1 00:00:00,680 --> 00:00:04,800 Speaker 1: I absolutely know that issues exist, and they are cultural 2 00:00:04,920 --> 00:00:08,479 Speaker 1: and they are baked into society, but that doesn't mean 3 00:00:08,520 --> 00:00:12,000 Speaker 1: we don't have an obligation to try. That's what I'm doing, 4 00:00:12,119 --> 00:00:13,960 Speaker 1: That's what we all have to do, and we have 5 00:00:14,000 --> 00:00:14,720 Speaker 1: to do it together. 6 00:00:19,320 --> 00:00:23,720 Speaker 2: From Fudromidia and BrX, It's Latino USA. I'm Marieno Rosa 7 00:00:24,320 --> 00:00:28,200 Speaker 2: today a conversation with Robert Santos, the first Latino to 8 00:00:28,320 --> 00:00:38,440 Speaker 2: lead the US Census Bureau. President Joe Biden announced last 9 00:00:38,479 --> 00:00:42,040 Speaker 2: April that his intended nominee to lead the US Census 10 00:00:42,320 --> 00:00:45,760 Speaker 2: would be Robert Santos. Then just a few weeks later, 11 00:00:45,840 --> 00:00:49,360 Speaker 2: Santos went before the Senate Homeland Security Committee for his 12 00:00:49,440 --> 00:00:50,400 Speaker 2: confirmation hearing. 13 00:00:50,800 --> 00:00:54,080 Speaker 1: It's an honor and I'm humbled to appear before you 14 00:00:54,120 --> 00:00:57,760 Speaker 1: today as the nominee for the Director of the Census Bureau. 15 00:00:58,520 --> 00:01:01,560 Speaker 1: I'd like to thank the President and Secretary Rimando for 16 00:01:01,600 --> 00:01:04,360 Speaker 1: the trust they have placed in me with this nomination. 17 00:01:04,959 --> 00:01:08,800 Speaker 2: Santos is super proud about being born and raised in 18 00:01:08,880 --> 00:01:13,080 Speaker 2: the barrios of San Antonio, Texas. He has served as 19 00:01:13,240 --> 00:01:18,839 Speaker 2: President of the American Statistical Association, vice President and chief 20 00:01:19,000 --> 00:01:23,160 Speaker 2: methodologist at the Urban Institute, along with other big roles 21 00:01:23,240 --> 00:01:27,000 Speaker 2: throughout his career. Santos has more than forty years of 22 00:01:27,040 --> 00:01:31,800 Speaker 2: experience in survey research and he specializes in quantitative and 23 00:01:31,920 --> 00:01:33,679 Speaker 2: qualitative research design. 24 00:01:34,240 --> 00:01:37,360 Speaker 1: I wouldn't be here today without the enduring support of 25 00:01:37,400 --> 00:01:41,880 Speaker 1: my family. At age eighteen, I married my wife, Adela, 26 00:01:41,959 --> 00:01:45,039 Speaker 1: and we've now been married forty eight years. She's my 27 00:01:45,120 --> 00:01:50,080 Speaker 1: most important source of support, counsel and love. Our two children, 28 00:01:50,240 --> 00:01:54,720 Speaker 1: Emilio and Clarissa, always support me and are constant sources 29 00:01:54,760 --> 00:01:56,080 Speaker 1: of comfort and pride. 30 00:01:56,600 --> 00:02:00,640 Speaker 2: During his confirmation hearing, Santos was asked about redistrict along 31 00:02:00,680 --> 00:02:04,840 Speaker 2: with potential big challenges for the upcoming twenty thirty Census. 32 00:02:05,840 --> 00:02:09,160 Speaker 2: Santos was confirmed in November of twenty twenty one. A 33 00:02:09,200 --> 00:02:12,280 Speaker 2: few months later and January of this year, he was 34 00:02:12,320 --> 00:02:16,000 Speaker 2: sworn in as the twenty sixth director of the US Census, 35 00:02:16,320 --> 00:02:19,720 Speaker 2: and he is the first Latino to hold that position. 36 00:02:20,160 --> 00:02:24,639 Speaker 3: Hi Robert Santos, I Robert Sambo, will support in the 37 00:02:25,360 --> 00:02:26,640 Speaker 3: will support in thefan. 38 00:02:27,240 --> 00:02:30,720 Speaker 2: Santos is no stranger to the US Census. Before his 39 00:02:30,800 --> 00:02:34,640 Speaker 2: nomination and confirmation, he warned in October of twenty twenty 40 00:02:35,160 --> 00:02:40,000 Speaker 2: that former President Trump's interference with the census count could 41 00:02:40,080 --> 00:02:45,480 Speaker 2: result in one of the most flawed census counts in history. 42 00:02:45,800 --> 00:02:49,680 Speaker 2: Census counts are important because they helped determine the number 43 00:02:49,720 --> 00:02:53,200 Speaker 2: of seats each state has in the US House of Representatives. 44 00:02:53,600 --> 00:02:57,040 Speaker 2: It's also used to help allocate and distribute billions of 45 00:02:57,120 --> 00:03:02,560 Speaker 2: federal dollars across local communities throughout the entire country. Trump 46 00:03:02,600 --> 00:03:05,160 Speaker 2: wanted a question on the past census that asked for 47 00:03:05,240 --> 00:03:08,680 Speaker 2: people's US citizenship status. 48 00:03:08,720 --> 00:03:10,240 Speaker 4: Well, you need it for many reasons. 49 00:03:10,360 --> 00:03:13,639 Speaker 3: Number One, you needed with Congress, you needed for Congress, 50 00:03:13,680 --> 00:03:18,440 Speaker 3: for despriting, you needed for appropriations. Citizenship has been on 51 00:03:18,520 --> 00:03:21,079 Speaker 3: that thing most of the time for many, many years. 52 00:03:21,760 --> 00:03:25,880 Speaker 2: A citizenship question had not been on the census for 53 00:03:26,000 --> 00:03:30,960 Speaker 2: several decades, and of course, citizenship status is not used 54 00:03:31,040 --> 00:03:37,000 Speaker 2: for redistricting. And after several lawsuits, the Supreme Court ultimately 55 00:03:37,160 --> 00:03:42,000 Speaker 2: blocked the citizenship question from being on the twenty twenty census, 56 00:03:42,040 --> 00:03:45,000 Speaker 2: but the damage had already been done and there was 57 00:03:45,040 --> 00:03:48,960 Speaker 2: an even further gap in trust with communities across the 58 00:03:49,080 --> 00:03:54,800 Speaker 2: United States. The weaponization of the US census isn't something new. 59 00:03:57,200 --> 00:03:59,960 Speaker 2: We've seen it with the founding of this country, when 60 00:04:00,160 --> 00:04:04,560 Speaker 2: enslaved Africans were counted as three fifths of a person 61 00:04:04,920 --> 00:04:08,920 Speaker 2: and later when Japanese Americans were in prison and tracked 62 00:04:08,960 --> 00:04:14,600 Speaker 2: down by using the senses. So on today's episode, I 63 00:04:14,680 --> 00:04:19,000 Speaker 2: have a conversation with director Robert Santos about his new role, 64 00:04:19,400 --> 00:04:22,640 Speaker 2: his love for his hometown of San Antonio, and the 65 00:04:22,760 --> 00:04:32,120 Speaker 2: complicated history of the US Censes. Director Robert Santos, Hello, 66 00:04:32,360 --> 00:04:34,080 Speaker 2: and thank you so much for being with me here 67 00:04:34,120 --> 00:04:35,360 Speaker 2: today on Latino USA. 68 00:04:35,800 --> 00:04:38,640 Speaker 1: I was ready to climb a ladder and do the 69 00:04:38,640 --> 00:04:41,440 Speaker 1: interview upside down if I could have the opportunity to 70 00:04:41,480 --> 00:04:44,400 Speaker 1: be a part of this experience with you, because I've 71 00:04:44,440 --> 00:04:48,120 Speaker 1: always valued everything that you've done on your program. 72 00:04:48,160 --> 00:04:50,640 Speaker 2: Oh my gosh, well, thank you. I don't I am 73 00:04:50,640 --> 00:04:52,760 Speaker 2: actually I'm having a moment. Did the director of the 74 00:04:52,880 --> 00:04:57,120 Speaker 2: US Census just say to me that he values the 75 00:04:57,160 --> 00:05:00,400 Speaker 2: work that I've been doing and knows my work? I 76 00:05:00,480 --> 00:05:01,599 Speaker 2: really am having a moment. 77 00:05:01,960 --> 00:05:05,520 Speaker 1: Every week we listen to your program and the job 78 00:05:05,560 --> 00:05:09,360 Speaker 1: you're doing to help the United States understand the value 79 00:05:09,560 --> 00:05:13,680 Speaker 1: of our rich diversity of Latinos, I think is amazing. 80 00:05:13,960 --> 00:05:17,000 Speaker 2: Thank you, Director Santos for being for being a supporter 81 00:05:17,080 --> 00:05:18,880 Speaker 2: of our work and knowing our work. It really means 82 00:05:18,880 --> 00:05:20,560 Speaker 2: a lot. And I think I'm going to start there 83 00:05:20,600 --> 00:05:24,600 Speaker 2: because if I think about my experience as a Latina 84 00:05:24,640 --> 00:05:27,840 Speaker 2: in the media over the last thirty years, I think 85 00:05:27,839 --> 00:05:31,240 Speaker 2: that people always saw me kind of like, you know, like, oh, 86 00:05:31,279 --> 00:05:34,240 Speaker 2: here she goes again bringing up Latinos and Latinas, and 87 00:05:34,279 --> 00:05:37,320 Speaker 2: I think, I mean, I'm not a big mathematician or 88 00:05:37,320 --> 00:05:41,600 Speaker 2: a statistician like you, but I can read a demographic 89 00:05:41,800 --> 00:05:45,440 Speaker 2: chart and I could see that the Latino population was 90 00:05:45,640 --> 00:05:47,800 Speaker 2: just increasing. 91 00:05:47,760 --> 00:05:50,799 Speaker 4: And so for a lot of my career, people have kind. 92 00:05:50,600 --> 00:05:53,920 Speaker 2: Of been like, oh God, here she comes talking about 93 00:05:54,000 --> 00:05:56,880 Speaker 2: Latinos again. I always found it very interesting that people 94 00:05:56,920 --> 00:05:59,719 Speaker 2: felt like it was a bother or a like a 95 00:05:59,800 --> 00:06:02,080 Speaker 2: threat or a problem instead of just like, no, but 96 00:06:02,160 --> 00:06:04,279 Speaker 2: we're just kind of looking at that, And I'm wondering 97 00:06:04,320 --> 00:06:07,120 Speaker 2: if you're kind of having that same sensation in your 98 00:06:07,160 --> 00:06:07,920 Speaker 2: life right now. 99 00:06:08,480 --> 00:06:12,320 Speaker 1: Yeah, thank you for offering that perspective, because actually, I've 100 00:06:12,360 --> 00:06:17,480 Speaker 1: been having that type of interaction my entire career. I've 101 00:06:17,520 --> 00:06:21,960 Speaker 1: had episode after episode where I was the sole Latino 102 00:06:22,160 --> 00:06:27,760 Speaker 1: in a room of research decision makers who maybe hadn't 103 00:06:27,839 --> 00:06:31,720 Speaker 1: realized that when they come to the table and they 104 00:06:31,800 --> 00:06:37,600 Speaker 1: frame research questions, or they perceive problems that they want 105 00:06:37,640 --> 00:06:42,640 Speaker 1: to help society solve, they do it with their cultural lens. 106 00:06:43,040 --> 00:06:46,800 Speaker 1: I've had many instances where I basically say, excuse me, 107 00:06:47,040 --> 00:06:50,320 Speaker 1: if you do that, you actually will be doing harm 108 00:06:50,760 --> 00:06:54,320 Speaker 1: and not good. Even though the statistical design and the 109 00:06:54,360 --> 00:06:59,799 Speaker 1: research design was pristine. However, if you frame the question 110 00:07:00,080 --> 00:07:03,720 Speaker 1: the wrong way, or you capture information in a way 111 00:07:03,760 --> 00:07:07,160 Speaker 1: that doesn't really reveal what's going on, or interpret it 112 00:07:07,320 --> 00:07:10,680 Speaker 1: by talking to people in the community to help get 113 00:07:10,720 --> 00:07:14,560 Speaker 1: it better understanding, you can end up actually doing more 114 00:07:14,560 --> 00:07:15,280 Speaker 1: harm than good. 115 00:07:16,120 --> 00:07:18,200 Speaker 2: And the other thing I need to know, Director Santos, 116 00:07:18,200 --> 00:07:21,200 Speaker 2: I'm sorry, I just need to know. I know you 117 00:07:21,320 --> 00:07:25,560 Speaker 2: used to have a ponytail. Do you still it's growing hotly. 118 00:07:28,560 --> 00:07:33,080 Speaker 1: I was asked to be considered for the nomination and 119 00:07:33,320 --> 00:07:35,400 Speaker 1: I decided to do it. I did it out of 120 00:07:35,800 --> 00:07:38,240 Speaker 1: you know, Goda son. I wanted to help my country, 121 00:07:38,680 --> 00:07:41,160 Speaker 1: and I believed I could offer something as a Latino 122 00:07:41,240 --> 00:07:46,400 Speaker 1: from my rich perspective, cultural perspective and research perspective. But 123 00:07:46,600 --> 00:07:50,040 Speaker 1: the one thing that I decided is that I have 124 00:07:50,160 --> 00:07:56,280 Speaker 1: to be myself, and myself is Santos with a ponytail. 125 00:07:56,680 --> 00:08:00,000 Speaker 1: And so I'm going to be myself and try to 126 00:08:00,160 --> 00:08:02,200 Speaker 1: do the best I can to help the Census Bureau 127 00:08:02,240 --> 00:08:05,280 Speaker 1: to help the American people. And if it works, great, 128 00:08:05,320 --> 00:08:07,320 Speaker 1: and if it doesn't, I tried. 129 00:08:07,920 --> 00:08:08,960 Speaker 4: I think it's really cool. 130 00:08:09,040 --> 00:08:11,480 Speaker 2: I just want to say, because when you're rocking it, 131 00:08:11,480 --> 00:08:14,880 Speaker 2: it works. And two, I just think you're saying something 132 00:08:14,880 --> 00:08:16,480 Speaker 2: about just having to be yourself. 133 00:08:16,600 --> 00:08:16,840 Speaker 4: Right. 134 00:08:17,520 --> 00:08:19,720 Speaker 2: So recently I was in San Antonio. That's the city 135 00:08:19,760 --> 00:08:22,480 Speaker 2: of where you were born and raised. I was at 136 00:08:22,480 --> 00:08:27,040 Speaker 2: Trinity University giving a lecture, and you know, I love 137 00:08:27,120 --> 00:08:30,640 Speaker 2: San Antonio. It's one of my favorite cities because what 138 00:08:30,760 --> 00:08:32,640 Speaker 2: I've been going to it ever since a little girl, 139 00:08:32,679 --> 00:08:35,040 Speaker 2: because I was always driving through Texas to get from 140 00:08:35,120 --> 00:08:40,080 Speaker 2: Chicago to Mexico. It's a majority Latino city in the 141 00:08:40,200 --> 00:08:44,200 Speaker 2: United States, in the state of Texas. So yeah, not 142 00:08:44,360 --> 00:08:46,679 Speaker 2: as a kid from San Antonio, but as somebody who 143 00:08:46,800 --> 00:08:49,920 Speaker 2: understands the power of the work of the Census and 144 00:08:49,920 --> 00:08:53,240 Speaker 2: demography and the picture of the future of the United States. 145 00:08:53,720 --> 00:08:56,520 Speaker 2: I mean, is San Antonio in fact the future of 146 00:08:56,559 --> 00:08:58,959 Speaker 2: what the United States looks like? And what does that 147 00:08:59,040 --> 00:09:00,000 Speaker 2: mean to you? 148 00:09:00,280 --> 00:09:04,559 Speaker 1: Well, there are many really interesting things about San Antonio. 149 00:09:04,960 --> 00:09:08,600 Speaker 1: The fact that it has always had a very prominent 150 00:09:08,679 --> 00:09:13,680 Speaker 1: place for Mexican Americans in particular, but Latinos more generally 151 00:09:14,160 --> 00:09:17,120 Speaker 1: as being part of the city. Yet when I was 152 00:09:17,200 --> 00:09:23,040 Speaker 1: growing up, it was pretty effectively segregated, and even in 153 00:09:23,120 --> 00:09:25,600 Speaker 1: some of the Latino communities. You know, I lived on 154 00:09:25,640 --> 00:09:29,400 Speaker 1: the side of the Woodland Lake that you know, wasn't 155 00:09:29,600 --> 00:09:32,720 Speaker 1: considered the best part, and so if I went into 156 00:09:32,800 --> 00:09:35,640 Speaker 1: the other side where there were folks were better off, 157 00:09:36,280 --> 00:09:40,800 Speaker 1: I might be looked upon a little differently. But it's 158 00:09:40,880 --> 00:09:45,240 Speaker 1: interesting that we've embraced the culture of the Mexican American 159 00:09:45,240 --> 00:09:46,920 Speaker 1: community in San Antonio. 160 00:09:47,080 --> 00:09:49,160 Speaker 2: I mean, I guess the reason why one of the 161 00:09:49,200 --> 00:09:51,960 Speaker 2: reasons why I keep on asking about San Antonio as 162 00:09:52,000 --> 00:09:54,400 Speaker 2: a city of the future and what it looks like. 163 00:09:54,880 --> 00:09:55,440 Speaker 4: And you're right. 164 00:09:55,480 --> 00:09:57,640 Speaker 2: I mean, you get out of the airport in San Antonio, 165 00:09:57,679 --> 00:09:59,920 Speaker 2: because I was just there and there were these like 166 00:10:00,280 --> 00:10:09,720 Speaker 2: huge artists representations of LATAs, the Chipotle Chiles, Chipotle salsa ervees, 167 00:10:10,480 --> 00:10:13,000 Speaker 2: and I was like, only in San Antonio will you 168 00:10:13,120 --> 00:10:16,240 Speaker 2: see this? Like at the airport it's and and all 169 00:10:16,280 --> 00:10:19,040 Speaker 2: of this is like we're talking about San Antonio, and 170 00:10:19,280 --> 00:10:21,520 Speaker 2: you know, as it relates to a kind of city 171 00:10:21,559 --> 00:10:23,720 Speaker 2: of the future, with a kind of sense of joy 172 00:10:23,800 --> 00:10:27,800 Speaker 2: and hope and laughter. But you know this, Director Santos, 173 00:10:28,040 --> 00:10:31,280 Speaker 2: that actually the way the narrative goes right now in 174 00:10:31,280 --> 00:10:35,920 Speaker 2: the United States today is that Latinos and Latinas pose 175 00:10:36,000 --> 00:10:39,920 Speaker 2: some kind of a threat, that we're majority not from 176 00:10:40,000 --> 00:10:42,760 Speaker 2: the United States, that we're coming here, that we're new. 177 00:10:43,960 --> 00:10:45,840 Speaker 4: So put those two things together for. 178 00:10:45,800 --> 00:10:50,600 Speaker 1: Me, Well, it's not unusual for societies to have segments 179 00:10:50,640 --> 00:10:55,520 Speaker 1: of the population that view individuals of different backgrounds to 180 00:10:55,600 --> 00:10:59,839 Speaker 1: be threats, when in fact it's very much of an opportunity. 181 00:11:00,400 --> 00:11:04,880 Speaker 1: We could not survive without immigrants coming in and helping 182 00:11:05,120 --> 00:11:10,120 Speaker 1: our economy in ways that otherwise the citizen population would 183 00:11:10,120 --> 00:11:13,720 Speaker 1: not be able to contribute. So I very much value 184 00:11:14,200 --> 00:11:17,119 Speaker 1: the diversity, and I think that's one of our strongest 185 00:11:17,160 --> 00:11:19,960 Speaker 1: points as a nation. And that's why I take so 186 00:11:20,080 --> 00:11:25,360 Speaker 1: much pride in being able to advance the measurement and 187 00:11:25,360 --> 00:11:28,640 Speaker 1: the accounting and the learning about the rich diversity of 188 00:11:28,679 --> 00:11:32,400 Speaker 1: our population and how it's getting more diverse. It's inevitable, 189 00:11:32,440 --> 00:11:36,040 Speaker 1: as you said, it's coming, and we need to find 190 00:11:36,160 --> 00:11:40,559 Speaker 1: better ways to leverage and embrace that because it's going 191 00:11:40,600 --> 00:11:44,640 Speaker 1: to improve society. But I bring a different perspective. I 192 00:11:44,679 --> 00:11:49,080 Speaker 1: think to research and the Census Bureau and sort of 193 00:11:49,280 --> 00:11:52,920 Speaker 1: research more generally social science research, and I believe that 194 00:11:53,000 --> 00:11:55,880 Speaker 1: you have to bring your whole self. So I believe 195 00:11:55,880 --> 00:11:59,480 Speaker 1: in diversity, equity, inclusion, and I think in order to 196 00:11:59,520 --> 00:12:03,920 Speaker 1: be a better scientist, a better mathematician, a better statistician, 197 00:12:04,600 --> 00:12:08,120 Speaker 1: you need to bring your culture to the table when 198 00:12:08,200 --> 00:12:12,520 Speaker 1: you talk about and think about research, about interpreting results, 199 00:12:12,600 --> 00:12:15,520 Speaker 1: about how you analyze it, even how you frame what 200 00:12:15,559 --> 00:12:18,120 Speaker 1: it is that you're going to look at, because that 201 00:12:18,200 --> 00:12:22,360 Speaker 1: way you can actually learn more and gain more relevant 202 00:12:22,679 --> 00:12:28,199 Speaker 1: insights into particular problems, whether it's hunger or housing, or 203 00:12:28,400 --> 00:12:31,800 Speaker 1: the pandemic and vaccination statuses or whatever. 204 00:12:32,640 --> 00:12:35,600 Speaker 2: Okay, so, Director Santos, I actually want to take you 205 00:12:35,720 --> 00:12:38,679 Speaker 2: back to those days when you were growing up as 206 00:12:38,679 --> 00:12:40,959 Speaker 2: a kid in San Antonio. You were on the west 207 00:12:41,000 --> 00:12:42,360 Speaker 2: side of the city. You said it was a very 208 00:12:42,360 --> 00:12:48,320 Speaker 2: segregated city, and so you growing up. What was life 209 00:12:48,520 --> 00:12:51,640 Speaker 2: like back then as a kid. Were you like, yeah, 210 00:12:51,679 --> 00:12:55,600 Speaker 2: we're definitely the majority. We got this, We're going places, 211 00:12:55,920 --> 00:13:00,040 Speaker 2: or did you feel like, wow, this country's in the 212 00:13:00,080 --> 00:13:03,080 Speaker 2: middle of a civil rights era. Latinos and Latinas were 213 00:13:03,120 --> 00:13:04,840 Speaker 2: not necessarily visible. 214 00:13:05,280 --> 00:13:06,760 Speaker 4: So what was it to. 215 00:13:06,679 --> 00:13:09,120 Speaker 1: Be honest, I was a kid in the sixties. I 216 00:13:09,200 --> 00:13:12,840 Speaker 1: was in elementary school and middle school, and I graduated 217 00:13:12,840 --> 00:13:17,160 Speaker 1: in seventy two, and so I didn't I wasn't able 218 00:13:17,440 --> 00:13:20,800 Speaker 1: until I was maybe in grad school at Michigan to 219 00:13:21,000 --> 00:13:25,800 Speaker 1: really connect the dots fully, to realize the value and 220 00:13:25,920 --> 00:13:30,320 Speaker 1: importance of being a Latino. And that's where between my 221 00:13:30,800 --> 00:13:35,480 Speaker 1: college and graduate school years where I really embraced and 222 00:13:35,840 --> 00:13:39,800 Speaker 1: understood the magnitude of the societal issues that we were 223 00:13:39,840 --> 00:13:43,400 Speaker 1: dealing with. But back when I was a kid, I 224 00:13:43,480 --> 00:13:47,240 Speaker 1: was basically surviving. I was fortunate enough to go to 225 00:13:47,600 --> 00:13:52,520 Speaker 1: parochial school for twelve years. That instilled some great values 226 00:13:52,679 --> 00:13:56,120 Speaker 1: in me that I take with me and I use 227 00:13:56,320 --> 00:14:00,559 Speaker 1: every day of my forty year career as well as 228 00:14:00,800 --> 00:14:04,680 Speaker 1: now my continuing career at the Census Bureau. And those 229 00:14:04,760 --> 00:14:08,240 Speaker 1: values of trying to help people, those values of being 230 00:14:08,280 --> 00:14:13,040 Speaker 1: inclusive and treating people fairly and trying to help society, 231 00:14:13,280 --> 00:14:15,720 Speaker 1: those are really important and they drive me and they've 232 00:14:15,760 --> 00:14:19,160 Speaker 1: drive everything that I've done, you know, treating people with 233 00:14:19,200 --> 00:14:23,000 Speaker 1: respect regardless of race, color, creed, religion, or whatever. 234 00:14:23,800 --> 00:14:26,360 Speaker 4: So your mom and dad worked at the Air Force Base. 235 00:14:26,480 --> 00:14:26,640 Speaker 2: Right. 236 00:14:27,040 --> 00:14:31,640 Speaker 1: Yes, there were some very fortunate to have civil service 237 00:14:31,760 --> 00:14:35,200 Speaker 1: positions at Kelly Air Force Base while it was open. 238 00:14:35,920 --> 00:14:39,200 Speaker 2: So this notion of I see you as my equal, 239 00:14:39,680 --> 00:14:42,760 Speaker 2: a child of the civil rights era? Where was that 240 00:14:42,800 --> 00:14:46,080 Speaker 2: coming from? Was that your mom and dad bringing it home? 241 00:14:46,240 --> 00:14:48,560 Speaker 2: And talk to me a little bit about having a 242 00:14:48,560 --> 00:14:51,760 Speaker 2: mom and dad in the Air Force, because, I mean, 243 00:14:52,000 --> 00:14:55,240 Speaker 2: my dad was a scientist, medical doctor, researcher. But we 244 00:14:55,280 --> 00:14:58,440 Speaker 2: didn't talk that stuff over dinner. But like your dad 245 00:14:58,480 --> 00:15:01,840 Speaker 2: was asking you math questions, So take me a little 246 00:15:01,880 --> 00:15:02,440 Speaker 2: bit back. 247 00:15:02,920 --> 00:15:08,040 Speaker 1: Yeah, it's interesting. We had a really tightly knit family 248 00:15:08,800 --> 00:15:15,680 Speaker 1: and everything circulated around familiar and because everything revolved around family, 249 00:15:16,600 --> 00:15:20,440 Speaker 1: our focus was we didn't necessarily at the dinner table 250 00:15:20,520 --> 00:15:24,440 Speaker 1: talk about the inequities of society as much as talked 251 00:15:24,440 --> 00:15:28,800 Speaker 1: about familia and how we help each other and how 252 00:15:28,920 --> 00:15:32,160 Speaker 1: we need to strive to get better education and get 253 00:15:32,200 --> 00:15:34,800 Speaker 1: good jobs. I mean, that was what it was all about. 254 00:15:35,000 --> 00:15:39,000 Speaker 1: And you know, how could anyone blame familias for talking 255 00:15:39,040 --> 00:15:41,960 Speaker 1: about that? In San Antonio who were Mexican American and 256 00:15:42,000 --> 00:15:47,240 Speaker 1: whose grandparents had fled because of the revolution, the violence 257 00:15:47,600 --> 00:15:50,520 Speaker 1: in northern Mexico that was going on to survive, and 258 00:15:50,560 --> 00:15:54,800 Speaker 1: they started in new life and with almost nothing, and 259 00:15:55,000 --> 00:16:00,240 Speaker 1: my grandparents starting with jobs as gardeners or as cleaning people. 260 00:16:00,720 --> 00:16:05,680 Speaker 1: We then grew and generation after generation improved and that 261 00:16:05,800 --> 00:16:09,320 Speaker 1: pursuit of the American dream, that's really what was the 262 00:16:09,360 --> 00:16:13,480 Speaker 1: focus of discussion. And me as a little kid with 263 00:16:13,520 --> 00:16:17,480 Speaker 1: my brother who's no longer with us, our focus was 264 00:16:17,480 --> 00:16:19,520 Speaker 1: on trying to have as good of a time as 265 00:16:19,560 --> 00:16:22,960 Speaker 1: we could, especially with my parents both being off to 266 00:16:23,000 --> 00:16:25,360 Speaker 1: work in us being latchkey kids, so we got into 267 00:16:25,520 --> 00:16:26,560 Speaker 1: all kinds of mischief. 268 00:16:27,480 --> 00:16:30,200 Speaker 2: Okay, well I need to know what mischief looks like 269 00:16:30,280 --> 00:16:31,840 Speaker 2: in West San Antonio. 270 00:16:31,920 --> 00:16:34,200 Speaker 4: Then give me a couple of examples. What were you 271 00:16:34,200 --> 00:16:34,760 Speaker 4: guys doing. 272 00:16:35,720 --> 00:16:38,640 Speaker 1: Well, it was mischief in the sense of, you know, 273 00:16:38,680 --> 00:16:43,480 Speaker 1: we'd have you know, mudball fights in San Antonio where 274 00:16:43,600 --> 00:16:46,240 Speaker 1: the back of the house was yeah, mudball. We just 275 00:16:46,320 --> 00:16:50,000 Speaker 1: you know, throw water in the dirt, make mudballs and 276 00:16:50,040 --> 00:16:52,720 Speaker 1: come at it and the back of the house would 277 00:16:52,760 --> 00:16:55,680 Speaker 1: be covered with mudballs that stuck to the side of 278 00:16:55,680 --> 00:16:59,400 Speaker 1: the house. Or we'd grab our bicycles and we were 279 00:16:59,440 --> 00:17:02,600 Speaker 1: like what a nine ten years old now, I'd say ten, 280 00:17:02,680 --> 00:17:06,840 Speaker 1: eleven or twelve, and then head off from Woodlawn Lake 281 00:17:06,880 --> 00:17:10,960 Speaker 1: area to pass downtown to Hemisphere where it was being built, 282 00:17:10,960 --> 00:17:13,680 Speaker 1: so we could watch the tower going up the wow 283 00:17:14,520 --> 00:17:16,960 Speaker 1: or go out to the airport and watch the jets 284 00:17:17,040 --> 00:17:20,679 Speaker 1: come in. And that's really long distances for kids in 285 00:17:20,720 --> 00:17:23,080 Speaker 1: the middle of the summer with no water. We just 286 00:17:23,119 --> 00:17:28,000 Speaker 1: stop at gas stations, but we would do crazy, crazy 287 00:17:28,040 --> 00:17:28,639 Speaker 1: stuff like that. 288 00:17:29,560 --> 00:17:32,600 Speaker 2: It's kind of incredible that kids get into all that 289 00:17:32,680 --> 00:17:35,480 Speaker 2: mischief and survive, right, It's kind of amazing. 290 00:17:35,720 --> 00:17:38,560 Speaker 1: What's really important, though, is if you combine that sense 291 00:17:38,560 --> 00:17:43,720 Speaker 1: of adventure with the values that were instilled during the 292 00:17:44,080 --> 00:17:48,320 Speaker 1: schooling that I had, it's those two things that have 293 00:17:48,560 --> 00:17:53,080 Speaker 1: propelled me to take chances and risks where maybe other 294 00:17:53,119 --> 00:17:57,680 Speaker 1: folks would not have done it. So pretty much in 295 00:17:57,760 --> 00:18:00,960 Speaker 1: every job I've ever taken, it's been a step up, 296 00:18:01,119 --> 00:18:03,840 Speaker 1: and I've said, oh my god, can I Am I really. 297 00:18:03,640 --> 00:18:04,639 Speaker 4: Going to be able to do this? 298 00:18:05,560 --> 00:18:08,040 Speaker 1: And then I'd end up saying, well, look, just like 299 00:18:08,119 --> 00:18:10,439 Speaker 1: I told you earlier, I'm going to try my best. 300 00:18:10,480 --> 00:18:13,240 Speaker 1: I'm going to be myself and if I if I 301 00:18:13,280 --> 00:18:16,280 Speaker 1: can contribute, great, and if I can't, I'll be able 302 00:18:16,320 --> 00:18:18,480 Speaker 1: to look myself in the mirror and say I try my. 303 00:18:18,480 --> 00:18:26,639 Speaker 4: Best coming up on LEATINGO USA. 304 00:18:26,880 --> 00:18:32,280 Speaker 2: Director Santos on rebuilding trust and facing the systemic problems 305 00:18:32,560 --> 00:18:33,320 Speaker 2: at the Census. 306 00:18:33,680 --> 00:19:29,639 Speaker 4: Stay with us, Yes, Hey, we're back. 307 00:19:30,400 --> 00:19:33,040 Speaker 2: We're going to continue now with my conversation with Director 308 00:19:33,080 --> 00:19:42,600 Speaker 2: of the US Census Bureau Robert Santos. The interesting thing, 309 00:19:42,640 --> 00:19:45,800 Speaker 2: Director Santos, is that I have a lot of feelings 310 00:19:45,880 --> 00:19:50,720 Speaker 2: about the senses. With the senses, it's actually something that 311 00:19:51,520 --> 00:19:55,440 Speaker 2: has had an impact in my life in very interesting ways. 312 00:19:55,440 --> 00:19:56,840 Speaker 2: And I kind of be honest with you, and I'm 313 00:19:56,840 --> 00:19:58,760 Speaker 2: sure you're not going to be surprised when I'm like, 314 00:19:58,800 --> 00:20:01,000 Speaker 2: it's kind of a love hate relationtionship with the Census. 315 00:20:02,160 --> 00:20:02,440 Speaker 4: I think. 316 00:20:02,480 --> 00:20:05,480 Speaker 2: I remember as a little girl that Hispanic was a 317 00:20:05,600 --> 00:20:10,600 Speaker 2: term that was created for the Census by a Republican administration, 318 00:20:10,960 --> 00:20:13,479 Speaker 2: and my family did not like the Republicans. So I 319 00:20:13,520 --> 00:20:15,919 Speaker 2: was like, I'm not Hispanic, I'm not a term that 320 00:20:16,040 --> 00:20:19,119 Speaker 2: was created. So the Census has this kind of again 321 00:20:19,200 --> 00:20:21,960 Speaker 2: this impact. In fact, in twenty ten, when I form 322 00:20:22,200 --> 00:20:26,000 Speaker 2: Futuro Media, my own company, one of the things that 323 00:20:26,320 --> 00:20:28,560 Speaker 2: made me believe that I could do it was data 324 00:20:28,560 --> 00:20:29,280 Speaker 2: from the Census. 325 00:20:29,560 --> 00:20:29,720 Speaker 4: Right. 326 00:20:30,040 --> 00:20:33,200 Speaker 2: The data was that the Latino population growth from twenty 327 00:20:33,280 --> 00:20:38,040 Speaker 2: to twenty ten had grown at forty three percent. So 328 00:20:39,040 --> 00:20:43,959 Speaker 2: the Census is an organization that we I think you 329 00:20:44,160 --> 00:20:47,119 Speaker 2: too have had a love hate relationship with. 330 00:20:47,200 --> 00:20:47,720 Speaker 4: Am I right? 331 00:20:48,080 --> 00:20:51,640 Speaker 2: How do you see how the Census has impacted your 332 00:20:51,760 --> 00:20:54,200 Speaker 2: personal life? Were you that guy who was like thinking 333 00:20:54,200 --> 00:20:57,080 Speaker 2: about the Census like decades. 334 00:20:56,600 --> 00:21:01,760 Speaker 1: Ago, actually decades ago? I was because I actually did 335 00:21:01,840 --> 00:21:06,320 Speaker 1: projects for the Census A as a researcher. I served 336 00:21:06,359 --> 00:21:09,760 Speaker 1: for six years on the advisory committee and said the 337 00:21:09,800 --> 00:21:12,920 Speaker 1: same thing day one as I did six years later 338 00:21:12,960 --> 00:21:15,000 Speaker 1: as I walked out the door in terms of advice. 339 00:21:15,520 --> 00:21:19,360 Speaker 1: But I actually have not had a love hate relationship. 340 00:21:19,400 --> 00:21:23,119 Speaker 1: I've had a love love relationship with the Census my 341 00:21:23,480 --> 00:21:27,200 Speaker 1: entire career because I recognize. 342 00:21:26,720 --> 00:21:30,399 Speaker 4: Love love like I mean, you've been critical of it, though. 343 00:21:30,320 --> 00:21:34,199 Speaker 1: Right, because I love the Census Bureau. 344 00:21:34,640 --> 00:21:36,680 Speaker 2: Are you, like really that person who's like, oh my god, 345 00:21:36,680 --> 00:21:37,959 Speaker 2: I've always loved this. 346 00:21:38,119 --> 00:21:39,000 Speaker 4: Are you that person? 347 00:21:40,040 --> 00:21:44,760 Speaker 1: I am in the sense that I want it and 348 00:21:44,840 --> 00:21:47,800 Speaker 1: we need it to improve and to be the best 349 00:21:47,840 --> 00:21:52,280 Speaker 1: that it is. It's been, It's done some exceptionally great 350 00:21:52,320 --> 00:21:58,560 Speaker 1: stuff in the past. All statistics have strengths and limitations. 351 00:21:58,960 --> 00:22:03,960 Speaker 1: The limitation for desennial Census historically have been ones where 352 00:22:03,960 --> 00:22:08,280 Speaker 1: people of color are undercounted. That's an issue I've been 353 00:22:08,320 --> 00:22:12,720 Speaker 1: critical before the Census, and now that i'm director, we're 354 00:22:12,840 --> 00:22:15,040 Speaker 1: looking at that. And it's not like they don't look 355 00:22:15,040 --> 00:22:20,520 Speaker 1: at it every day of our lives. We have experts 356 00:22:20,560 --> 00:22:23,760 Speaker 1: who are trying their best to think of new, creative 357 00:22:23,760 --> 00:22:27,800 Speaker 1: ways to help with participation, et cetera. But I recognize 358 00:22:27,960 --> 00:22:31,439 Speaker 1: that the data that the census provides is a vital 359 00:22:31,520 --> 00:22:38,439 Speaker 1: part of our democracy. We can't improve communities, neighborhoods, we 360 00:22:38,600 --> 00:22:44,159 Speaker 1: can't identify problems unless we can measure properly that the 361 00:22:44,240 --> 00:22:47,119 Speaker 1: state of the nation who we are as a people. 362 00:22:47,760 --> 00:22:51,119 Speaker 1: And it's in that context that I've always loved the 363 00:22:51,160 --> 00:22:54,960 Speaker 1: Census Bureau because I admire them doing the best that 364 00:22:55,040 --> 00:22:58,160 Speaker 1: can be done, even though it's not perfection. 365 00:22:58,440 --> 00:23:00,000 Speaker 4: Because I mean, that's what I was going to say. 366 00:23:00,280 --> 00:23:04,679 Speaker 2: So is it that you've been up at night not 367 00:23:04,920 --> 00:23:08,119 Speaker 2: now just because you're the director of the Census, but 368 00:23:08,200 --> 00:23:14,200 Speaker 2: that in the past because the undercounting of in particular 369 00:23:14,280 --> 00:23:21,159 Speaker 2: Latino Latina LATINX community and frankly, and I know this 370 00:23:21,200 --> 00:23:23,600 Speaker 2: is not a surprise to you, there's deep distrust now 371 00:23:23,640 --> 00:23:27,959 Speaker 2: with any government institution in the United States. I mean, 372 00:23:28,000 --> 00:23:30,000 Speaker 2: are those things that have kept you up at night? 373 00:23:30,040 --> 00:23:32,760 Speaker 2: This whole notion of like the deep, deep undercounting that 374 00:23:33,320 --> 00:23:38,879 Speaker 2: comes from one I suppose deep disorganization, but also deep distrust. 375 00:23:39,920 --> 00:23:42,200 Speaker 1: I'm not prepared to say it keeps me up at night, 376 00:23:42,280 --> 00:23:47,680 Speaker 1: as much as it's a core issue that we need 377 00:23:47,720 --> 00:23:52,160 Speaker 1: to address for the future, we need to recognize its existence. 378 00:23:52,600 --> 00:23:56,400 Speaker 1: There are mistrust issues that have been historical as well 379 00:23:56,400 --> 00:24:00,520 Speaker 1: as more recent, and I would never have taken job 380 00:24:00,760 --> 00:24:03,720 Speaker 1: unless I thought I could help in that regard. So 381 00:24:03,840 --> 00:24:09,200 Speaker 1: one of the primary agenda items for me, or contributions 382 00:24:09,240 --> 00:24:11,880 Speaker 1: that I want to make as Director of the Census 383 00:24:11,880 --> 00:24:15,600 Speaker 1: Bureau is to put a human face on the Census Bureau. 384 00:24:15,920 --> 00:24:19,639 Speaker 1: We're not a bunch of mathematicians in our little offices 385 00:24:20,240 --> 00:24:23,639 Speaker 1: thinking big thoughts. We're actually human beings. 386 00:24:23,680 --> 00:24:24,200 Speaker 4: We all have. 387 00:24:24,280 --> 00:24:28,639 Speaker 1: Cultures, we all have issues, we all are human in nature. 388 00:24:29,119 --> 00:24:32,480 Speaker 1: And I'm bringing that because I think I can. I'm 389 00:24:32,520 --> 00:24:38,040 Speaker 1: going to outreach to communities, to neighborhoods, to stakeholders, to congress, 390 00:24:38,119 --> 00:24:41,880 Speaker 1: to local governments, to tribal communities. I want to get 391 00:24:41,920 --> 00:24:44,600 Speaker 1: out there and I want to find out what those 392 00:24:44,680 --> 00:24:47,040 Speaker 1: issues are with my staff. 393 00:24:47,240 --> 00:24:48,200 Speaker 4: So the Census. 394 00:24:47,880 --> 00:24:50,600 Speaker 1: SPIRO will be a part of all of that and 395 00:24:50,960 --> 00:24:56,760 Speaker 1: establish a continuous relationship with people and with communities, rather 396 00:24:56,880 --> 00:25:00,480 Speaker 1: than simply two years before a census saying, Okay, it's 397 00:25:00,480 --> 00:25:03,320 Speaker 1: time for us to have partnerships. We recognize that we 398 00:25:03,359 --> 00:25:05,919 Speaker 1: need to have this continuously, and I'm going to be 399 00:25:06,920 --> 00:25:10,960 Speaker 1: upfront and center trying to work with everyone to establish 400 00:25:11,119 --> 00:25:14,920 Speaker 1: a true two way relationship, not just to help us 401 00:25:15,320 --> 00:25:19,119 Speaker 1: get participation, but also here is information that's useful for 402 00:25:19,240 --> 00:25:22,600 Speaker 1: your specific community. Here are some tools you can use 403 00:25:22,600 --> 00:25:26,320 Speaker 1: to identify community needs, to solve problems, to create more 404 00:25:26,400 --> 00:25:30,399 Speaker 1: economic development. That's the type of two way relationship that 405 00:25:30,440 --> 00:25:31,080 Speaker 1: I really want. 406 00:25:30,960 --> 00:25:32,720 Speaker 4: To get, Director Santos. 407 00:25:32,760 --> 00:25:38,000 Speaker 2: The last administration and all of the controversy leading up 408 00:25:38,359 --> 00:25:44,240 Speaker 2: to the twenty twenty senses has, I mean, it's so polarized, 409 00:25:45,240 --> 00:25:50,600 Speaker 2: and it forced people more into a place of darkness, 410 00:25:50,920 --> 00:25:53,960 Speaker 2: I suppose in regards to the Senses. So I mean 411 00:25:54,040 --> 00:25:57,480 Speaker 2: you're trying to kind of I don't want to say 412 00:25:57,520 --> 00:25:59,919 Speaker 2: catch up, because you're actually trying to do something very future. 413 00:26:00,359 --> 00:26:03,800 Speaker 2: But you've got a lot of lead from the last 414 00:26:03,840 --> 00:26:07,159 Speaker 2: administration in the last decades. I mean that lead is 415 00:26:07,480 --> 00:26:09,240 Speaker 2: how do you deal with that lead that is weighing 416 00:26:09,320 --> 00:26:13,280 Speaker 2: you down, which is part historical and you know, systemic. 417 00:26:13,680 --> 00:26:17,200 Speaker 1: I do not view this as an issue of oh 418 00:26:17,240 --> 00:26:19,600 Speaker 1: my god, look what's happened in the past. I view 419 00:26:19,640 --> 00:26:22,239 Speaker 1: it as where do we need to get into the 420 00:26:22,320 --> 00:26:25,639 Speaker 1: future and how do we need to address these types 421 00:26:25,680 --> 00:26:30,320 Speaker 1: of issues. So I'm I'm looking forward because one of 422 00:26:30,400 --> 00:26:34,439 Speaker 1: the greatest attributes and strengths of the Census Bureau is 423 00:26:34,480 --> 00:26:39,920 Speaker 1: that it is a non partisan federal statistical agency. So 424 00:26:40,000 --> 00:26:44,840 Speaker 1: I'll say it again, it's a non partisan federal statistical agency, 425 00:26:45,280 --> 00:26:49,320 Speaker 1: which is the only reason that I was willing to join. 426 00:26:49,920 --> 00:26:55,879 Speaker 1: Because the notion of scientific integrity, objectivity is something and 427 00:26:55,960 --> 00:27:00,520 Speaker 1: transparency not many organizations want to reveal, like the good 428 00:27:00,600 --> 00:27:02,880 Speaker 1: and the bad and the ugly about everything we do. 429 00:27:03,480 --> 00:27:05,720 Speaker 1: We put that up front because that's part of our 430 00:27:05,800 --> 00:27:09,199 Speaker 1: job that the American people deserve to hear and to 431 00:27:09,280 --> 00:27:12,760 Speaker 1: see the strengths and limitations of all of our data products. 432 00:27:13,119 --> 00:27:16,640 Speaker 1: And it's because of that scientific integrity and our non 433 00:27:16,720 --> 00:27:20,359 Speaker 1: powers in nature that I think we have a really 434 00:27:20,400 --> 00:27:24,080 Speaker 1: good starting point to take wherever we are right now 435 00:27:24,320 --> 00:27:27,720 Speaker 1: and move forward and create really great ties to communities 436 00:27:27,760 --> 00:27:30,120 Speaker 1: and great things, and that's what I'm going to be doing, 437 00:27:30,600 --> 00:27:32,159 Speaker 1: and I know that that's what the rest of the 438 00:27:32,160 --> 00:27:33,880 Speaker 1: sense of spirit is going to be doing as well. 439 00:27:34,240 --> 00:27:36,840 Speaker 2: Your excitement about being at the Census is clear, like 440 00:27:36,880 --> 00:27:37,600 Speaker 2: we can feel it. 441 00:27:37,760 --> 00:27:39,959 Speaker 4: We absolutely can feel it. I can see it. 442 00:27:40,840 --> 00:27:43,080 Speaker 2: So I want to zoom out for a bit, because 443 00:27:43,320 --> 00:27:45,760 Speaker 2: when I think about the senses, I think the other 444 00:27:45,840 --> 00:27:49,840 Speaker 2: word that comes to mind is white supremacy and systemic 445 00:27:49,960 --> 00:27:53,280 Speaker 2: racism and how that is a part of the institution. 446 00:27:54,040 --> 00:27:57,000 Speaker 2: We have to acknowledge how people in this country were 447 00:27:57,119 --> 00:28:00,800 Speaker 2: first counted right, Enslaved black people were basic counted only 448 00:28:00,800 --> 00:28:04,280 Speaker 2: as three fifths of a human being, and areas with 449 00:28:04,359 --> 00:28:07,600 Speaker 2: large enslaved populations benefited from this in terms of federal 450 00:28:07,640 --> 00:28:13,440 Speaker 2: funding and political power and representation. So again, your excitement 451 00:28:13,520 --> 00:28:15,520 Speaker 2: to be at the Census, But the question I'm going 452 00:28:15,560 --> 00:28:20,080 Speaker 2: to ask you is, well, should the Census be dismantled, 453 00:28:20,119 --> 00:28:23,399 Speaker 2: should it be reassembled? How do we deal with the 454 00:28:23,440 --> 00:28:25,439 Speaker 2: fact that, you know, close to four out of the 455 00:28:25,480 --> 00:28:29,840 Speaker 2: five senior executives at the Bureau identify as white, according 456 00:28:29,840 --> 00:28:32,720 Speaker 2: to an NPR study from last year. So you're dealing 457 00:28:32,760 --> 00:28:36,360 Speaker 2: with your big dreams and a powerful institution, but one 458 00:28:36,400 --> 00:28:40,600 Speaker 2: that has, in this case issues of white supremacy. 459 00:28:42,320 --> 00:28:45,760 Speaker 1: Well, I think that, you know, pundits and others can 460 00:28:45,840 --> 00:28:49,640 Speaker 1: characterize the Census Bureau as they might. I do know 461 00:28:49,800 --> 00:28:53,520 Speaker 1: that because of things like the pandemic, we are at 462 00:28:53,560 --> 00:28:59,480 Speaker 1: a wonderful inflection point where we understand the value of 463 00:28:59,600 --> 00:29:04,960 Speaker 1: diverse city equity and inclusion, and everyone I've spoken to 464 00:29:05,680 --> 00:29:10,000 Speaker 1: wants to make progress in this regard, including myself. I 465 00:29:10,080 --> 00:29:13,160 Speaker 1: think that it would be naive to think that any 466 00:29:13,240 --> 00:29:18,880 Speaker 1: government or any society does not have issues with them 467 00:29:19,040 --> 00:29:22,680 Speaker 1: with regard to historical racism and things of that sort. 468 00:29:23,240 --> 00:29:26,520 Speaker 1: But in terms of where we go from now, by 469 00:29:27,040 --> 00:29:33,120 Speaker 1: leveraging this diversity, equity and inclusion principles, we are recognizing 470 00:29:33,160 --> 00:29:38,000 Speaker 1: the value not only for creating a more diverse workforce 471 00:29:38,120 --> 00:29:42,480 Speaker 1: within the Census Bureau, but also questioning every single thing 472 00:29:42,640 --> 00:29:45,719 Speaker 1: we do with regard to what we measure, how we 473 00:29:45,800 --> 00:29:49,600 Speaker 1: measure it, how relevant it is, and not only that 474 00:29:50,000 --> 00:29:54,040 Speaker 1: when we produce it, how valuable it is based on 475 00:29:54,160 --> 00:29:58,080 Speaker 1: community engagement and getting folks reaction to results and things 476 00:29:58,120 --> 00:30:01,800 Speaker 1: of that sort. So I'm very much you know, I 477 00:30:01,840 --> 00:30:07,400 Speaker 1: am absolutely not a Pollyanna. I absolutely know that issues 478 00:30:07,560 --> 00:30:11,960 Speaker 1: exist and they are cultural and they are baked into society. 479 00:30:12,000 --> 00:30:15,120 Speaker 1: But that doesn't mean we cannot don't have an obligation 480 00:30:15,240 --> 00:30:18,520 Speaker 1: to try. That's what I'm doing, That's what we all 481 00:30:18,560 --> 00:30:20,360 Speaker 1: have to do, and we have to do it together 482 00:30:20,600 --> 00:30:22,000 Speaker 1: and we need each other's support. 483 00:30:22,760 --> 00:30:25,680 Speaker 2: Director Santos forgive me that I should know the answer 484 00:30:25,760 --> 00:30:29,440 Speaker 2: to this question, but I don't. Has the census apologized 485 00:30:30,120 --> 00:30:33,280 Speaker 2: for the fact that the data from the census was 486 00:30:33,400 --> 00:30:38,560 Speaker 2: used to enter, i e. Imprison American citizens of Japanese 487 00:30:38,600 --> 00:30:42,080 Speaker 2: descent and that they were targeted because of the use 488 00:30:42,120 --> 00:30:44,680 Speaker 2: of the census data. Has there been a formal apology 489 00:30:44,680 --> 00:30:46,640 Speaker 2: that I just didn't know about. 490 00:30:47,120 --> 00:30:49,479 Speaker 1: Yeah, thank you, thank you for asking. That's a really 491 00:30:49,720 --> 00:30:55,720 Speaker 1: really important question. Can prove it Actually years back, apologized 492 00:30:55,760 --> 00:30:58,840 Speaker 1: formally to representatives of the Japanese community. 493 00:30:59,480 --> 00:31:01,800 Speaker 2: So how do we because you know this as well 494 00:31:02,040 --> 00:31:05,800 Speaker 2: in our community, especially after the last administration, the previous 495 00:31:05,800 --> 00:31:10,600 Speaker 2: administration in particular Latinos and Latinas and building this trust 496 00:31:11,440 --> 00:31:17,720 Speaker 2: and immigrants and refugees, undocumented people, how do you rebuild 497 00:31:17,720 --> 00:31:19,560 Speaker 2: the trust? And I know I get the whole like 498 00:31:19,640 --> 00:31:22,200 Speaker 2: we are the census, we are you, But I mean 499 00:31:22,760 --> 00:31:25,640 Speaker 2: you also deal with hard facts. You also want to 500 00:31:25,640 --> 00:31:28,680 Speaker 2: deal with the humanizing of it. How do you create 501 00:31:28,720 --> 00:31:32,520 Speaker 2: trust in an institution that is so large and that 502 00:31:32,640 --> 00:31:35,400 Speaker 2: has this past history And I know you want to 503 00:31:35,400 --> 00:31:37,480 Speaker 2: look at the future. So in the future, how do 504 00:31:37,600 --> 00:31:38,520 Speaker 2: you want to create. 505 00:31:38,800 --> 00:31:42,560 Speaker 1: And we are already taking steps in that direction. It 506 00:31:42,680 --> 00:31:47,040 Speaker 1: is critical that we engage with the public with we 507 00:31:47,080 --> 00:31:50,320 Speaker 1: engage in local communities. We engage with people of color 508 00:31:50,520 --> 00:31:56,360 Speaker 1: and communities of color in their various manifestations, whether it's 509 00:31:56,440 --> 00:31:59,720 Speaker 1: through with non Leo or maldef or the Asian American 510 00:32:00,320 --> 00:32:05,080 Speaker 1: associations that look out for those interests. It's really important 511 00:32:05,120 --> 00:32:09,440 Speaker 1: to have those types of conversations that are continuous, and 512 00:32:09,840 --> 00:32:17,320 Speaker 1: it's through having those conversations and demonstrating that their concerns 513 00:32:17,520 --> 00:32:24,440 Speaker 1: matter by incorporating those into actions we take in the future. 514 00:32:25,040 --> 00:32:28,640 Speaker 1: Through that loop and through us demonstrating with hard data 515 00:32:28,800 --> 00:32:33,600 Speaker 1: that we can we can help their communities and all communities, 516 00:32:33,880 --> 00:32:36,280 Speaker 1: I think we will build build trust. 517 00:32:36,960 --> 00:32:38,239 Speaker 2: And what are we going to do or what are 518 00:32:38,240 --> 00:32:39,719 Speaker 2: you going to do with the fact that there's an 519 00:32:39,760 --> 00:32:45,840 Speaker 2: acknowledgment of a pretty severe undercount that happened, particularly in black, Latino, 520 00:32:45,920 --> 00:32:51,560 Speaker 2: Latin and LATINX communities. What's your plan you again, if 521 00:32:51,600 --> 00:32:53,440 Speaker 2: you're like, well, we can't deal with what happened in 522 00:32:53,480 --> 00:32:55,880 Speaker 2: the past, that's already happened. But then what is the plan, 523 00:32:56,920 --> 00:32:58,440 Speaker 2: like a very specific plan. 524 00:32:59,400 --> 00:33:02,320 Speaker 1: Yes, and we're in the midst of forming plans for 525 00:33:02,400 --> 00:33:05,960 Speaker 1: the twenty thirty census, but please be aware that the 526 00:33:06,760 --> 00:33:12,480 Speaker 1: plans for increasing participation and representation in the data collections 527 00:33:12,480 --> 00:33:15,760 Speaker 1: that we do are spread to all of the one 528 00:33:15,840 --> 00:33:19,360 Speaker 1: hundred and thirty or so surveys that we do every year, 529 00:33:19,760 --> 00:33:22,560 Speaker 1: as well as our economic censuses that are coming up. 530 00:33:22,800 --> 00:33:27,040 Speaker 1: And Latinos and African Americans have local businesses and such, 531 00:33:27,520 --> 00:33:31,239 Speaker 1: so we're looking to to do that. 532 00:33:32,360 --> 00:33:35,880 Speaker 2: So again, I love the fact that I have these 533 00:33:36,000 --> 00:33:40,680 Speaker 2: very specific reactions about the Census when every year, every decade, 534 00:33:40,760 --> 00:33:42,160 Speaker 2: you know, when I have to deal with this. But 535 00:33:43,200 --> 00:33:48,560 Speaker 2: the term Hispanic, the term Latino, Latina, LATINX, you know, 536 00:33:48,760 --> 00:33:53,600 Speaker 2: Afro Latiniva, indigenous cells. I mean, I every time I 537 00:33:53,640 --> 00:33:55,600 Speaker 2: look at the Census, I'm like, but I'm not here. 538 00:33:56,360 --> 00:33:59,760 Speaker 2: I don't feel I like, I don't the boxes, which box, 539 00:34:00,200 --> 00:34:03,160 Speaker 2: checking of the box. I'm sure you felt this way too, 540 00:34:03,800 --> 00:34:06,200 Speaker 2: So what's your plan to kind of make the senses 541 00:34:06,720 --> 00:34:09,200 Speaker 2: like read the room, understand the United States and it's 542 00:34:09,239 --> 00:34:12,680 Speaker 2: actually living in because it feels like it's the senses 543 00:34:12,719 --> 00:34:16,279 Speaker 2: again of the white men from the nineteen fifties that 544 00:34:16,320 --> 00:34:18,880 Speaker 2: were kind of creating the paradigms, and the paradigms have 545 00:34:18,960 --> 00:34:19,560 Speaker 2: all shifted. 546 00:34:20,080 --> 00:34:24,440 Speaker 1: That is a wonderful starting point for this notion that 547 00:34:25,040 --> 00:34:30,040 Speaker 1: society has tangibly changed over the last twenty thirty forty years, 548 00:34:30,600 --> 00:34:35,800 Speaker 1: where people are understanding and embracing different cultures and ancestries, 549 00:34:36,520 --> 00:34:40,680 Speaker 1: and an organization like the Census Bureau and more broadly, 550 00:34:40,960 --> 00:34:44,480 Speaker 1: the federal statistical system, because there's lots of other groups 551 00:34:44,560 --> 00:34:48,000 Speaker 1: in the federal government that collect data, need to understand 552 00:34:48,080 --> 00:34:52,719 Speaker 1: and be contemporary with the way that people identify themselves 553 00:34:53,160 --> 00:34:55,880 Speaker 1: and our notions of who we are, especially with multi 554 00:34:55,960 --> 00:35:00,759 Speaker 1: race couples and children and multi ethnic couples and children. 555 00:35:01,520 --> 00:35:04,880 Speaker 1: People are just becoming more aware of who they are, 556 00:35:05,120 --> 00:35:07,800 Speaker 1: and when they do that, they think of themselves differently, 557 00:35:08,440 --> 00:35:11,400 Speaker 1: and so using standards like the ones we currently have 558 00:35:11,560 --> 00:35:15,759 Speaker 1: that we're developed in nineteen ninety seven aren't necessarily the 559 00:35:15,800 --> 00:35:21,560 Speaker 1: best ones to capture the rich diversity of our wonderful population. 560 00:35:21,800 --> 00:35:25,960 Speaker 1: Right now, we are at the Census Bureau don't have 561 00:35:26,440 --> 00:35:30,800 Speaker 1: the authority to simply change race ethnicity questions. It needs 562 00:35:30,840 --> 00:35:34,080 Speaker 1: to go through a process by the federal government to 563 00:35:34,160 --> 00:35:38,640 Speaker 1: update the standards, and we are actively working with the 564 00:35:38,680 --> 00:35:41,960 Speaker 1: Office of Management and Budget, which is part of the 565 00:35:42,000 --> 00:35:46,040 Speaker 1: White House. They're the group that creates and revises standards, 566 00:35:46,600 --> 00:35:50,480 Speaker 1: and our understanding is that that process with regard to 567 00:35:51,239 --> 00:35:55,480 Speaker 1: ethnicity as well as with regard to SOJII questions, sexual 568 00:35:55,520 --> 00:36:00,640 Speaker 1: orientation and gender identity, well, those discussions will become soon 569 00:36:01,040 --> 00:36:05,000 Speaker 1: and we have existing research that we've already done as 570 00:36:05,040 --> 00:36:08,080 Speaker 1: well as ideas on how to go forward to better 571 00:36:08,200 --> 00:36:12,879 Speaker 1: capture that rich diversity and the disaggregation of Latinos, disaggregation 572 00:36:12,960 --> 00:36:17,840 Speaker 1: of whites, disaggregation African Americans, Asians, tribal communities, and so forth. 573 00:36:18,680 --> 00:36:22,040 Speaker 2: I remember when I started hearing that term disaggregation, So 574 00:36:22,200 --> 00:36:25,359 Speaker 2: just so people get it, can you just define what 575 00:36:25,400 --> 00:36:28,279 Speaker 2: disaggregation means, because I think while you're the head of 576 00:36:28,280 --> 00:36:31,319 Speaker 2: the census, people will be hearing that murd a lot more. 577 00:36:32,000 --> 00:36:35,600 Speaker 1: Yeah, forgive me, I like to pride myself as being 578 00:36:35,719 --> 00:36:37,840 Speaker 1: someone who can speak more. 579 00:36:39,440 --> 00:36:40,080 Speaker 5: To the public. 580 00:36:40,640 --> 00:36:43,759 Speaker 1: But then I throw out, I bust out the term 581 00:36:44,520 --> 00:36:48,799 Speaker 1: disaggregation and Oh, it's obviously it's a it's an industry term. 582 00:36:49,600 --> 00:36:57,600 Speaker 1: Disaggregation really is very basic. Latinos are not a monolithic population. 583 00:36:58,280 --> 00:37:01,279 Speaker 1: We're luck together as a group of different groups of 584 00:37:01,440 --> 00:37:04,839 Speaker 1: a set of peoples. They're Kubanos, you know, folks from 585 00:37:04,960 --> 00:37:10,080 Speaker 1: Dominican Mexicans, even you know, Central and South America and 586 00:37:10,160 --> 00:37:13,719 Speaker 1: so forth in Puerto Ricans. And it's important to be 587 00:37:13,800 --> 00:37:18,680 Speaker 1: able to understand those differences because different communities can have 588 00:37:18,760 --> 00:37:23,759 Speaker 1: different mixes of a specific type of Latino. Not to mention, 589 00:37:23,880 --> 00:37:27,759 Speaker 1: you bring in immigrant status as well, and that will 590 00:37:27,800 --> 00:37:32,440 Speaker 1: trigger notions of what types of community needs there are. 591 00:37:33,160 --> 00:37:36,960 Speaker 1: How to better address issues like, you know, how do 592 00:37:37,000 --> 00:37:39,960 Speaker 1: we convince folks to take vaccines, how do we get 593 00:37:40,040 --> 00:37:43,080 Speaker 1: folks to register to vote? How do we get folks 594 00:37:43,120 --> 00:37:47,520 Speaker 1: to understand the value of fruits and vegetables for a 595 00:37:47,560 --> 00:37:50,600 Speaker 1: more nutritious meal, even though they may not have a 596 00:37:50,600 --> 00:37:54,240 Speaker 1: Liverpool wage to you know, to buy those types of products. 597 00:37:54,760 --> 00:37:58,480 Speaker 1: So we really need to understand the rich diversity, and 598 00:37:58,520 --> 00:37:59,839 Speaker 1: that's what desegregation means. 599 00:38:00,440 --> 00:38:03,000 Speaker 2: I think part of what you're trying to do is, 600 00:38:03,040 --> 00:38:07,120 Speaker 2: as you say, you want you and your whole staff 601 00:38:07,120 --> 00:38:10,280 Speaker 2: to bring their entire selves into the Census Bureau because 602 00:38:10,280 --> 00:38:13,960 Speaker 2: that ultimately will lead to a better Census Bureau. You 603 00:38:14,040 --> 00:38:18,200 Speaker 2: have actually and you talk a lot about equity and inclusion, 604 00:38:18,960 --> 00:38:21,840 Speaker 2: and you've actually taken some steps. So what are you 605 00:38:21,960 --> 00:38:25,480 Speaker 2: doing in terms of your own staff and that diversity 606 00:38:25,640 --> 00:38:26,960 Speaker 2: representation and inclusion. 607 00:38:27,800 --> 00:38:31,719 Speaker 1: Well, on the staff that I work with directly, there 608 00:38:31,840 --> 00:38:38,000 Speaker 1: is actually a incredibly rich diversity of Latinos, of African Americans, 609 00:38:38,719 --> 00:38:44,080 Speaker 1: of white individuals from different backgrounds. We have efforts to 610 00:38:44,320 --> 00:38:49,759 Speaker 1: transform and modernize the Census Bureau because we absolutely need 611 00:38:49,800 --> 00:38:54,359 Speaker 1: it in order to survive in the future. And part 612 00:38:54,400 --> 00:38:57,680 Speaker 1: of that is making sure that we do things like 613 00:38:58,080 --> 00:39:02,600 Speaker 1: review all of our policies and practices for two things. 614 00:39:03,360 --> 00:39:06,680 Speaker 1: One is to make sure they are equitable, and my 615 00:39:06,800 --> 00:39:09,200 Speaker 1: guess is that most, if not all, will end up 616 00:39:09,239 --> 00:39:11,960 Speaker 1: being equitable. We've got to do our due diligence. And 617 00:39:12,000 --> 00:39:16,319 Speaker 1: the second is the practice. It's policies and practice. You 618 00:39:16,360 --> 00:39:20,000 Speaker 1: can have an equitable policy, but if it's not implemented 619 00:39:20,560 --> 00:39:23,279 Speaker 1: in the right way, you may as well not have 620 00:39:23,320 --> 00:39:28,040 Speaker 1: the policy. You know, all together, we're also looking in 621 00:39:28,120 --> 00:39:33,600 Speaker 1: a very honed way at assembling data from different sources 622 00:39:34,080 --> 00:39:37,960 Speaker 1: in ways that can facilitate a better understanding of community 623 00:39:38,000 --> 00:39:39,120 Speaker 1: from an equity lens. 624 00:39:40,000 --> 00:39:41,880 Speaker 2: All right, well, you've been able to tell us a 625 00:39:41,920 --> 00:39:44,840 Speaker 2: lot about you know, kind of your work right now, 626 00:39:44,880 --> 00:39:47,520 Speaker 2: but we do know that you'll there will be a 627 00:39:47,520 --> 00:39:50,200 Speaker 2: finite period of time in which you serve as the 628 00:39:50,280 --> 00:39:54,360 Speaker 2: director of the Senses. And I can tell, with all 629 00:39:54,440 --> 00:39:56,800 Speaker 2: due respect that you're a little bit of a nerd. 630 00:39:56,880 --> 00:39:59,640 Speaker 4: Am I right? Yes, I confess. 631 00:40:01,280 --> 00:40:04,239 Speaker 2: So what do you want the legacy? Your legacy? You're 632 00:40:04,280 --> 00:40:09,040 Speaker 2: the first Latino to lead the Senses. You're the first 633 00:40:09,040 --> 00:40:11,719 Speaker 2: man with a bonytail that we know of in the 634 00:40:11,760 --> 00:40:12,480 Speaker 2: modern ages. 635 00:40:13,200 --> 00:40:14,759 Speaker 4: So what do you want your legacy to be? 636 00:40:15,320 --> 00:40:18,160 Speaker 1: It's interesting people keep asking me that, and I keep 637 00:40:18,200 --> 00:40:22,239 Speaker 1: telling them I am not that type of leader, don't. 638 00:40:22,480 --> 00:40:25,839 Speaker 1: I don't want to leave the Census Bureau? And folks say, well, 639 00:40:25,920 --> 00:40:28,800 Speaker 1: Rob did X, Rob did Y, and Rob did C. 640 00:40:29,440 --> 00:40:33,120 Speaker 1: I would much rather because of who I am and 641 00:40:33,239 --> 00:40:38,040 Speaker 1: my belief in how I lead to enable all kinds 642 00:40:38,040 --> 00:40:41,920 Speaker 1: of staff to do great things, and then to help 643 00:40:41,960 --> 00:40:47,480 Speaker 1: them find the resources, to be innovative, to tangibly demonstrate 644 00:40:47,560 --> 00:40:50,800 Speaker 1: what it means to live in an equitable work environment. 645 00:40:51,400 --> 00:40:53,680 Speaker 1: So my legacy, if you look at it from the 646 00:40:53,760 --> 00:40:57,799 Speaker 1: in that sense, isn't going to be an accomplishment as 647 00:40:57,880 --> 00:41:04,000 Speaker 1: much as a driver to allow people to become excellent 648 00:41:04,320 --> 00:41:09,200 Speaker 1: in the context of diversity, equity, and inclusion. And that's 649 00:41:09,200 --> 00:41:11,920 Speaker 1: what my legacy. I want my legacy to be. I 650 00:41:12,000 --> 00:41:15,279 Speaker 1: helped people do their job better well. 651 00:41:15,440 --> 00:41:20,040 Speaker 4: Director Robert Roberto Santos, thank you so much for joining 652 00:41:20,080 --> 00:41:21,000 Speaker 4: me on Let You Know USA. 653 00:41:22,120 --> 00:41:25,719 Speaker 1: It was an absolute honor, Maria, and thank you very 654 00:41:25,800 --> 00:41:32,880 Speaker 1: much for this opportunity to let folks know who I am. 655 00:41:33,000 --> 00:41:37,360 Speaker 2: Since my conversation with Director Santos, the White House Office 656 00:41:37,400 --> 00:41:40,440 Speaker 2: of Management and Budget announced that it has started a 657 00:41:40,480 --> 00:41:46,000 Speaker 2: formal review in order to revise the race and Ethnicity classifications. 658 00:41:46,640 --> 00:41:50,880 Speaker 2: It uses these to collect data across federal agencies to 659 00:41:51,000 --> 00:41:56,120 Speaker 2: quote better reflect the diversity of the American people end quote. 660 00:41:56,280 --> 00:42:01,000 Speaker 2: These classifications have not been revised since nine Team ninety seven. 661 00:42:16,560 --> 00:42:20,360 Speaker 2: This episode was produced by Renaldo Leanos Junior and edited by. 662 00:42:20,239 --> 00:42:21,400 Speaker 4: Julio Ricardo Barella. 663 00:42:21,760 --> 00:42:25,480 Speaker 2: It was mixed by Stefane Lebau and Julia Caruso. The 664 00:42:25,600 --> 00:42:31,640 Speaker 2: Latino USA team includes Andrea Lopez Grusado, Marta Martinez, Daisy Contreres, 665 00:42:31,760 --> 00:42:37,560 Speaker 2: Mike Sergent, Julieta Martinelli, Victoriestrera, Alejandra Sarrassa, Patricia Sulvan and 666 00:42:37,600 --> 00:42:41,840 Speaker 2: Julia Rocha, with help from Raoul Pees. Our associate engineers 667 00:42:41,960 --> 00:42:46,360 Speaker 2: are gabriel A. Bias and JJ Carubin. Our marketing manager 668 00:42:46,480 --> 00:42:50,520 Speaker 2: is Luis Luna. Our theme music was composed by Zane Rubinos. 669 00:42:50,640 --> 00:42:53,600 Speaker 2: I'm your host and executive producer Mario Josa joins again 670 00:42:53,600 --> 00:42:56,520 Speaker 2: on our next episode, and remember not tevayas and I'll 671 00:42:56,520 --> 00:42:59,240 Speaker 2: see you on all of our social media aste. 672 00:42:59,280 --> 00:43:05,040 Speaker 5: La Proxima Joe Latino USA is made possible in part 673 00:43:05,120 --> 00:43:10,600 Speaker 5: by W. K. Kellogg Foundation, a partner with communities where 674 00:43:10,680 --> 00:43:16,759 Speaker 5: children come first, the Heising Simons Foundation Unlocking Knowledge, opportunity 675 00:43:17,000 --> 00:43:23,400 Speaker 5: and possibilities more at hsfoundation dot org and the John D. 676 00:43:23,680 --> 00:43:25,440 Speaker 5: And Catherine T. MacArthur Foundation. 677 00:43:29,400 --> 00:43:31,880 Speaker 2: And by the way, I hear you're a big griller 678 00:43:32,160 --> 00:43:33,880 Speaker 2: and you love to barbecue, and I'm like, okay, I 679 00:43:33,960 --> 00:43:37,520 Speaker 2: want to be invited to that barbecue, Director Santos, Okay, 680 00:43:38,120 --> 00:43:40,840 Speaker 2: that's the barbecue I want to be invited to. Yours 681 00:43:41,320 --> 00:43:44,520 Speaker 2: your open invitation, Jean san Antonio barbecue. 682 00:43:44,800 --> 00:43:45,320 Speaker 4: But anyway,