05:38,760 Speaker 1: the reason why I seven in the first hour is 97 00:05:38,760 --> 00:05:41,160 Speaker 1: because we went to a restaurant. I didn't know what 98 00:05:41,200 --> 00:05:42,719 Speaker 1: it was at the time, but it turned out to 99 00:05:42,720 --> 00:05:46,200 Speaker 1: be Chili's. And within an hour or so, I had 100 00:05:46,240 --> 00:05:49,520 Speaker 1: had so many people just smile and ask where I 101 00:05:49,600 --> 00:05:52,640 Speaker 1: was from, and somebody here on me during that time, 102 00:05:53,200 --> 00:05:56,800 Speaker 1: and I had never experienced anything like it where my 103 00:05:57,440 --> 00:05:59,440 Speaker 1: call at the color of my skin and my ethnicity 104 00:05:59,640 --> 00:06:02,120 Speaker 1: seemed to be the thing that made people want to 105 00:06:02,120 --> 00:06:04,320 Speaker 1: get to know me as opposed to make people not 106 00:06:04,400 --> 00:06:07,000 Speaker 1: want to talk to me. And that thought so special. Oh, 107 00:06:07,040 --> 00:06:11,960 Speaker 1: that's so interesting, and that was like almost immediate immediate. 108 00:06:12,440 --> 00:06:15,400 Speaker 1: I really wanted to ask you. You know, this is 109 00:06:15,400 --> 00:06:21,400 Speaker 1: not our nation's brightest moment. We are struggling with, you know, 110 00:06:21,600 --> 00:06:26,080 Speaker 1: so much turmoil and so many challenges. What do I 111 00:06:26,080 --> 00:06:28,800 Speaker 1: feel like officially to become an American at this pretty 112 00:06:28,880 --> 00:06:33,200 Speaker 1: messy and divisive time? You know? I my husband asked me. 113 00:06:33,640 --> 00:06:35,400 Speaker 1: My husband's name is Rob, and he asked me the 114 00:06:35,440 --> 00:06:38,480 Speaker 1: same question. He said, does it feel weird after wanting 115 00:06:38,520 --> 00:06:41,320 Speaker 1: this your whole life to get to the point where 116 00:06:42,080 --> 00:06:44,760 Speaker 1: you are are now an American citizen? And we actually 117 00:06:44,800 --> 00:06:47,159 Speaker 1: do have a lot to be ashamed of? And I 118 00:06:47,240 --> 00:06:50,200 Speaker 1: say that as a true patriot. I and I do 119 00:06:50,279 --> 00:06:52,680 Speaker 1: class myself as a patriot. Even though I'm an immigrant. 120 00:06:52,720 --> 00:06:54,720 Speaker 1: I fought my whole life to be able to live here. 121 00:06:55,080 --> 00:06:58,960 Speaker 1: I love this country, truly, I do, and it's sad 122 00:06:59,080 --> 00:07:03,000 Speaker 1: that I became and during this time. However, I've always 123 00:07:03,000 --> 00:07:06,320 Speaker 1: been an incredibly optimistic person my whole life. The thing 124 00:07:06,320 --> 00:07:09,200 Speaker 1: that actually drives many people crazy is that I always 125 00:07:09,240 --> 00:07:13,760 Speaker 1: see hope, even though sometimes I probably isn't very much. However, 126 00:07:13,840 --> 00:07:16,320 Speaker 1: even now I see true hope, and so for me. 127 00:07:17,000 --> 00:07:19,680 Speaker 1: I was excited to be able to vote this year. 128 00:07:20,000 --> 00:07:22,640 Speaker 1: I thought, what better year than to get my citizenship 129 00:07:22,640 --> 00:07:24,920 Speaker 1: when I can finally vote and encourage people to vote. 130 00:07:24,920 --> 00:07:27,000 Speaker 1: And I've been encouraging people to vote for quite some time, 131 00:07:27,320 --> 00:07:30,080 Speaker 1: but it didn't really mean enough when I wasn't able 132 00:07:30,120 --> 00:07:31,960 Speaker 1: to vote myself and to say, I mean it with you. 133 00:07:33,200 --> 00:07:35,720 Speaker 1: And so the way I see is, yes, it was 134 00:07:35,760 --> 00:07:38,440 Speaker 1: a very strange year to become a citizen. However, I 135 00:07:38,480 --> 00:07:41,080 Speaker 1: will forever remember it as the first time I voted 136 00:07:41,200 --> 00:07:43,560 Speaker 1: was a time when I desperately wanted my vote to 137 00:07:43,600 --> 00:07:48,760 Speaker 1: be here. Absolutely. Well. You know, since um, you've had 138 00:07:48,800 --> 00:07:52,600 Speaker 1: the opportunity to criss cross our country. You have been 139 00:07:52,840 --> 00:07:58,440 Speaker 1: all over America. You've met Americans. Oh wow, So you 140 00:07:58,440 --> 00:08:02,000 Speaker 1: you really are talking with people literally on the ground, 141 00:08:02,120 --> 00:08:05,760 Speaker 1: and you're having very personal conversations. I mean when you, 142 00:08:05,760 --> 00:08:08,440 Speaker 1: you know, hold up somebody's pajamas and say, you know, 143 00:08:08,600 --> 00:08:11,280 Speaker 1: you're not gonna have sex in these pajamas, and the 144 00:08:11,320 --> 00:08:14,280 Speaker 1: stuff that you tell them, Um, you know, you're really 145 00:08:14,720 --> 00:08:16,880 Speaker 1: in their lives in a way that most of us 146 00:08:16,960 --> 00:08:21,040 Speaker 1: never get a chance to be. So how has that 147 00:08:21,280 --> 00:08:25,840 Speaker 1: affected your feelings about you know, both the country and 148 00:08:25,960 --> 00:08:29,679 Speaker 1: you know your place in it. It's been interesting going 149 00:08:29,720 --> 00:08:31,840 Speaker 1: to places I've never been before. Within this country. I 150 00:08:31,920 --> 00:08:34,920 Speaker 1: had lived here for ten years or nine years at 151 00:08:34,960 --> 00:08:37,160 Speaker 1: the time when I got the job, and open to 152 00:08:37,240 --> 00:08:39,720 Speaker 1: that point, i'd probably visited three or four states. I 153 00:08:39,760 --> 00:08:42,719 Speaker 1: felt like I knew that you talking men too well enough. 154 00:08:42,960 --> 00:08:45,000 Speaker 1: The New York I been too well enough. But going 155 00:08:45,280 --> 00:08:48,080 Speaker 1: across the country has really opened my eyes, not just 156 00:08:48,120 --> 00:08:51,000 Speaker 1: with where I go to universities across the country and 157 00:08:51,040 --> 00:08:54,400 Speaker 1: do speaking engagements and speak with college students who are 158 00:08:54,520 --> 00:08:58,240 Speaker 1: at that impressionable age and talk about what they're going through. 159 00:08:58,320 --> 00:09:02,360 Speaker 1: And it's been interest in learning what has happened with 160 00:09:02,440 --> 00:09:06,480 Speaker 1: their lives since two thousand eighteen. And it feels like 161 00:09:06,520 --> 00:09:08,480 Speaker 1: so many people have fed up, they feel stuck in 162 00:09:08,600 --> 00:09:11,240 Speaker 1: what they don't feel hid and that has been the 163 00:09:11,280 --> 00:09:14,280 Speaker 1: most common interaction we've had with people, is that they 164 00:09:14,280 --> 00:09:17,800 Speaker 1: don't feel seeing, they don't feel loved enough. That really 165 00:09:17,880 --> 00:09:21,760 Speaker 1: resonates with me because I think when you sort of 166 00:09:21,800 --> 00:09:25,800 Speaker 1: strip it all down, um, loving and being loved is 167 00:09:25,840 --> 00:09:29,800 Speaker 1: at the core of the you know, human experience, and 168 00:09:30,240 --> 00:09:33,240 Speaker 1: you see that with the people that you're working with 169 00:09:33,360 --> 00:09:36,760 Speaker 1: and that you're visiting with. Do you get the sense 170 00:09:36,880 --> 00:09:39,920 Speaker 1: that this divisiveness that we see in the country can 171 00:09:39,960 --> 00:09:44,959 Speaker 1: be reconciled and healed with different attitudes, not just from leaders, 172 00:09:45,000 --> 00:09:47,319 Speaker 1: but from all of us. I would like to believe. 173 00:09:47,360 --> 00:09:50,840 Speaker 1: So I think that what Netflix did super well. And 174 00:09:50,920 --> 00:09:53,360 Speaker 1: if this isn't just a sales pitch for Netflix, that 175 00:09:53,640 --> 00:09:56,640 Speaker 1: believe me. I just truly believe they did this very well. 176 00:09:56,679 --> 00:09:59,319 Speaker 1: They decided that they were going to bring back where 177 00:09:59,400 --> 00:10:03,280 Speaker 1: I time when we knew that things were going to 178 00:10:03,480 --> 00:10:06,000 Speaker 1: become more divided than they have been in a very 179 00:10:06,000 --> 00:10:10,640 Speaker 1: long time, and so Netflix saw our community as the bridge. 180 00:10:10,720 --> 00:10:12,600 Speaker 1: We get to speak with people in a way that 181 00:10:12,720 --> 00:10:15,960 Speaker 1: most people aren't afforded. For example, I can speak with 182 00:10:16,000 --> 00:10:18,000 Speaker 1: women without them feeling bettened at all by me. I 183 00:10:18,000 --> 00:10:21,199 Speaker 1: can speak with men without them worrying that we might 184 00:10:21,200 --> 00:10:23,120 Speaker 1: be trying to get their women or trying to compete 185 00:10:23,160 --> 00:10:25,440 Speaker 1: for their job. We are a community that they're not 186 00:10:25,960 --> 00:10:28,360 Speaker 1: majorly threatened by, and they're willing to open up to us, 187 00:10:28,600 --> 00:10:31,920 Speaker 1: and we use our skills, which are very personal, as 188 00:10:31,960 --> 00:10:34,880 Speaker 1: a vehicle to be able to have conversations. And so 189 00:10:35,480 --> 00:10:37,960 Speaker 1: we are in a very fudge position where people will 190 00:10:38,000 --> 00:10:40,680 Speaker 1: open up to us. More so than they would most 191 00:10:40,720 --> 00:10:43,520 Speaker 1: other people. When I'm in somebody's closet and I'm seeing 192 00:10:43,520 --> 00:10:46,280 Speaker 1: them in their underwear, they are in their most vulnerable state. 193 00:10:46,280 --> 00:10:47,920 Speaker 1: I can ask them pretty much anything at that point 194 00:10:48,160 --> 00:10:52,440 Speaker 1: and they'll likely answer. I think that that timing was crucial. 195 00:10:52,640 --> 00:10:57,120 Speaker 1: Netflix saw us as the bridge between the Democrats and Republicans, 196 00:10:57,200 --> 00:11:00,600 Speaker 1: quite honestly, and we went in with the mission we 197 00:11:00,640 --> 00:11:03,920 Speaker 1: wanted to meet as many people who didn't sing from 198 00:11:03,920 --> 00:11:06,880 Speaker 1: our hymn sheet that the people who had no interest 199 00:11:07,040 --> 00:11:09,840 Speaker 1: ordinarily in hearing outside of the story. But when you're 200 00:11:09,840 --> 00:11:11,920 Speaker 1: in your underwear, and you're probably more likely to tell 201 00:11:11,960 --> 00:11:14,600 Speaker 1: me what you think because I've got you trapped, And 202 00:11:14,640 --> 00:11:17,800 Speaker 1: that feels very special, and we put a face to 203 00:11:18,559 --> 00:11:21,679 Speaker 1: what people may see as a threat. They don't understand 204 00:11:21,800 --> 00:11:26,120 Speaker 1: our community, and the five of us represent many communities, 205 00:11:26,960 --> 00:11:30,400 Speaker 1: and so they get a personal interaction with a person 206 00:11:30,440 --> 00:11:32,760 Speaker 1: that they've probably never spoken to before. And so I'm 207 00:11:32,800 --> 00:11:35,720 Speaker 1: able to say to somebody, when you vote for somebody 208 00:11:36,360 --> 00:11:41,240 Speaker 1: like Trump, you are voting against me, You're voting against 209 00:11:41,240 --> 00:11:44,199 Speaker 1: my people, you voting against everything that we represent. So 210 00:11:44,440 --> 00:11:46,960 Speaker 1: it's not just a blind vote for a Republican. And 211 00:11:47,000 --> 00:11:50,000 Speaker 1: I think that's My biggest concern with a lot of 212 00:11:50,040 --> 00:11:52,960 Speaker 1: Americans who vote, they will vote for whoever it is, 213 00:11:52,960 --> 00:11:55,640 Speaker 1: as long as it's their party. And I will never 214 00:11:55,720 --> 00:11:58,360 Speaker 1: understand that. I don't think most Brits vote that way. 215 00:11:58,679 --> 00:12:00,760 Speaker 1: If we don't like somebody, we're not going to vote 216 00:12:00,800 --> 00:12:03,040 Speaker 1: with them, regardless of whether there are patty or not. 217 00:12:03,400 --> 00:12:05,960 Speaker 1: And I wish that we had more of that mentality here, 218 00:12:06,040 --> 00:12:08,600 Speaker 1: and so I feel the opportunity that we have with 219 00:12:08,720 --> 00:12:11,760 Speaker 1: Queer I is to have those conversations and say, I 220 00:12:11,800 --> 00:12:15,439 Speaker 1: am the person you're actually voting against. Here we're taking 221 00:12:15,440 --> 00:12:19,960 Speaker 1: a quick break. Stay with us. When you think about, 222 00:12:20,240 --> 00:12:22,760 Speaker 1: you know, Queer I and being part of it now, 223 00:12:22,960 --> 00:12:27,560 Speaker 1: it's so much more than a makeover. It really is 224 00:12:27,640 --> 00:12:31,120 Speaker 1: about meeting people where they are, giving them a boost, 225 00:12:31,360 --> 00:12:34,920 Speaker 1: trying to give them some sense of meaning and purpose 226 00:12:35,679 --> 00:12:39,120 Speaker 1: and even a financial boost. And I really love what 227 00:12:39,240 --> 00:12:43,200 Speaker 1: the Fab five does for these folks that you meet, 228 00:12:43,840 --> 00:12:47,080 Speaker 1: but it also kind of makes me sad that there 229 00:12:47,120 --> 00:12:50,200 Speaker 1: are so many millions of people who will never meet you. 230 00:12:50,320 --> 00:12:54,440 Speaker 1: Maybe they'll get you vicariously by watching the program. So 231 00:12:54,600 --> 00:12:57,200 Speaker 1: have you thought about, you know, if you could waive 232 00:12:57,280 --> 00:13:00,920 Speaker 1: the proverbial magic wand what are a couple of things 233 00:13:00,960 --> 00:13:03,800 Speaker 1: that you think could be changed that would help more 234 00:13:03,840 --> 00:13:06,240 Speaker 1: people than you'll ever possibly be able to get to. 235 00:13:06,559 --> 00:13:09,360 Speaker 1: The one thing for me personally that I try to 236 00:13:09,360 --> 00:13:11,920 Speaker 1: communicate as much as possible wherever ever I am, whether 237 00:13:11,960 --> 00:13:14,400 Speaker 1: it be in person, on the show or if I'm 238 00:13:14,400 --> 00:13:17,480 Speaker 1: doing TV, and I will always try and put this 239 00:13:17,520 --> 00:13:21,040 Speaker 1: one agenda. All the things that we're offering are just 240 00:13:21,320 --> 00:13:23,480 Speaker 1: as I've mentioned, for a vehicle to have a conversation 241 00:13:23,520 --> 00:13:25,839 Speaker 1: and to really encourage a certain kind of self esteem 242 00:13:25,840 --> 00:13:28,319 Speaker 1: in a person and to encourage them to see themselves 243 00:13:28,400 --> 00:13:32,480 Speaker 1: as better than they believe they are. And the main 244 00:13:32,720 --> 00:13:34,760 Speaker 1: thing I want people to take away is that we 245 00:13:34,840 --> 00:13:37,600 Speaker 1: are incredibly mean to ourselves when we look in the mirror. 246 00:13:37,960 --> 00:13:40,800 Speaker 1: The things that we think about ourselves are seldom things 247 00:13:40,840 --> 00:13:43,480 Speaker 1: that people are thinking of us. And so to look 248 00:13:43,520 --> 00:13:45,559 Speaker 1: in the mirror and remind ourselves and the things that 249 00:13:45,600 --> 00:13:48,000 Speaker 1: are actually wonderful about us, the reason why we have 250 00:13:48,080 --> 00:13:51,520 Speaker 1: friends and family who love us. I want people to 251 00:13:51,600 --> 00:13:54,959 Speaker 1: realize that those things are so much more important than 252 00:13:55,000 --> 00:13:57,200 Speaker 1: the new wardrobe I might give them, all the new 253 00:13:57,440 --> 00:14:00,800 Speaker 1: sofa that Bobby might give them. They're just the things 254 00:14:00,880 --> 00:14:04,760 Speaker 1: that make a good TV show our show is reminding 255 00:14:04,800 --> 00:14:06,960 Speaker 1: them that they are so much more than they think 256 00:14:07,000 --> 00:14:08,880 Speaker 1: they are, and so we're just kind of holding up 257 00:14:08,880 --> 00:14:11,600 Speaker 1: a merrit to them and saying, look at you. I 258 00:14:11,640 --> 00:14:14,800 Speaker 1: want you to tell me, basically, in a nutshell, what 259 00:14:15,080 --> 00:14:17,280 Speaker 1: you think that everybody else sees in you that you 260 00:14:17,320 --> 00:14:20,680 Speaker 1: clearly don't. Why do people love you? There's a reason why. 261 00:14:20,800 --> 00:14:23,600 Speaker 1: But you went through that whole process yourself. I mean 262 00:14:23,720 --> 00:14:28,120 Speaker 1: your memoir, naturally, Tan, you know, talks about your struggles 263 00:14:28,120 --> 00:14:31,480 Speaker 1: and your conflicts and your doubts, and you know, very 264 00:14:31,560 --> 00:14:35,520 Speaker 1: personal aspects of how you became who you are today. 265 00:14:35,680 --> 00:14:39,800 Speaker 1: I mean, we see you, We see the confidence, the optimism, 266 00:14:39,880 --> 00:14:42,680 Speaker 1: the joy in your life. But it wasn't always like that, 267 00:14:42,880 --> 00:14:46,040 Speaker 1: was it. No. I think if anybody ever suggests that 268 00:14:46,080 --> 00:14:49,280 Speaker 1: they have always been happy and that there's never a 269 00:14:49,280 --> 00:14:52,360 Speaker 1: time when they've suffered hardship, I just wouldn't believe it. 270 00:14:52,840 --> 00:14:54,800 Speaker 1: I think to get to the point where you can 271 00:14:54,920 --> 00:14:57,120 Speaker 1: be as optimistic as I am, you have to have 272 00:14:57,200 --> 00:15:00,560 Speaker 1: seen some bad things and experienced a lot. Then you 273 00:15:00,560 --> 00:15:04,040 Speaker 1: you've overcome it, and you've overcome it through great strength. 274 00:15:04,040 --> 00:15:06,200 Speaker 1: It does require great strength. There were times when I 275 00:15:06,240 --> 00:15:09,000 Speaker 1: struggled with my businesses. When I first moved to America, 276 00:15:09,080 --> 00:15:11,680 Speaker 1: I started my business as it was the American dream 277 00:15:11,720 --> 00:15:14,440 Speaker 1: that I was desperate to fulfill, and I did. But 278 00:15:14,520 --> 00:15:17,240 Speaker 1: it didn't get to that point without a few years 279 00:15:17,240 --> 00:15:21,200 Speaker 1: of hallacious hard work and as a child going through 280 00:15:21,240 --> 00:15:24,520 Speaker 1: the racism that we went through so regularly, and just 281 00:15:24,640 --> 00:15:26,600 Speaker 1: then that there was light of the tunnel. Even though 282 00:15:26,640 --> 00:15:28,720 Speaker 1: somebody may not have liked us for our skin color 283 00:15:28,800 --> 00:15:32,160 Speaker 1: or religion, my sexuality, there was still so much more 284 00:15:32,160 --> 00:15:35,600 Speaker 1: that I liked about myself, even if those strangers couldn't 285 00:15:35,640 --> 00:15:38,240 Speaker 1: see it. And so that is the message I desperately 286 00:15:38,240 --> 00:15:40,400 Speaker 1: want to push forward on the likes of CERA or 287 00:15:40,440 --> 00:15:43,560 Speaker 1: any platform I have, is that yes, people may throw stones, 288 00:15:43,640 --> 00:15:47,440 Speaker 1: but the one thing I say to everyone, I refused 289 00:15:47,480 --> 00:15:50,000 Speaker 1: to be the reason I'm unhappy. No matter what has 290 00:15:50,040 --> 00:15:52,080 Speaker 1: gone on in my life, I refused to be the 291 00:15:52,080 --> 00:15:54,400 Speaker 1: reason I'm unhappy. They can say what they want. I 292 00:15:54,440 --> 00:15:57,280 Speaker 1: have more control of my feelings than they do, and 293 00:15:57,320 --> 00:16:00,400 Speaker 1: so I will find a way to make myself happy. Man, 294 00:16:00,640 --> 00:16:04,560 Speaker 1: and I just have to thank you for being naturally 295 00:16:04,680 --> 00:16:08,520 Speaker 1: you and talking with me today. I hope we get 296 00:16:08,520 --> 00:16:12,000 Speaker 1: to meet in person at some point whenever the pandemic. 297 00:16:13,480 --> 00:16:17,400 Speaker 1: We can I encrupt you. Go right ahead, Dan, I 298 00:16:17,440 --> 00:16:20,960 Speaker 1: know that people, many people had their opinions on what 299 00:16:21,040 --> 00:16:24,400 Speaker 1: you are during your campaign. I am not just saying 300 00:16:24,400 --> 00:16:27,760 Speaker 1: this because I've adored you for my whole life. You 301 00:16:27,920 --> 00:16:31,480 Speaker 1: looked wonderful. Here's the thing. I will mention this also, 302 00:16:31,720 --> 00:16:35,880 Speaker 1: it didn't matter. It shouldn't matter. Trump turned up looking 303 00:16:36,160 --> 00:16:39,080 Speaker 1: like a joke every time, and nobody seem to care 304 00:16:39,120 --> 00:16:42,240 Speaker 1: that much. But you clearly made an effort. I love 305 00:16:42,320 --> 00:16:45,840 Speaker 1: that you did so many times the full modoco look 306 00:16:45,840 --> 00:16:47,400 Speaker 1: where you would go for a full blue or a 307 00:16:47,440 --> 00:16:52,240 Speaker 1: full whatever. But I thought you looked regal almost. Do 308 00:16:52,320 --> 00:16:56,080 Speaker 1: I hope that in your spare time you hung around 309 00:16:56,080 --> 00:17:01,120 Speaker 1: in sweats? Yes, I do, but going okay, but yeah, 310 00:17:01,360 --> 00:17:05,280 Speaker 1: I thought it was so appropriate and you made more 311 00:17:05,280 --> 00:17:07,600 Speaker 1: of an effort that I've ever seen any money necessarily 312 00:17:07,680 --> 00:17:12,520 Speaker 1: make in those situations. And I really appreciated it. Thank you, 313 00:17:12,720 --> 00:17:18,919 Speaker 1: Thank you, I love you even more. Tan France is 314 00:17:18,960 --> 00:17:23,720 Speaker 1: the author of Naturally Tan, a memoir. Season six of 315 00:17:23,800 --> 00:17:27,040 Speaker 1: Queer Eye, which will be filmed in Austin, Texas, one 316 00:17:27,040 --> 00:17:30,520 Speaker 1: of my favorite American cities is on hold due to 317 00:17:30,560 --> 00:17:33,719 Speaker 1: the pandemic. But you can watch the most recent season, 318 00:17:33,760 --> 00:17:41,440 Speaker 1: as well as his other show Next in Fashion on Netflix. Now, 319 00:17:41,480 --> 00:17:45,119 Speaker 1: I'll be talking to Lorella pray Lee. Lorella is a 320 00:17:45,240 --> 00:17:50,440 Speaker 1: dreamer who became a US citizen and she's an incredible organizer. 321 00:17:50,520 --> 00:17:53,720 Speaker 1: I can speak from experience. I was lucky enough to 322 00:17:53,800 --> 00:17:58,320 Speaker 1: have her working on my twenty sixteen presidential campaign and 323 00:17:58,400 --> 00:18:03,520 Speaker 1: she was everywhere. No matter where I went, there she was. 324 00:18:04,040 --> 00:18:07,879 Speaker 1: She just has a natural ability to draw people to 325 00:18:08,040 --> 00:18:12,000 Speaker 1: her to the causes that she is advocating. She was 326 00:18:12,040 --> 00:18:15,520 Speaker 1: born in Peru. Her parents brought her to the United 327 00:18:15,560 --> 00:18:19,640 Speaker 1: States as a very young child for medical treatments, and 328 00:18:19,720 --> 00:18:22,960 Speaker 1: you're going to hear about that now. At just thirty 329 00:18:23,000 --> 00:18:27,560 Speaker 1: two years old, she's president of Community Change, an organization 330 00:18:27,680 --> 00:18:32,440 Speaker 1: that empowers low income Americans to fight for a more 331 00:18:32,480 --> 00:18:37,040 Speaker 1: just future for themselves, their children, and generations to come. 332 00:18:37,600 --> 00:18:40,359 Speaker 1: As you're about to hear, Lurella is a kind of 333 00:18:40,400 --> 00:18:43,080 Speaker 1: person who makes you want to get up and go 334 00:18:43,160 --> 00:18:50,560 Speaker 1: out and change the world. Hello, Corella, how are you? Lorella? 335 00:18:50,640 --> 00:18:54,080 Speaker 1: I am so excited to talk with you. It's been 336 00:18:54,200 --> 00:18:57,600 Speaker 1: way too long. You are always on the front lines 337 00:18:57,800 --> 00:19:00,000 Speaker 1: of trying to help people and trying to make change. 338 00:19:00,000 --> 00:19:03,679 Speaker 1: Ange and maybe you could just give our listeners a 339 00:19:03,720 --> 00:19:07,000 Speaker 1: little background of you know, how you ended up in 340 00:19:07,040 --> 00:19:10,280 Speaker 1: the United States, and uh, you know what your life 341 00:19:10,320 --> 00:19:13,560 Speaker 1: was like here. Yeah. I had a car accident when 342 00:19:13,560 --> 00:19:16,520 Speaker 1: I was two and a half and that resulted in 343 00:19:16,520 --> 00:19:19,119 Speaker 1: the amputation of my right leg. So for many years, 344 00:19:19,160 --> 00:19:22,840 Speaker 1: we actually did a lot of trips between Peru and 345 00:19:23,000 --> 00:19:25,960 Speaker 1: the States. And then my family decided to move here 346 00:19:26,000 --> 00:19:28,239 Speaker 1: when I was ten years old. And I grew up 347 00:19:28,240 --> 00:19:31,080 Speaker 1: in Connecticut, in New Melford, Connecticut. Of all the places 348 00:19:31,119 --> 00:19:34,639 Speaker 1: my parents could have picked, that was their choice, you know. 349 00:19:34,680 --> 00:19:37,400 Speaker 1: And then I got here and I was a young 350 00:19:37,640 --> 00:19:42,760 Speaker 1: brown girl with one leg um navigating the world in 351 00:19:42,800 --> 00:19:47,119 Speaker 1: a different language. And I then found out I was undocumented. 352 00:19:47,320 --> 00:19:49,880 Speaker 1: You know, it didn't come until later. So it's been 353 00:19:49,920 --> 00:19:52,840 Speaker 1: a lot of ups and downs, but I would say 354 00:19:52,880 --> 00:19:56,040 Speaker 1: all of my downs have come with a tremendous opportunity 355 00:19:56,119 --> 00:19:59,720 Speaker 1: to learn. Do you remember the moment when you learned 356 00:19:59,760 --> 00:20:04,439 Speaker 1: you were undocumented and what that meant to you? I 357 00:20:04,480 --> 00:20:08,000 Speaker 1: think it happened around your desire to apply for college, right, 358 00:20:10,359 --> 00:20:14,760 Speaker 1: I mean it was it was devastating. I actually think 359 00:20:14,960 --> 00:20:19,320 Speaker 1: I knew that I was undocumented long before I internalized 360 00:20:19,359 --> 00:20:22,199 Speaker 1: what that meant. And I had had many conversations with 361 00:20:22,240 --> 00:20:24,880 Speaker 1: my mother where I asked, you know, well, how come 362 00:20:24,960 --> 00:20:27,000 Speaker 1: I can't do this, or how come we can't do this? 363 00:20:27,720 --> 00:20:29,240 Speaker 1: And she would always say, oh, it's you know, you 364 00:20:29,240 --> 00:20:32,240 Speaker 1: can't get a driver's license because you can't drive because 365 00:20:32,640 --> 00:20:36,160 Speaker 1: of your leg I think really it was her way 366 00:20:36,160 --> 00:20:39,680 Speaker 1: of protecting me. And when I found out I was undocumented, 367 00:20:40,000 --> 00:20:43,280 Speaker 1: it was devastating. For that moment, and I would say 368 00:20:43,320 --> 00:20:46,800 Speaker 1: for the next several years, I carried a lot of shame. 369 00:20:47,280 --> 00:20:50,720 Speaker 1: I was really embarrassed and I was afraid. It was 370 00:20:50,760 --> 00:20:53,639 Speaker 1: almost as if I thought that I was walking around 371 00:20:54,080 --> 00:20:57,080 Speaker 1: and you know, I carried a label that said undocumented 372 00:20:57,119 --> 00:21:00,719 Speaker 1: on my forehead. And you know, I remember I was driving. 373 00:21:00,800 --> 00:21:05,200 Speaker 1: Anytime I drove and a police car showed up behind me, 374 00:21:05,320 --> 00:21:08,639 Speaker 1: I would just my whole body, would my whole this 375 00:21:08,720 --> 00:21:12,880 Speaker 1: whole state and physiology of my body would change. And 376 00:21:12,960 --> 00:21:16,199 Speaker 1: I would very nervously begin to think about when is 377 00:21:16,280 --> 00:21:18,440 Speaker 1: when is the earliest turn that I could make where 378 00:21:18,440 --> 00:21:21,600 Speaker 1: the police would not follow me? And what about becoming 379 00:21:21,640 --> 00:21:25,960 Speaker 1: a dreamer? Talk about you know, the movement, the dream act. 380 00:21:26,680 --> 00:21:30,080 Speaker 1: You know, I walked into a room at a field 381 00:21:30,080 --> 00:21:33,400 Speaker 1: planning meeting that United we Dream, the largest immigrant youth 382 00:21:33,440 --> 00:21:36,119 Speaker 1: let network where I spent a good really was my 383 00:21:36,160 --> 00:21:39,240 Speaker 1: first political home in this country. And a lot of 384 00:21:39,280 --> 00:21:42,800 Speaker 1: young people were wearing these shirts that said undocumented and unafraid, 385 00:21:42,880 --> 00:21:46,280 Speaker 1: and I was just looking at them, like, I don't 386 00:21:46,280 --> 00:21:49,520 Speaker 1: know what world you're living in. I am very much 387 00:21:49,560 --> 00:21:53,480 Speaker 1: undocumented and I am very afraid. And I learned there 388 00:21:53,560 --> 00:21:57,119 Speaker 1: that organizing is the art of the possible, and to 389 00:21:57,280 --> 00:22:00,439 Speaker 1: believe that, even though there were many people who have 390 00:22:00,480 --> 00:22:03,480 Speaker 1: been fighting on our behalf and telling our stories, that 391 00:22:03,560 --> 00:22:06,520 Speaker 1: if we wanted to change the laws in this country, 392 00:22:06,640 --> 00:22:10,280 Speaker 1: if we wanted to fight for citizenship for everyone, then 393 00:22:10,359 --> 00:22:13,160 Speaker 1: we had to step into our full power and our 394 00:22:13,160 --> 00:22:16,800 Speaker 1: full truth, reject the stories that had been told about us, 395 00:22:17,280 --> 00:22:20,440 Speaker 1: and begin to paint a different narrative. I know that 396 00:22:21,320 --> 00:22:25,280 Speaker 1: you know, you got married in you got your green card, 397 00:22:25,720 --> 00:22:30,080 Speaker 1: You were then among the group sworn in as American 398 00:22:30,200 --> 00:22:36,399 Speaker 1: citizens by President Obama in during this time that you 399 00:22:36,440 --> 00:22:39,880 Speaker 1: were undocumented, and now, of course as an American citizen, 400 00:22:40,400 --> 00:22:44,760 Speaker 1: how have you thought of yourself as an American and 401 00:22:44,800 --> 00:22:48,199 Speaker 1: how have you understood the American dream? How has it 402 00:22:48,320 --> 00:22:50,879 Speaker 1: how has it been defined for you? And buy you. 403 00:22:51,800 --> 00:22:55,440 Speaker 1: So to me, the most powerful part of the American 404 00:22:55,560 --> 00:22:59,359 Speaker 1: dream is the way that it challenges each one of 405 00:22:59,480 --> 00:23:03,800 Speaker 1: us to reshape and reimagine what our country can be. 406 00:23:04,680 --> 00:23:08,639 Speaker 1: And so, you know, I think being American is realizing 407 00:23:08,920 --> 00:23:13,960 Speaker 1: that the truth that this country holds might be self evident, 408 00:23:14,640 --> 00:23:17,800 Speaker 1: but they are not self executing. How do we look 409 00:23:17,800 --> 00:23:20,960 Speaker 1: at America every day and say I will not settle 410 00:23:21,000 --> 00:23:23,919 Speaker 1: for that because I know another world is possible. To me, 411 00:23:24,080 --> 00:23:27,199 Speaker 1: that is really the American dream. And the fact that 412 00:23:27,280 --> 00:23:29,359 Speaker 1: I get to do that as someone who was not 413 00:23:29,600 --> 00:23:33,560 Speaker 1: born here but who is committed to making all of 414 00:23:33,600 --> 00:23:37,439 Speaker 1: these things real, that maybe that is only possible in 415 00:23:37,480 --> 00:23:41,200 Speaker 1: a place like the United States. It's important to keep 416 00:23:41,240 --> 00:23:44,680 Speaker 1: the movement going, to keep the organizing going, to make 417 00:23:45,280 --> 00:23:49,359 Speaker 1: the case even if people get discouraged or disappointed, to 418 00:23:49,440 --> 00:23:51,600 Speaker 1: persuade them not to give up. So what are you 419 00:23:51,640 --> 00:23:56,920 Speaker 1: seeing out there? Oh man? Um? We are living through 420 00:23:57,000 --> 00:24:02,719 Speaker 1: a really hard period right now, nearly for intent Black 421 00:24:02,920 --> 00:24:08,280 Speaker 1: and Hispanic households right now with children are struggling to 422 00:24:08,359 --> 00:24:12,600 Speaker 1: feed their families, and so that is consuming people's minds 423 00:24:12,680 --> 00:24:16,119 Speaker 1: because parents are having to make very hard choices about 424 00:24:16,480 --> 00:24:19,120 Speaker 1: how to make sure that they can stay in their apartment, 425 00:24:19,280 --> 00:24:22,160 Speaker 1: how to make sure that they can feed their families, 426 00:24:22,359 --> 00:24:25,840 Speaker 1: And to me, all of these things are a policy choice. 427 00:24:26,200 --> 00:24:29,480 Speaker 1: Mass unemployment is a policy choice. Right food and security 428 00:24:29,520 --> 00:24:32,879 Speaker 1: is a policy choice. Mass evictions is a policy choice. 429 00:24:33,440 --> 00:24:36,800 Speaker 1: And so I think that people are living through and 430 00:24:36,840 --> 00:24:39,000 Speaker 1: we are going to continue to lift through this very 431 00:24:39,080 --> 00:24:42,440 Speaker 1: hard period. And I also feel like there's a tremendous 432 00:24:42,440 --> 00:24:46,280 Speaker 1: amount of hope. You have always epitomized that to me, 433 00:24:46,800 --> 00:24:51,000 Speaker 1: and you shared a story in the past about how 434 00:24:51,400 --> 00:24:53,679 Speaker 1: when you lost your leg in that accident when you 435 00:24:53,720 --> 00:24:56,560 Speaker 1: were a two year old, your parents told people not 436 00:24:56,640 --> 00:24:59,920 Speaker 1: to help you. My dad Yeah, um, your dad said, 437 00:25:00,400 --> 00:25:02,760 Speaker 1: you know no, she's going to stand up on her own. 438 00:25:03,240 --> 00:25:06,760 Speaker 1: She's going to get around on her own. And somehow 439 00:25:06,760 --> 00:25:10,679 Speaker 1: in my head I see this analogy because these days, 440 00:25:10,760 --> 00:25:15,439 Speaker 1: staying strong and telling people stay strong and keep going 441 00:25:15,800 --> 00:25:19,600 Speaker 1: and let's try to make a big change is quite 442 00:25:19,640 --> 00:25:23,440 Speaker 1: an ask. That Trump administration has done so much to 443 00:25:24,600 --> 00:25:30,480 Speaker 1: insult and undermine and demean immigrants, separating kids at the border, 444 00:25:31,080 --> 00:25:36,240 Speaker 1: restricting DOCCA, demonizing people list obviously goes on and on. 445 00:25:36,760 --> 00:25:41,199 Speaker 1: So how do you personally find the strength to get 446 00:25:41,200 --> 00:25:45,920 Speaker 1: back up every day? Keep going, keep fighting, and keep 447 00:25:46,040 --> 00:25:51,960 Speaker 1: using your extraordinary voice and example to convince others to 448 00:25:52,000 --> 00:25:55,120 Speaker 1: do that with you. I mean, part of me believes 449 00:25:55,160 --> 00:25:57,439 Speaker 1: that some of it was my father's training from when 450 00:25:57,480 --> 00:26:00,760 Speaker 1: I was very little, that the you you can do 451 00:26:00,800 --> 00:26:03,959 Speaker 1: this exercise every time I fell, and I felt a 452 00:26:04,040 --> 00:26:05,919 Speaker 1: lot when I was learning how to walk with a 453 00:26:05,920 --> 00:26:08,439 Speaker 1: prosthetic leg, when I was moving around with crutches when 454 00:26:08,440 --> 00:26:12,000 Speaker 1: I was little. I remember, in particular, a moment when 455 00:26:12,160 --> 00:26:15,800 Speaker 1: we were at maybe it was a carnival, and I 456 00:26:15,880 --> 00:26:19,119 Speaker 1: fell and one of my shoes also fell off, and 457 00:26:19,160 --> 00:26:20,880 Speaker 1: I was I was in a lot of pain, and 458 00:26:20,960 --> 00:26:23,719 Speaker 1: all of these people were rushing towards me, you know, 459 00:26:23,760 --> 00:26:25,679 Speaker 1: to help me up, and he just sort of he 460 00:26:25,720 --> 00:26:29,040 Speaker 1: had this motion, just sort of pushed people away just 461 00:26:29,080 --> 00:26:32,680 Speaker 1: by looking at them and moving his hand. And I 462 00:26:32,720 --> 00:26:35,960 Speaker 1: was angry. I was angry that he didn't help me up, 463 00:26:36,359 --> 00:26:39,040 Speaker 1: And you know, I think about it now and I'm 464 00:26:39,080 --> 00:26:42,680 Speaker 1: just grateful, you know, I think that it was lessons 465 00:26:42,840 --> 00:26:46,680 Speaker 1: learned for the future, and those lessons learned we're about 466 00:26:47,200 --> 00:26:50,280 Speaker 1: remembering that in life, we are going to fall, and 467 00:26:50,359 --> 00:26:52,359 Speaker 1: we're going to get up, and we're going to fall again, 468 00:26:52,440 --> 00:26:54,679 Speaker 1: and you're going to get up again. Um now we 469 00:26:54,920 --> 00:26:58,119 Speaker 1: we can make the getting up easier. And that's what 470 00:26:58,240 --> 00:27:02,120 Speaker 1: gives me hope. This believe that there's the world as 471 00:27:02,119 --> 00:27:03,840 Speaker 1: it should be, and then there was the world as 472 00:27:03,880 --> 00:27:07,760 Speaker 1: it is, and we as organizers, we as people, if 473 00:27:07,800 --> 00:27:11,920 Speaker 1: we vote, if we make our voices heard, we can 474 00:27:11,960 --> 00:27:15,199 Speaker 1: play a role in closing that gap, the gap that 475 00:27:15,280 --> 00:27:17,320 Speaker 1: exists between the world as it should be in the 476 00:27:17,320 --> 00:27:20,679 Speaker 1: world as it is, and in this time in particular, 477 00:27:20,800 --> 00:27:25,119 Speaker 1: because of all that the pandemic has exposed. My dream 478 00:27:25,280 --> 00:27:28,360 Speaker 1: is that we take the pain and the fear and 479 00:27:28,480 --> 00:27:32,200 Speaker 1: the anguish that so many people are feeling right now, 480 00:27:32,520 --> 00:27:36,199 Speaker 1: particularly in black, brown and immigrant communities, and that we 481 00:27:36,359 --> 00:27:39,840 Speaker 1: use that to create an America where people feel seen 482 00:27:40,000 --> 00:27:43,840 Speaker 1: and heard and where everyone can thrive. And if we 483 00:27:43,960 --> 00:27:47,920 Speaker 1: believe that that is possible, then we can fight to 484 00:27:48,200 --> 00:27:52,040 Speaker 1: overturn all these structural barriers that have been put in place, 485 00:27:52,440 --> 00:27:55,639 Speaker 1: and we could make it easier for people to stand 486 00:27:55,760 --> 00:27:58,840 Speaker 1: up after they fall, because that is a part of life. 487 00:27:59,320 --> 00:28:02,640 Speaker 1: I love that, Lorella. I am in your corner. I'm 488 00:28:02,640 --> 00:28:06,679 Speaker 1: one of your biggest fans and admirers, and uh, I 489 00:28:06,840 --> 00:28:10,360 Speaker 1: just can't wait to see what you do next. Keep 490 00:28:10,440 --> 00:28:14,920 Speaker 1: that energy, keep that optimism, keep that sense of hopefulness 491 00:28:14,960 --> 00:28:19,000 Speaker 1: in the face of setbacks, because it's contagious when people 492 00:28:19,040 --> 00:28:21,640 Speaker 1: see you do it and then they feel like I'm 493 00:28:21,640 --> 00:28:23,720 Speaker 1: going to do it too. So thank you, my friend, 494 00:28:23,720 --> 00:28:29,040 Speaker 1: Thank you for talking to me today. Thank you for 495 00:28:29,160 --> 00:28:34,280 Speaker 1: more information on the organization that Lorella leads, Community Change, 496 00:28:34,359 --> 00:28:37,920 Speaker 1: and the work they're doing on voter engagement, immigrant rights, 497 00:28:37,960 --> 00:28:46,360 Speaker 1: and affordable childcare. Please visit community change dot org. Tan 498 00:28:46,480 --> 00:28:49,680 Speaker 1: and Lorella each have their own American Dream success stories, 499 00:28:50,000 --> 00:28:53,320 Speaker 1: but at the same time, lots of Americans are struggling 500 00:28:53,440 --> 00:28:56,800 Speaker 1: just to get by. There's food insecurity, in other words, 501 00:28:56,800 --> 00:28:59,920 Speaker 1: people don't have enough food. The jobs that have been law, 502 00:29:00,240 --> 00:29:03,080 Speaker 1: many of them haven't come back and may not come back. 503 00:29:03,520 --> 00:29:07,400 Speaker 1: People have burned through their savings trying to keep themselves afloat. 504 00:29:07,800 --> 00:29:10,920 Speaker 1: You know, for many people, the American Dream has never 505 00:29:10,960 --> 00:29:14,320 Speaker 1: felt more out of reach. That's why I wanted to 506 00:29:14,360 --> 00:29:19,280 Speaker 1: talk with economists Roger Chetty. You know, he is the 507 00:29:19,440 --> 00:29:24,120 Speaker 1: expert on this issue. Last year, the Atlantic magazine ran 508 00:29:24,240 --> 00:29:28,240 Speaker 1: a profile of him called the Economist who Could Fix 509 00:29:28,440 --> 00:29:32,640 Speaker 1: the American Dream. Well, that caught my attention, So let's 510 00:29:32,640 --> 00:29:37,479 Speaker 1: get right to it. What do we mean, what do 511 00:29:37,560 --> 00:29:41,520 Speaker 1: you mean when we talk about the American dream? And 512 00:29:41,560 --> 00:29:46,160 Speaker 1: what about it needs fixing? Yeah, So, one way I 513 00:29:46,200 --> 00:29:49,240 Speaker 1: think about it just from a personal perspective, I was 514 00:29:49,280 --> 00:29:51,040 Speaker 1: a kid who grew up in India until I was 515 00:29:51,360 --> 00:29:54,560 Speaker 1: eight years old, uh came to the US at that point, 516 00:29:54,640 --> 00:29:58,760 Speaker 1: and the image many people have of America is it's 517 00:29:58,800 --> 00:30:01,560 Speaker 1: a place where, no matter what your background is, if 518 00:30:01,560 --> 00:30:04,440 Speaker 1: you work hard, you have a shot of making it 519 00:30:04,480 --> 00:30:07,800 Speaker 1: that there's kind of no ceiling, right, And to me, 520 00:30:08,000 --> 00:30:11,000 Speaker 1: that's at least one key aspect of the American dream. 521 00:30:11,040 --> 00:30:13,440 Speaker 1: And so I then think about how do you measure 522 00:30:13,480 --> 00:30:16,520 Speaker 1: that in the data? Are we living up to that aspiration? 523 00:30:16,560 --> 00:30:19,680 Speaker 1: Are we really a land of opportunity where anyone can 524 00:30:19,800 --> 00:30:22,840 Speaker 1: rise up? And one way people have thought about measuring 525 00:30:22,880 --> 00:30:27,000 Speaker 1: the concept historically is that America is a place where 526 00:30:27,360 --> 00:30:29,640 Speaker 1: most kids can expect to go on to have a 527 00:30:29,720 --> 00:30:33,400 Speaker 1: higher standard of living than their parents did. And so 528 00:30:33,720 --> 00:30:36,360 Speaker 1: we did a study a couple of years ago where 529 00:30:36,360 --> 00:30:39,800 Speaker 1: we tried to measure a very simple statistic, what fraction 530 00:30:39,840 --> 00:30:43,000 Speaker 1: of kids go on to earn more than their parents 531 00:30:43,040 --> 00:30:46,480 Speaker 1: did when we measure both kids incomes and their parents 532 00:30:46,560 --> 00:30:49,640 Speaker 1: incomes in their mid thirties around when they're forty years old. 533 00:30:50,280 --> 00:30:53,520 Speaker 1: And what we found, I think was a really disturbing 534 00:30:53,560 --> 00:30:56,360 Speaker 1: and worrisome pattern, which is back in the middle of 535 00:30:56,360 --> 00:30:58,440 Speaker 1: the last century. If you look at kids born, say 536 00:30:58,480 --> 00:31:02,840 Speaker 1: in the nineteen forties or nineteen fifties, of kids went 537 00:31:02,920 --> 00:31:05,080 Speaker 1: on to earn more than their parents did. But if 538 00:31:05,080 --> 00:31:07,880 Speaker 1: you look at what's happened over time, you see a 539 00:31:08,000 --> 00:31:10,600 Speaker 1: dramatic feeding of the American dream. We find that for 540 00:31:10,720 --> 00:31:14,160 Speaker 1: kids who are turning thirty today, there's only a fifty 541 00:31:14,240 --> 00:31:18,120 Speaker 1: fifty shot of earning more than your parents did. And 542 00:31:18,160 --> 00:31:21,360 Speaker 1: so it's that sort of trend that I think animates 543 00:31:21,960 --> 00:31:24,560 Speaker 1: my interest in figuring out how you can make America 544 00:31:24,760 --> 00:31:28,200 Speaker 1: land of opportunity once again. You were part of a 545 00:31:28,240 --> 00:31:32,120 Speaker 1: team that built something called an Opportunity Atlas. I just 546 00:31:32,440 --> 00:31:36,880 Speaker 1: love that title, which maps the level of opportunity in 547 00:31:36,920 --> 00:31:42,120 Speaker 1: our country literally down to neighborhoods. And part of what's 548 00:31:42,200 --> 00:31:47,280 Speaker 1: so remarkable about this Opportunity Atlas is that you can 549 00:31:47,360 --> 00:31:52,240 Speaker 1: see just a few streets separate areas where a kid 550 00:31:52,360 --> 00:31:55,640 Speaker 1: is likely to grow up and improve his or her 551 00:31:55,840 --> 00:32:02,280 Speaker 1: economic status from areas where a kid isn't. What makes 552 00:32:02,520 --> 00:32:09,600 Speaker 1: some neighborhoods economically mobile, creating more opportunity and other neighborhoods 553 00:32:09,680 --> 00:32:14,200 Speaker 1: less so, and maybe explain how you and your team 554 00:32:14,320 --> 00:32:19,760 Speaker 1: were able to aggregate the data that created this opportunity ATLAS, Yeah, 555 00:32:19,800 --> 00:32:23,040 Speaker 1: absolutely so. A lot of what we do is using 556 00:32:23,120 --> 00:32:26,440 Speaker 1: big data, and so in this case, we used anonymized 557 00:32:26,480 --> 00:32:30,680 Speaker 1: information from Census and Social Security and tax data. Information 558 00:32:30,720 --> 00:32:34,280 Speaker 1: the government has to be essentially mapped the lives of 559 00:32:34,360 --> 00:32:38,960 Speaker 1: millions of kids, tracing their outcomes in adulthood, their levels 560 00:32:39,000 --> 00:32:43,360 Speaker 1: of income, college attendance rates, teenage birth rates, things like that, 561 00:32:43,960 --> 00:32:47,280 Speaker 1: back to the neighborhoods in which they grew up. And specifically, 562 00:32:47,320 --> 00:32:49,719 Speaker 1: what we were able to do analyzing data for twenty 563 00:32:49,720 --> 00:32:54,280 Speaker 1: million families is compare kids who grew up in families 564 00:32:54,320 --> 00:32:57,320 Speaker 1: at the same income level, and what we calculate is 565 00:32:57,880 --> 00:33:00,360 Speaker 1: what are the odds of rising up for the kids, 566 00:33:00,360 --> 00:33:02,280 Speaker 1: What are the chances they reached the middle class? What 567 00:33:02,320 --> 00:33:05,480 Speaker 1: are the chances they earn you know, more than eighty 568 00:33:05,480 --> 00:33:08,480 Speaker 1: thousand or hundred thousand dollars a year in adulthood? And so, 569 00:33:08,640 --> 00:33:13,320 Speaker 1: as you noted, you find incredibly large differences across nearby 570 00:33:13,320 --> 00:33:18,280 Speaker 1: neighborhoods and that from a social science perspective, is first 571 00:33:18,280 --> 00:33:21,160 Speaker 1: of all, useful to note in its own right, because 572 00:33:21,360 --> 00:33:23,720 Speaker 1: there's a great deal of effort in the federal government 573 00:33:23,760 --> 00:33:27,160 Speaker 1: to try to reduce segregation and help families move to 574 00:33:27,240 --> 00:33:30,160 Speaker 1: higher opportunity areas, and this kind of data can be 575 00:33:30,240 --> 00:33:32,960 Speaker 1: really useful for supporting that sort of work. But it 576 00:33:33,000 --> 00:33:36,720 Speaker 1: can also be useful to your question in understanding what 577 00:33:36,960 --> 00:33:41,240 Speaker 1: is it that makes opportunity more available in some neighborhoods 578 00:33:41,280 --> 00:33:43,360 Speaker 1: relative to others. And we've looked at a variety of 579 00:33:43,360 --> 00:33:47,360 Speaker 1: different factors and basically distill it to three or four 580 00:33:47,440 --> 00:33:50,959 Speaker 1: things that seem like systematic strong patterns. So the first 581 00:33:51,560 --> 00:33:55,200 Speaker 1: is that more mixed income areas tend to have higher 582 00:33:55,320 --> 00:34:00,600 Speaker 1: levels of upward mobility. Uh second major factor is the 583 00:34:00,760 --> 00:34:04,840 Speaker 1: availability of social capital. So social capital is kind of 584 00:34:04,880 --> 00:34:08,440 Speaker 1: a complicated concept that is a bit hard to define 585 00:34:08,440 --> 00:34:10,600 Speaker 1: that the way I think about it is just will 586 00:34:10,680 --> 00:34:13,359 Speaker 1: someone else in your community help you out even if 587 00:34:13,360 --> 00:34:17,200 Speaker 1: you're not doing well. So as an example, people often 588 00:34:17,200 --> 00:34:19,640 Speaker 1: talk about Salt Lake City with the Mormon Church as 589 00:34:19,680 --> 00:34:22,480 Speaker 1: an example of a place with a lot of social capital, 590 00:34:22,800 --> 00:34:24,840 Speaker 1: And in our data, Salt Lake City looks like a 591 00:34:24,840 --> 00:34:28,919 Speaker 1: place where low income kids have great chances of rising up. 592 00:34:28,960 --> 00:34:32,080 Speaker 1: A third very important factor, which is intuitive, is the 593 00:34:32,160 --> 00:34:34,920 Speaker 1: quality of public schools in an area. And then a 594 00:34:35,000 --> 00:34:38,080 Speaker 1: fourth factor, which i'll mention, illustrates. I think the complexity 595 00:34:38,080 --> 00:34:42,160 Speaker 1: of the issues is there's a very strong correlation between 596 00:34:42,239 --> 00:34:46,120 Speaker 1: rates of upward mobility and measures of family structure. So 597 00:34:46,320 --> 00:34:49,879 Speaker 1: areas with more two parent families tend to have higher 598 00:34:49,920 --> 00:34:53,120 Speaker 1: rates of upward mobility. But in understanding this, it's very 599 00:34:53,120 --> 00:34:56,879 Speaker 1: important to note that it's not literally about whether your 600 00:34:56,960 --> 00:35:00,479 Speaker 1: own parents are married or not. Even if your own 601 00:35:00,600 --> 00:35:03,920 Speaker 1: parents are married, kids who grow up in areas with 602 00:35:03,960 --> 00:35:06,839 Speaker 1: a larger share of single parents tend to be less 603 00:35:06,880 --> 00:35:09,960 Speaker 1: likely to climb the income letter. And so the reason 604 00:35:10,040 --> 00:35:13,360 Speaker 1: I provide that additional nuances it shows you that the 605 00:35:13,440 --> 00:35:15,839 Speaker 1: mechanism is not maybe the first thing lots of people 606 00:35:15,840 --> 00:35:19,040 Speaker 1: would think of that it your own parents marital structure 607 00:35:19,080 --> 00:35:22,680 Speaker 1: is the critical thing. It's again something about the community 608 00:35:22,760 --> 00:35:27,480 Speaker 1: that's getting picked up. There. We'll be right back. You know, 609 00:35:27,960 --> 00:35:31,920 Speaker 1: we're in the midst of this nationwide pandemic health crisis. 610 00:35:32,040 --> 00:35:37,279 Speaker 1: It's revealed again more inequities and our health care systems, 611 00:35:37,360 --> 00:35:41,239 Speaker 1: the job markets, and even education. What do you think 612 00:35:41,320 --> 00:35:46,480 Speaker 1: the long term effects of COVID will be on social mobility, 613 00:35:46,600 --> 00:35:50,880 Speaker 1: especially on the communities that you've been studying that don't 614 00:35:50,920 --> 00:35:55,160 Speaker 1: have a lot of opportunity to spare. So in our team, 615 00:35:55,239 --> 00:35:57,719 Speaker 1: the way we've been thinking about COVID, everyone I think 616 00:35:57,800 --> 00:36:00,520 Speaker 1: is within how can they contribute to this crisis? And 617 00:36:00,560 --> 00:36:03,880 Speaker 1: so our thought was, can we use the big data 618 00:36:03,920 --> 00:36:07,640 Speaker 1: approach again to measure the impacts of COVID more rapidly, 619 00:36:07,719 --> 00:36:10,360 Speaker 1: in a very precise way. How is it affecting different 620 00:36:10,360 --> 00:36:13,799 Speaker 1: people and businesses in America? And in this case, we 621 00:36:13,880 --> 00:36:15,960 Speaker 1: found that the best approach was not to turn the 622 00:36:16,000 --> 00:36:20,239 Speaker 1: government data, but actually to data from private companies which 623 00:36:20,280 --> 00:36:24,240 Speaker 1: have the best real time information on what is happening 624 00:36:24,239 --> 00:36:26,440 Speaker 1: in our economies. Let me give you an example. If 625 00:36:26,480 --> 00:36:28,960 Speaker 1: you want to see what is happening to consumer spending 626 00:36:28,960 --> 00:36:33,200 Speaker 1: in America, get data from companies that process credit and 627 00:36:33,239 --> 00:36:37,080 Speaker 1: debit card transactions. So you swipe your credit card, We 628 00:36:37,200 --> 00:36:40,719 Speaker 1: collect all of that information and anonymized way, and three 629 00:36:40,840 --> 00:36:43,120 Speaker 1: or four days later we have a sense of what 630 00:36:43,280 --> 00:36:46,279 Speaker 1: is happening to spending in America. And that is incredibly 631 00:36:46,320 --> 00:36:49,320 Speaker 1: valuable because when you look at the sort of data 632 00:36:49,760 --> 00:36:52,719 Speaker 1: you can see the effects of various policy changes. So, 633 00:36:52,760 --> 00:36:56,799 Speaker 1: for instance, when the stimulus checks went out literally on 634 00:36:56,960 --> 00:37:00,799 Speaker 1: April sixteen, relative to April fourteen, you see a huge 635 00:37:00,880 --> 00:37:04,160 Speaker 1: uptick in spending, especially for low income folks who were 636 00:37:04,160 --> 00:37:07,719 Speaker 1: really strapped for cash. Right. And so with that sort 637 00:37:07,760 --> 00:37:10,760 Speaker 1: of real time data from private companies of various types, 638 00:37:11,160 --> 00:37:14,000 Speaker 1: we have been studying what is happening to economic outcomes 639 00:37:14,000 --> 00:37:17,840 Speaker 1: and economic opportunity in the COVID crisis, And so, you know, 640 00:37:17,840 --> 00:37:19,480 Speaker 1: there are lots of issues in the short run, how 641 00:37:19,480 --> 00:37:22,239 Speaker 1: do we get Americans back to work, and what is 642 00:37:22,239 --> 00:37:24,560 Speaker 1: happening to businesses and so forth. And I'm happy to 643 00:37:24,560 --> 00:37:26,560 Speaker 1: talk about that, but I want to tie this back 644 00:37:26,560 --> 00:37:29,280 Speaker 1: to the longer term kind of conversation we've been having 645 00:37:29,320 --> 00:37:33,319 Speaker 1: on economic opportunity, and I want to share one piece 646 00:37:33,320 --> 00:37:36,600 Speaker 1: of data that to me is very alarming. So we've 647 00:37:36,600 --> 00:37:41,880 Speaker 1: been tracking data on an online math learning platform called zern, 648 00:37:42,080 --> 00:37:45,000 Speaker 1: which about a million students in the US use in 649 00:37:45,080 --> 00:37:49,160 Speaker 1: their schools to do math lessons. And we basically look 650 00:37:49,200 --> 00:37:53,120 Speaker 1: at what happened when schools shut down to progress on 651 00:37:53,160 --> 00:37:55,560 Speaker 1: this platform. And what we find is that for kids 652 00:37:55,560 --> 00:37:59,800 Speaker 1: in high income families when schools went to remote instruction, 653 00:38:00,120 --> 00:38:02,640 Speaker 1: there was a temporary debt in the amount of progress 654 00:38:02,640 --> 00:38:05,520 Speaker 1: they were making, but they very quickly rebounded back to 655 00:38:05,560 --> 00:38:07,600 Speaker 1: the levels that they were at when they were in school. 656 00:38:08,239 --> 00:38:11,280 Speaker 1: For kids in low income families, you see a sixty 657 00:38:11,360 --> 00:38:14,560 Speaker 1: percent drop off in terms of the progress they're making 658 00:38:14,560 --> 00:38:18,319 Speaker 1: in math, and there's absolutely no recovery basically, and that 659 00:38:18,400 --> 00:38:22,000 Speaker 1: I think is incredibly alarming for all of the reasons 660 00:38:22,000 --> 00:38:24,239 Speaker 1: that we've been talking about earlier in the conversation, which 661 00:38:24,280 --> 00:38:29,439 Speaker 1: is these early childhood formational years are incredibly important, uh 662 00:38:29,480 --> 00:38:33,239 Speaker 1: in determining kids long term outcomes. And my worry is 663 00:38:33,239 --> 00:38:36,080 Speaker 1: the COVID crisis is bring to the forefront many of 664 00:38:36,080 --> 00:38:38,680 Speaker 1: the inequalities that I think have been a little bit 665 00:38:38,760 --> 00:38:42,280 Speaker 1: hidden to many Americans at least, And in a sense, 666 00:38:42,600 --> 00:38:44,600 Speaker 1: we're going to be seeing the impacts of this crisis 667 00:38:44,600 --> 00:38:48,520 Speaker 1: if we don't respond appropriately, not just in the coming months, 668 00:38:48,520 --> 00:38:52,399 Speaker 1: but ten twenty years from now, because of these impacts. Well, 669 00:38:52,440 --> 00:38:55,840 Speaker 1: I mean, one of the findings that you have shown 670 00:38:56,200 --> 00:38:59,799 Speaker 1: is that you know, a really great kindergarten teacher can 671 00:39:00,040 --> 00:39:05,880 Speaker 1: underrate hundreds of thousands of dollars in future earnings for students. 672 00:39:05,880 --> 00:39:08,879 Speaker 1: But because of COVID, kids are not in school, or 673 00:39:08,920 --> 00:39:12,160 Speaker 1: if they are, it's kind of a sporadic you know, 674 00:39:12,320 --> 00:39:16,640 Speaker 1: we're in, we're out. And it's absolutely clear, as you 675 00:39:16,800 --> 00:39:20,560 Speaker 1: pointed out, how this is going to have long term 676 00:39:20,680 --> 00:39:25,680 Speaker 1: impacts on low income kids. It will probably creep up 677 00:39:25,719 --> 00:39:29,359 Speaker 1: the income ladder somewhat more than you might find at 678 00:39:29,360 --> 00:39:34,080 Speaker 1: other times because families aren't able to get back to work, namely, 679 00:39:34,360 --> 00:39:36,319 Speaker 1: mothers are not able to get back to work, so 680 00:39:36,360 --> 00:39:39,920 Speaker 1: the standard of living drops, plus the education is not 681 00:39:40,239 --> 00:39:43,600 Speaker 1: proceeding the way it needs to be. I agree with 682 00:39:43,640 --> 00:39:46,640 Speaker 1: you that we we have a lot of long term 683 00:39:46,680 --> 00:39:49,200 Speaker 1: problems we're going to have to unpack and then try 684 00:39:49,239 --> 00:39:52,280 Speaker 1: to address. But but let me wrap up by asking 685 00:39:52,360 --> 00:39:56,600 Speaker 1: you this. I'm hoping for a change in the November 686 00:39:56,680 --> 00:40:00,800 Speaker 1: election where we might actually get back to making policy 687 00:40:00,880 --> 00:40:04,359 Speaker 1: based on evidence and data and facts and reason and 688 00:40:05,000 --> 00:40:08,400 Speaker 1: lots of uh, you know, challenges to that in the 689 00:40:08,440 --> 00:40:12,440 Speaker 1: current administration, but we're going to have to really have 690 00:40:12,719 --> 00:40:17,080 Speaker 1: an organized effort to move quickly. So, if you were 691 00:40:17,200 --> 00:40:23,239 Speaker 1: asked by an incoming administration, Okay, what are the three things, 692 00:40:23,360 --> 00:40:26,480 Speaker 1: professor Chetty that we need to do as soon as 693 00:40:26,480 --> 00:40:30,520 Speaker 1: we can to try to make up for you know, 694 00:40:30,640 --> 00:40:37,560 Speaker 1: not just historic inequity, but the incredibly damaging impact of COVID. 695 00:40:37,960 --> 00:40:43,120 Speaker 1: What would be your three most important policy suggestions. Yeah, 696 00:40:43,239 --> 00:40:45,799 Speaker 1: so we need to have a solid based in the 697 00:40:45,840 --> 00:40:49,200 Speaker 1: short run to be able to build towards long term solutions. 698 00:40:49,239 --> 00:40:52,360 Speaker 1: And so the first set of policy efforts that I 699 00:40:52,360 --> 00:40:56,840 Speaker 1: would focus on our short term, targeted supports to the 700 00:40:56,960 --> 00:41:00,040 Speaker 1: people and the places that have been hard as to 701 00:41:00,120 --> 00:41:04,120 Speaker 1: by this crisis to help restore employment at kind of 702 00:41:04,120 --> 00:41:08,600 Speaker 1: a basic level. I would then push towards trying to 703 00:41:08,640 --> 00:41:11,520 Speaker 1: address what I see as the structural factors that are 704 00:41:11,600 --> 00:41:15,480 Speaker 1: leading to the inequalities that are becoming apparent in this crisis. So, 705 00:41:15,520 --> 00:41:18,719 Speaker 1: I think one response to what we're seeing in terms 706 00:41:18,760 --> 00:41:20,960 Speaker 1: of the educational inequity that we just talked about in 707 00:41:21,000 --> 00:41:23,920 Speaker 1: the COVID crisis is, oh, that just happened in the 708 00:41:23,920 --> 00:41:26,160 Speaker 1: context of COVID. We need to fix that now, but 709 00:41:26,239 --> 00:41:28,640 Speaker 1: then things are going to be fine afterwards. I think 710 00:41:28,640 --> 00:41:30,400 Speaker 1: that's the wrong way to look at it. It's actually 711 00:41:31,080 --> 00:41:35,040 Speaker 1: a you're seeing at the surface a much deeper problem 712 00:41:35,120 --> 00:41:38,000 Speaker 1: that's been around for many, many years, and I think 713 00:41:38,040 --> 00:41:41,440 Speaker 1: what we should do is use this as an opportunity 714 00:41:41,560 --> 00:41:44,560 Speaker 1: to do something that will be much more trans transformational. 715 00:41:44,960 --> 00:41:48,040 Speaker 1: So you know, my one positive hope coming out of 716 00:41:48,040 --> 00:41:50,920 Speaker 1: the COVID crisis is in the same way that the 717 00:41:50,960 --> 00:41:54,960 Speaker 1: Great Depression, I think was an incredible shock to the country, 718 00:41:55,000 --> 00:41:58,040 Speaker 1: it also led to I think a transformative set of 719 00:41:58,040 --> 00:42:01,320 Speaker 1: policies that paved the way for an incredible amount of 720 00:42:01,360 --> 00:42:04,759 Speaker 1: inclusive growth in America over the next many decades. And 721 00:42:04,800 --> 00:42:06,800 Speaker 1: I think this is the moment to try to seize 722 00:42:06,840 --> 00:42:10,080 Speaker 1: the opportunity and make a similar effort. And so what 723 00:42:10,239 --> 00:42:15,040 Speaker 1: does that then involve? Reducing segregation in America? So that 724 00:42:15,080 --> 00:42:17,520 Speaker 1: can be through affordable housing policy, it can be through 725 00:42:18,040 --> 00:42:20,879 Speaker 1: zoning changes, the way we collect taxes, and so forth. 726 00:42:20,920 --> 00:42:23,719 Speaker 1: Their number of specifics, but I think that is one 727 00:42:24,160 --> 00:42:27,360 Speaker 1: major area to focus on. Another major area to focus on, 728 00:42:27,400 --> 00:42:31,560 Speaker 1: given that opportunity seems to emerge so locally, is place 729 00:42:31,640 --> 00:42:35,759 Speaker 1: based investments. So traditionally when people talk about place based investments, 730 00:42:35,800 --> 00:42:39,480 Speaker 1: it's often things like tax credits for businesses or things 731 00:42:39,560 --> 00:42:43,200 Speaker 1: focused on the labor market. But as we've been discussing, 732 00:42:43,600 --> 00:42:47,400 Speaker 1: the foundations I think are really in the context of childhood. 733 00:42:47,880 --> 00:42:50,040 Speaker 1: And so when I think about place based efforts, it's 734 00:42:50,040 --> 00:42:55,000 Speaker 1: about how do you provide in specific communities, better schools, 735 00:42:55,080 --> 00:42:58,200 Speaker 1: more social capital, and importantly do it in a way 736 00:42:58,320 --> 00:43:01,680 Speaker 1: that doesn't just end up raising house prices and creating 737 00:43:01,719 --> 00:43:04,680 Speaker 1: gentrification such that the people you were trying to help 738 00:43:05,120 --> 00:43:07,200 Speaker 1: end up having to move out. So I think that's 739 00:43:07,200 --> 00:43:10,839 Speaker 1: a second major area of focus. And then third, uh 740 00:43:10,960 --> 00:43:16,120 Speaker 1: the universities that provide important pathways to opportunity for many folks. 741 00:43:17,200 --> 00:43:20,439 Speaker 1: There's I think another crisis in America playing out there 742 00:43:20,560 --> 00:43:24,000 Speaker 1: where there are many colleges that produce good outcomes for 743 00:43:24,120 --> 00:43:27,759 Speaker 1: kids but are inaccessible to kids from lower income backgrounds, 744 00:43:27,760 --> 00:43:30,560 Speaker 1: either because they can't afford it, or because those colleges 745 00:43:30,600 --> 00:43:33,759 Speaker 1: for various reasons, are not admitting as many kids from 746 00:43:33,760 --> 00:43:37,680 Speaker 1: low income backgrounds. And so I think a push towards 747 00:43:38,320 --> 00:43:42,800 Speaker 1: essentially making your contribution to social mobility a key factor 748 00:43:42,920 --> 00:43:45,960 Speaker 1: that determines how a college is regarded, perhaps even how 749 00:43:46,000 --> 00:43:50,880 Speaker 1: much funding federal funding college gets. I think is is 750 00:43:50,920 --> 00:43:54,279 Speaker 1: another important area for focus. So, you know, just to 751 00:43:54,400 --> 00:43:57,080 Speaker 1: provide some perspective that those may seem like things that 752 00:43:57,120 --> 00:44:00,919 Speaker 1: are not directly about COVID, but I think that longer 753 00:44:01,040 --> 00:44:06,320 Speaker 1: term perspective is incredibly important combined with short run solutions. Well, 754 00:44:06,440 --> 00:44:10,359 Speaker 1: I agree completely and that longer term perspective combined with 755 00:44:10,440 --> 00:44:12,839 Speaker 1: the short term solutions, is one of the ways I 756 00:44:12,920 --> 00:44:17,000 Speaker 1: hope that we can work together as a nation to 757 00:44:17,080 --> 00:44:22,080 Speaker 1: revitalize the American Dream. And if we lose the idea 758 00:44:22,280 --> 00:44:25,520 Speaker 1: and the reality of the American dream, we really do 759 00:44:25,760 --> 00:44:29,880 Speaker 1: see a continuing fraying of our social fabric in ways 760 00:44:29,960 --> 00:44:33,680 Speaker 1: that I know distress you and certainly distress me. So 761 00:44:34,160 --> 00:44:38,480 Speaker 1: thank you, rog Please keep up your extraordinary commitment to 762 00:44:39,480 --> 00:44:44,319 Speaker 1: helping us understand how we can actually improve opportunity in 763 00:44:44,360 --> 00:44:47,960 Speaker 1: America for many, many more Americans. Thank you so much, 764 00:44:48,640 --> 00:44:52,839 Speaker 1: my pleasure. You can learn more about Roger's projects and 765 00:44:52,920 --> 00:44:58,000 Speaker 1: find lots of cool maps and data visualization at Opportunity 766 00:44:58,080 --> 00:45:03,560 Speaker 1: Insights dot org. Well that's it for this week's show. 767 00:45:04,000 --> 00:45:07,080 Speaker 1: You and Me Both is brought to you by iHeart Radio. 768 00:45:07,640 --> 00:45:12,040 Speaker 1: We're produced by Julie Supran and Kathleen Russo, with help 769 00:45:12,120 --> 00:45:17,759 Speaker 1: from Whoma Aberdeen, Nikki e Tour, Oscar Flores, Brianna Johnson, 770 00:45:18,040 --> 00:45:23,439 Speaker 1: Nick Merrill, Lauren Peterson, Rob Russo and Lona Valmorrow. Our 771 00:45:23,600 --> 00:45:28,239 Speaker 1: engineer is Zack McNeice and the original music is by 772 00:45:28,480 --> 00:45:33,799 Speaker 1: Forest Gray. Our podcast is recorded on the riverside platform, 773 00:45:33,880 --> 00:45:36,959 Speaker 1: and a big thanks to the Riverside team for they're 774 00:45:37,000 --> 00:45:41,360 Speaker 1: helping make a podcast during a pandemic. If you like 775 00:45:41,480 --> 00:45:44,239 Speaker 1: this episode, how about telling someone else about it or 776 00:45:44,280 --> 00:45:47,520 Speaker 1: tweet about it or posted on Instagram. That would be 777 00:45:47,560 --> 00:45:50,239 Speaker 1: a big help in getting the word out. And you 778 00:45:50,280 --> 00:45:52,640 Speaker 1: can subscribe to You and Me both on the I 779 00:45:52,800 --> 00:45:57,400 Speaker 1: Heart Radio app, Apple Podcast or wherever you get your podcasts. 780 00:45:57,560 --> 00:46:01,000 Speaker 1: And while you're there, please leave us a review. We'd 781 00:46:01,040 --> 00:46:04,440 Speaker 1: love to hear from you. Send us your questions, your comments, 782 00:46:04,560 --> 00:46:07,560 Speaker 1: or your best fashion advice. Do You and Me both 783 00:46:07,719 --> 00:46:12,200 Speaker 1: pod at gmail dot com. Come back next week when 784 00:46:12,239 --> 00:46:14,680 Speaker 1: we're going to hold your hand and help you get 785 00:46:14,719 --> 00:46:18,520 Speaker 1: through this election day. Along with my special co host 786 00:46:18,840 --> 00:46:25,160 Speaker 1: America Ferrara, the Unbelievable Glennon Doyle, The Dynamics Orlina Maxwell, 787 00:46:25,360 --> 00:46:28,160 Speaker 1: and more, Let's win this thing together.