1 00:00:15,356 --> 00:00:22,356 Speaker 1: Pushkin. Once upon a time in the middle of the 2 00:00:22,436 --> 00:00:25,556 Speaker 1: nineteen eighties, when the Cold War still raged and a 3 00:00:25,596 --> 00:00:28,636 Speaker 1: man named Ronald Reagan occupied the White House, there were 4 00:00:28,676 --> 00:00:33,116 Speaker 1: three major weekly news magazines in the United States. Time 5 00:00:33,196 --> 00:00:36,796 Speaker 1: Magazine was number one, with millions upon millions of copies 6 00:00:36,836 --> 00:00:42,156 Speaker 1: in circulation, Newsweek was number two, and What News Magazine 7 00:00:42,196 --> 00:00:46,716 Speaker 1: came in third place, a sleepy little publication based in Washington, 8 00:00:46,796 --> 00:00:52,516 Speaker 1: DC known as US News and World Report. One of 9 00:00:52,516 --> 00:00:56,916 Speaker 1: the magazine's managing editors in those years, Peter Bernstein, remembers 10 00:00:56,916 --> 00:00:58,396 Speaker 1: the day when everything changed. 11 00:00:58,956 --> 00:01:02,436 Speaker 2: It was a very exciting time. I mean, because Moore 12 00:01:02,556 --> 00:01:05,516 Speaker 2: had just taken over. There were a lot of people buzzing. 13 00:01:05,156 --> 00:01:11,436 Speaker 1: Around mort being Mortimer B. Zuckerman, a Canadian billionaire who 14 00:01:11,436 --> 00:01:14,436 Speaker 1: bought US News and Will Report with dreams of becoming 15 00:01:14,516 --> 00:01:15,356 Speaker 1: a media baron. 16 00:01:15,916 --> 00:01:19,276 Speaker 2: There are a ton of really good ideas sort of 17 00:01:19,316 --> 00:01:21,916 Speaker 2: in the magazine, and I think it's fair to say 18 00:01:21,956 --> 00:01:25,076 Speaker 2: our feeling was that the execution could have been a 19 00:01:25,156 --> 00:01:27,556 Speaker 2: lot better. And one of the things we wanted to 20 00:01:27,596 --> 00:01:30,356 Speaker 2: do was distinguish ourselves from Time and Newsweek, because we 21 00:01:30,356 --> 00:01:31,796 Speaker 2: were the third. 22 00:01:33,836 --> 00:01:37,276 Speaker 1: And how do you distinguish yourself if you're always coming 23 00:01:37,316 --> 00:01:40,956 Speaker 1: in third. If a Canadian billionaire with visions of grandeur 24 00:01:41,316 --> 00:01:46,236 Speaker 1: is breathing down your neck, you do something audacious. You 25 00:01:46,356 --> 00:01:50,796 Speaker 1: create something that no educated parent could possibly ignore, a 26 00:01:50,836 --> 00:01:55,516 Speaker 1: scheme to examine every American college and university and rank 27 00:01:55,596 --> 00:01:59,596 Speaker 1: them from top to bottom. 28 00:01:59,956 --> 00:02:03,796 Speaker 2: We were looking to reinvent the magazine, and the college 29 00:02:03,876 --> 00:02:06,276 Speaker 2: rankings became part of that. 30 00:02:06,796 --> 00:02:09,716 Speaker 1: So Bernstein and his colleagues began collecting a mountain of 31 00:02:09,716 --> 00:02:12,796 Speaker 1: statistics on the universities and colleges of the United States. 32 00:02:13,356 --> 00:02:15,796 Speaker 1: To make sense of those numbers, they came up with 33 00:02:15,796 --> 00:02:19,716 Speaker 1: an algorithm, a secret algorithm that could assign every school 34 00:02:19,796 --> 00:02:23,556 Speaker 1: a score of one through one hundred, regardless of its size, 35 00:02:23,636 --> 00:02:27,996 Speaker 1: or mission or complexity, an algorithm to capture the elusive 36 00:02:28,116 --> 00:02:30,316 Speaker 1: quality of academic excellence. 37 00:02:31,036 --> 00:02:35,596 Speaker 2: Finding those points of data and putting them into a ranking, 38 00:02:35,956 --> 00:02:42,116 Speaker 2: as you can appreciate, is a complicated task. Yes, full 39 00:02:42,156 --> 00:02:50,076 Speaker 2: of value, judgments, full of problems, challenges, dangers, But we 40 00:02:50,076 --> 00:02:53,876 Speaker 2: were undaunted and precede it. 41 00:02:55,116 --> 00:02:56,356 Speaker 1: I love that you're laughing about this. 42 00:02:56,916 --> 00:03:00,596 Speaker 2: It was a very heady time, and we thought, and 43 00:03:00,716 --> 00:03:03,596 Speaker 2: we did a rarely challenge time in news. We get 44 00:03:03,596 --> 00:03:04,076 Speaker 2: their game. 45 00:03:06,276 --> 00:03:11,316 Speaker 1: The rankings became an institution. This news surged, careers were forged, 46 00:03:11,636 --> 00:03:14,996 Speaker 1: fortunes made. I mean, what's fasci today is that time 47 00:03:15,036 --> 00:03:19,036 Speaker 1: and newsic have basically disappeared. The rest of US News 48 00:03:19,036 --> 00:03:21,996 Speaker 1: has basically disappeared. But the rankings are as strong as ever. 49 00:03:22,716 --> 00:03:26,396 Speaker 2: Well, it's nice to know in this world of effemera 50 00:03:26,516 --> 00:03:32,156 Speaker 2: that something can last. But and as a journalist, you 51 00:03:32,196 --> 00:03:36,196 Speaker 2: know who you know when your work is used for 52 00:03:36,196 --> 00:03:39,716 Speaker 2: for old fish after a day, it's nice to see 53 00:03:39,716 --> 00:03:41,756 Speaker 2: that something hasn't impact for a while. 54 00:03:44,236 --> 00:03:47,196 Speaker 1: Peter left US News long ago, but he and his 55 00:03:47,236 --> 00:03:50,796 Speaker 1: colleagues had added something new to the American academic calendar 56 00:03:51,196 --> 00:03:56,036 Speaker 1: beyond freshman week, finals commencement. There's now the day the 57 00:03:56,116 --> 00:03:57,396 Speaker 1: new rankings come out. 58 00:03:57,636 --> 00:04:00,996 Speaker 3: The new thirtieth edition of Best Colleges was just released 59 00:04:00,996 --> 00:04:02,636 Speaker 3: this morning, and we've got it. 60 00:04:02,756 --> 00:04:04,276 Speaker 4: You're seeing the two thousand. 61 00:04:03,996 --> 00:04:07,276 Speaker 5: And the list for twenty nineteen was Princeton University, followed 62 00:04:07,276 --> 00:04:08,556 Speaker 5: by Harvard Tied. 63 00:04:09,116 --> 00:04:12,356 Speaker 6: Scholars of America's best colleges have been revealed. The US 64 00:04:12,436 --> 00:04:14,876 Speaker 6: News and World Report is out with its angle list, 65 00:04:14,956 --> 00:04:17,076 Speaker 6: and we've got the inside scoop on how. 66 00:04:17,156 --> 00:04:20,916 Speaker 1: The algorithm that's developed is undergoing a constant state of 67 00:04:20,956 --> 00:04:23,876 Speaker 1: evolution over the years. How often are you tweaking it? 68 00:04:24,756 --> 00:04:27,156 Speaker 2: I thought you might ask about this. I mean I 69 00:04:27,196 --> 00:04:30,676 Speaker 2: did go online and look at it, and I was 70 00:04:30,676 --> 00:04:33,756 Speaker 2: glad to see they are tweaking it on a regular basis, 71 00:04:33,796 --> 00:04:36,836 Speaker 2: at least it looking if you look at their methodology. 72 00:04:37,116 --> 00:04:40,676 Speaker 2: And of course they've also been reacting to competition. I mean, 73 00:04:41,116 --> 00:04:43,756 Speaker 2: you know a lot of people have been critical of 74 00:04:43,796 --> 00:04:48,196 Speaker 2: the rankings and whether this mythology really this methodology? 75 00:04:48,396 --> 00:04:51,796 Speaker 1: Excuse me, that's it, Peter. That is like the definition 76 00:04:51,836 --> 00:04:55,596 Speaker 1: of a Freudian slip. You're talking about your you're talking 77 00:04:55,636 --> 00:04:59,436 Speaker 1: about your brain child, and you refer to it as mythology. 78 00:05:01,636 --> 00:05:05,716 Speaker 2: That's true. I couldn't have come up with that one consciously. 79 00:05:06,876 --> 00:05:12,156 Speaker 1: At what point did the US news methodology become a mythology? 80 00:05:13,196 --> 00:05:18,476 Speaker 1: Let's find out. My name is Malcolm Gladwell. You're listening 81 00:05:18,556 --> 00:05:23,076 Speaker 1: to my podcast, Revisionist History about Things Overlooked and Misunderstood. 82 00:05:25,316 --> 00:05:27,596 Speaker 1: In this episode, I ask, how is it that a 83 00:05:27,636 --> 00:05:30,836 Speaker 1: promotional gimmick from the nineteen eighties turned into a fetish 84 00:05:30,916 --> 00:05:39,076 Speaker 1: object for American higher education? How do these rankings work 85 00:05:39,596 --> 00:05:42,796 Speaker 1: and why does everyone take them so seriously? We're going 86 00:05:42,876 --> 00:05:46,276 Speaker 1: to launch a revisionist history investigation, one that will take 87 00:05:46,356 --> 00:05:49,716 Speaker 1: us to all kinds of strange places, to the bond markets, 88 00:05:50,116 --> 00:05:54,556 Speaker 1: to Portland, Oregon, to New Orleans. We'll meet a mysterious 89 00:05:54,556 --> 00:05:58,596 Speaker 1: college administrator who asked to be identified only as Dean, 90 00:05:59,236 --> 00:06:02,316 Speaker 1: as well as a band of hackers who agreed to 91 00:06:02,356 --> 00:06:08,476 Speaker 1: join our cause. All right, all right, so we're ready 92 00:06:08,516 --> 00:06:11,836 Speaker 1: to go this very now. Before we start, can both 93 00:06:11,876 --> 00:06:14,716 Speaker 1: of you guys introduce yourselves. 94 00:06:15,836 --> 00:06:19,476 Speaker 5: So I'm Kelly McConville, and I'm an assistant professor of 95 00:06:19,516 --> 00:06:21,356 Speaker 5: statistics at Reed College. 96 00:06:21,676 --> 00:06:25,396 Speaker 4: I'm playing too, and I'm an international student who is 97 00:06:25,436 --> 00:06:28,676 Speaker 4: currently studying at UNC's High school. 98 00:06:29,036 --> 00:06:31,996 Speaker 1: So these are some of my accomplices, and here's why 99 00:06:32,036 --> 00:06:35,476 Speaker 1: I needed them. Us News will tell you what variables 100 00:06:35,516 --> 00:06:38,516 Speaker 1: they use to determine whether a school is good or mediocre, 101 00:06:38,876 --> 00:06:42,756 Speaker 1: but they won't disclose exactly how they combine those variables 102 00:06:42,796 --> 00:06:46,396 Speaker 1: into a score. I mean, why would they. It's their 103 00:06:46,476 --> 00:06:50,196 Speaker 1: secret Sauce they charged forty dollars a year for premium 104 00:06:50,236 --> 00:06:53,916 Speaker 1: access to their findings. This is a big business. So 105 00:06:53,956 --> 00:06:56,516 Speaker 1: I figured my only chance at really getting under the 106 00:06:56,516 --> 00:06:58,996 Speaker 1: hood of the ranking algorithm was to find out if 107 00:06:58,996 --> 00:07:03,516 Speaker 1: anyone had in effect hacked the algorithm, and it turns 108 00:07:03,556 --> 00:07:06,956 Speaker 1: out someone had. It was a group of students at Reed, 109 00:07:07,236 --> 00:07:10,596 Speaker 1: a small liberal arts college in Portland, under the leadership 110 00:07:10,596 --> 00:07:15,156 Speaker 1: of their professor Kelly mcconvill. Tell me how on earth 111 00:07:16,036 --> 00:07:19,396 Speaker 1: this whole project of looking at US News rankings? How 112 00:07:19,396 --> 00:07:19,996 Speaker 1: did it begin? 113 00:07:21,196 --> 00:07:21,356 Speaker 4: So? 114 00:07:21,876 --> 00:07:26,476 Speaker 5: I teach a course called Statistics Practicum, and in that course, 115 00:07:26,516 --> 00:07:31,356 Speaker 5: the students complete a semester long empirical research project, and 116 00:07:31,636 --> 00:07:34,676 Speaker 5: I solicit those projects and the data from other READ 117 00:07:34,756 --> 00:07:36,076 Speaker 5: faculty and staff. 118 00:07:36,956 --> 00:07:39,556 Speaker 1: Every year, US News asks for a lot of data 119 00:07:39,556 --> 00:07:43,876 Speaker 1: from schools, but the Read administration had stopped supplying that data. 120 00:07:44,356 --> 00:07:47,676 Speaker 1: They decided they didn't believe in the rankings anymore. But 121 00:07:47,796 --> 00:07:50,996 Speaker 1: still the magazine kept generating a ranking for Read anyway, 122 00:07:51,476 --> 00:07:54,276 Speaker 1: and someone in the Read administration came to Kelly McConville 123 00:07:54,276 --> 00:07:57,796 Speaker 1: and said, ever since we dropped out, our US News 124 00:07:57,836 --> 00:08:01,996 Speaker 1: ranking has plummeted. We think they've been punishing us. Can 125 00:08:01,996 --> 00:08:03,196 Speaker 1: you double check their math? 126 00:08:03,996 --> 00:08:06,596 Speaker 5: That was our task. We were tasked with recreating the 127 00:08:06,636 --> 00:08:10,076 Speaker 5: model and then seeing what our ranking would be if 128 00:08:10,116 --> 00:08:11,156 Speaker 5: we did supplier data. 129 00:08:11,396 --> 00:08:13,716 Speaker 1: Yeah, So tell me, the two of you walk me 130 00:08:13,796 --> 00:08:18,396 Speaker 1: through how does one go about conceptually trying to answer 131 00:08:18,476 --> 00:08:19,076 Speaker 1: this question. 132 00:08:19,916 --> 00:08:22,196 Speaker 5: They use a model that's called a weight in some 133 00:08:22,436 --> 00:08:27,116 Speaker 5: model that means they take about twenty or so different 134 00:08:27,116 --> 00:08:30,916 Speaker 5: factors about a school, like class size and graduation rates. 135 00:08:31,756 --> 00:08:34,996 Speaker 5: They wait each of those factors based on how important 136 00:08:35,716 --> 00:08:39,036 Speaker 5: they think the factor is, and then they sum up 137 00:08:39,036 --> 00:08:41,636 Speaker 5: all those pieces and then calibrate it so that the 138 00:08:41,716 --> 00:08:44,436 Speaker 5: highest scores at one hundred, and then based on those scores, 139 00:08:44,436 --> 00:08:45,716 Speaker 5: they rank as schools. 140 00:08:47,036 --> 00:08:48,876 Speaker 1: The Red team had to build their own version of 141 00:08:48,916 --> 00:08:52,356 Speaker 1: the US News algorithm from scratch, trying to get as 142 00:08:52,476 --> 00:08:53,916 Speaker 1: close to it as possible. 143 00:08:54,956 --> 00:08:59,276 Speaker 5: We grabbed all the variables we could from open government sources, 144 00:09:00,076 --> 00:09:03,716 Speaker 5: and we built a model that isn't trying to recreate 145 00:09:03,836 --> 00:09:07,516 Speaker 5: the US newswait in some model. Instead, it's just trying 146 00:09:07,516 --> 00:09:10,316 Speaker 5: to predict the US New score of a school with 147 00:09:10,356 --> 00:09:11,716 Speaker 5: a high degree of accuracy. 148 00:09:13,236 --> 00:09:14,916 Speaker 1: Whying how close did you get? 149 00:09:15,796 --> 00:09:20,316 Speaker 4: I'll say fairly close. The only school that's outside of 150 00:09:20,476 --> 00:09:23,596 Speaker 4: like a reasonable range of predictive score in the test 151 00:09:23,636 --> 00:09:26,316 Speaker 4: status read oh really, And all other schools are like 152 00:09:26,916 --> 00:09:32,236 Speaker 4: within a reasonable prediction interval of their scores. 153 00:09:33,196 --> 00:09:37,476 Speaker 1: Meaning the Reed students identical twin algorithm is so good 154 00:09:37,796 --> 00:09:40,596 Speaker 1: that when they run their rankings of American colleges. Their 155 00:09:40,636 --> 00:09:44,996 Speaker 1: list looks almost exactly like the US News list, with 156 00:09:45,036 --> 00:09:49,996 Speaker 1: one exception Read College. Wait, so they were messing. 157 00:09:49,676 --> 00:09:54,196 Speaker 4: With you based on our finding, it seems reasonable they 158 00:09:54,316 --> 00:09:54,916 Speaker 4: this something. 159 00:09:56,476 --> 00:10:01,356 Speaker 1: In twenty nineteen, US News put Read in ninetieth place. 160 00:10:02,596 --> 00:10:04,756 Speaker 1: Where do you think you should be ranked? 161 00:10:06,596 --> 00:10:08,796 Speaker 4: Thirty sixth Oh? 162 00:10:09,316 --> 00:10:13,836 Speaker 1: Wait? What that much of a difference? Yeah, that's bananas. 163 00:10:14,316 --> 00:10:17,596 Speaker 1: Oh my, oh, they really did a number on Reed. 164 00:10:21,436 --> 00:10:23,956 Speaker 1: Now we don't need to go much further into the 165 00:10:24,036 --> 00:10:27,756 Speaker 1: ensuing beef between Read and US News. The magazine calls 166 00:10:27,796 --> 00:10:33,236 Speaker 1: the undergraduates analysis quote inaccurate. But just imagine my joy 167 00:10:33,236 --> 00:10:36,876 Speaker 1: when I ran across Swaying's analysis. Here. I was searching 168 00:10:36,916 --> 00:10:40,276 Speaker 1: for some way to understand the secret algorithm cooked up 169 00:10:40,316 --> 00:10:43,036 Speaker 1: by Peter Bernstein and his pals back in the nineteen eighties, 170 00:10:43,356 --> 00:10:46,356 Speaker 1: and lo and behold, a bunch of undergraduates at Reed 171 00:10:46,436 --> 00:10:50,396 Speaker 1: College had cracked the code. And were they motivated to 172 00:10:50,436 --> 00:10:56,836 Speaker 1: help me? Absolutely? Because US News dissed their school. My 173 00:10:56,916 --> 00:11:00,116 Speaker 1: first question to Kelly and her team was where should 174 00:11:00,116 --> 00:11:03,716 Speaker 1: I start? And they said start with a little something 175 00:11:04,036 --> 00:11:07,876 Speaker 1: called the peer Assessment score. Can you give me a 176 00:11:07,876 --> 00:11:10,756 Speaker 1: more precise sort of statistic sense of just how important 177 00:11:10,956 --> 00:11:11,236 Speaker 1: is it? 178 00:11:12,076 --> 00:11:16,916 Speaker 4: Like, okay, So we find that the pure assessment score 179 00:11:17,516 --> 00:11:22,276 Speaker 4: has the largest effects, So it has a coefficient of 180 00:11:22,356 --> 00:11:26,116 Speaker 4: like six point five eight. In other words, like, if 181 00:11:26,116 --> 00:11:30,316 Speaker 4: you hold everything else constant and you like increase the 182 00:11:30,396 --> 00:11:35,516 Speaker 4: peer assessment scorer by one unit, your overall score will 183 00:11:35,556 --> 00:11:38,476 Speaker 4: increase by six point five to eight. 184 00:11:39,516 --> 00:11:42,836 Speaker 1: The peer assessment score was at the heart of the 185 00:11:42,916 --> 00:11:47,276 Speaker 1: US News secret sauce, a measure of reputation, one of 186 00:11:47,356 --> 00:11:51,076 Speaker 1: the most powerful elements in the whole ranking system. So 187 00:11:51,196 --> 00:11:55,836 Speaker 1: if I'm a school and I'm anxious to move up 188 00:11:55,876 --> 00:11:57,916 Speaker 1: the US News rankings, the thing I should really be 189 00:11:57,996 --> 00:12:00,716 Speaker 1: focused on is trying to boost my reputation score. 190 00:12:02,116 --> 00:12:02,356 Speaker 4: Yeah. 191 00:12:02,596 --> 00:12:06,636 Speaker 1: Yeah, I had my marching orders, and I knew where 192 00:12:06,676 --> 00:12:09,516 Speaker 1: I had to go. Next to the guardian of the 193 00:12:09,676 --> 00:12:13,036 Speaker 1: US newsgates that dragon at the mouth of the cave. 194 00:12:14,236 --> 00:12:28,116 Speaker 1: Robert Morse. Robert Morse, the man who runs the US 195 00:12:28,236 --> 00:12:33,196 Speaker 1: News rankings, is an older man, white hair, very preppy, nice, 196 00:12:33,516 --> 00:12:37,796 Speaker 1: if a bit lugubrious, heavy hangs the head that where's 197 00:12:37,836 --> 00:12:41,436 Speaker 1: the crown? I called him up. I wanted to understand 198 00:12:41,876 --> 00:12:45,956 Speaker 1: the mysterious variable that the read College hackers had told 199 00:12:45,996 --> 00:12:49,956 Speaker 1: me was so important? Describe again, how is the reputation 200 00:12:50,196 --> 00:12:51,876 Speaker 1: score generated? 201 00:12:52,636 --> 00:12:57,316 Speaker 7: So we send out three surveys per school, and then 202 00:12:57,356 --> 00:13:00,916 Speaker 7: they respond. They rate the schools on a scale of 203 00:13:01,076 --> 00:13:03,476 Speaker 7: five to one or no response. 204 00:13:04,076 --> 00:13:06,196 Speaker 1: So who are the three people at each school who 205 00:13:06,596 --> 00:13:09,316 Speaker 1: are asked to fill out the survey. 206 00:13:09,356 --> 00:13:13,796 Speaker 7: In the provos and the enrollment manager or the head 207 00:13:13,796 --> 00:13:14,676 Speaker 7: of admissions. 208 00:13:15,516 --> 00:13:18,916 Speaker 1: The surveys arrive via email once a year to everyone 209 00:13:18,916 --> 00:13:21,796 Speaker 1: who matters in American Higher ed. If you're at a 210 00:13:21,836 --> 00:13:24,236 Speaker 1: liberal arts college, you're given a list of all two 211 00:13:24,356 --> 00:13:28,356 Speaker 1: hundred and twenty two other liberal arts colleges in your category. 212 00:13:28,436 --> 00:13:30,796 Speaker 1: If you're part of a big university, you get a 213 00:13:30,836 --> 00:13:33,756 Speaker 1: list of the three hundred and eighty eight other big 214 00:13:33,876 --> 00:13:37,556 Speaker 1: universities in the United States. Your job is to rank 215 00:13:37,596 --> 00:13:39,916 Speaker 1: the schools on your list on a scale of one 216 00:13:39,956 --> 00:13:45,316 Speaker 1: to five, five being amazing, one being there's a serious 217 00:13:45,316 --> 00:13:50,196 Speaker 1: problem here. And on what basis are people making those judgments? 218 00:13:50,756 --> 00:13:53,476 Speaker 7: Well, that's a good question. I mean, we ask them 219 00:13:53,516 --> 00:13:56,996 Speaker 7: to base it on their view of the school's reputation 220 00:13:57,196 --> 00:13:59,676 Speaker 7: for undergraduate academic quality. 221 00:14:00,076 --> 00:14:01,236 Speaker 1: But I mean, how would you know. 222 00:14:03,676 --> 00:14:07,276 Speaker 7: I mean, we believe that to aggregate sum of all 223 00:14:07,356 --> 00:14:11,116 Speaker 7: the raiders who are a leader is in higher education. 224 00:14:11,996 --> 00:14:14,516 Speaker 7: You know their presidents and provosts and mission deans. So 225 00:14:14,596 --> 00:14:18,356 Speaker 7: they're not rookies. When you aggregate their views at any 226 00:14:18,396 --> 00:14:24,996 Speaker 7: given time, they're representing where those schools stand in the marketplace. 227 00:14:25,716 --> 00:14:29,836 Speaker 1: I mean, so it's it's an assessment of their feelings 228 00:14:30,396 --> 00:14:31,276 Speaker 1: what other schools. 229 00:14:33,036 --> 00:14:36,716 Speaker 7: Well, they're leaders in higher education, so it's based on 230 00:14:36,836 --> 00:14:42,756 Speaker 7: their knowledge of the other schools that they've gathered or 231 00:14:42,796 --> 00:14:48,516 Speaker 7: through meetings or for exposure. Do they necessarily know a 232 00:14:48,556 --> 00:14:51,956 Speaker 7: lot about all the schools they're rating. I don't know. 233 00:14:52,596 --> 00:14:55,556 Speaker 1: If I rate a restaurant on Yelp, it's because I've 234 00:14:55,556 --> 00:15:03,036 Speaker 1: eaten there, right, yes, But here, when I rate a 235 00:15:03,196 --> 00:15:06,396 Speaker 1: university on the US News ranking, it's not because I've 236 00:15:06,636 --> 00:15:08,396 Speaker 1: attended that university or taught there. 237 00:15:09,276 --> 00:15:12,436 Speaker 7: It's just, well, you may have. We shouldn't say that 238 00:15:12,516 --> 00:15:15,356 Speaker 7: you didn't. But you're saying, have the people who rated 239 00:15:15,396 --> 00:15:19,396 Speaker 7: the schools been on every campus or taught at that 240 00:15:19,516 --> 00:15:22,756 Speaker 7: school or no? In depth their course catalog? 241 00:15:23,036 --> 00:15:23,116 Speaker 4: No. 242 00:15:23,716 --> 00:15:26,836 Speaker 7: Do some of them have greater degrees of knowledge about 243 00:15:26,836 --> 00:15:29,996 Speaker 7: the schools they're rating, yes? Do some of them have 244 00:15:30,236 --> 00:15:34,036 Speaker 7: lesser degrees of knowledge? Yes? So I think it varies 245 00:15:34,116 --> 00:15:38,276 Speaker 7: from having substantial knowledge to far less knowledge. 246 00:15:39,156 --> 00:15:41,516 Speaker 1: In my naivete, I had imagined that there would be 247 00:15:41,556 --> 00:15:43,956 Speaker 1: some level of rigor to this crucial variable in the 248 00:15:44,036 --> 00:15:47,316 Speaker 1: US news wait, in some model a methodology that I 249 00:15:47,316 --> 00:15:53,196 Speaker 1: could study, analyze, learn from. But Morse wasn't being very helpful, 250 00:15:53,756 --> 00:15:56,276 Speaker 1: so I tried to draw him out. I mean, I 251 00:15:56,356 --> 00:16:01,716 Speaker 1: was fascinated that there's a little clump where BYU Bring 252 00:16:01,756 --> 00:16:06,716 Speaker 1: them Young, Yeshiva and Gonzaga are all ranked right in 253 00:16:06,756 --> 00:16:10,796 Speaker 1: the same roughly equally in the National University's rank. So 254 00:16:10,876 --> 00:16:15,356 Speaker 1: a Mormon school, Conservative Jewish school, and the Jesuit school. 255 00:16:16,236 --> 00:16:20,516 Speaker 1: And I was trying to think, what is the rabbi 256 00:16:20,596 --> 00:16:23,076 Speaker 1: who runs Yeshiva know about bring them Young? And what 257 00:16:23,116 --> 00:16:28,556 Speaker 1: does the Jesuit priest who runs Gonzaga know about Yeshiva? 258 00:16:28,636 --> 00:16:33,596 Speaker 1: And it's a good point, like is Gonzaga giving George 259 00:16:33,596 --> 00:16:36,396 Speaker 1: ten of five and giving Boston College a five? 260 00:16:36,516 --> 00:16:40,196 Speaker 7: And we're not looking at how people are rating other schools. 261 00:16:40,356 --> 00:16:43,316 Speaker 7: We are doing a trim means, so we take off 262 00:16:43,356 --> 00:16:46,556 Speaker 7: a few of the highest ratings and a few of 263 00:16:46,556 --> 00:16:51,956 Speaker 7: the lowest ratings in an effort to eliminate some of 264 00:16:51,996 --> 00:16:57,036 Speaker 7: the strategic voting that you're alluding to well, I. 265 00:16:56,996 --> 00:16:59,076 Speaker 1: Don't know if that's strategic voting. I'm wondering if it's 266 00:16:59,116 --> 00:17:04,796 Speaker 1: just that. If I'm president of Gonzaga, I'm powerfully motivated 267 00:17:04,836 --> 00:17:07,996 Speaker 1: to believe that the Jesuit education is the best education 268 00:17:08,076 --> 00:17:11,076 Speaker 1: out there. So when I look at Georgetown, I think 269 00:17:11,316 --> 00:17:14,876 Speaker 1: they're doing the right thing. And when I look at Yeshiva, 270 00:17:14,876 --> 00:17:18,796 Speaker 1: I say, where's the New Testament? Why are they not 271 00:17:18,876 --> 00:17:21,116 Speaker 1: using the New Testament? I mean, this is just natural 272 00:17:21,236 --> 00:17:24,116 Speaker 1: human biases. I just don't know what they have to 273 00:17:24,116 --> 00:17:25,476 Speaker 1: do with the quality of the institution. 274 00:17:29,836 --> 00:17:32,396 Speaker 7: Well, I don't have a different answer. 275 00:17:35,956 --> 00:17:39,396 Speaker 1: Devoted listeners of revisionist history. Well, remember how years ago 276 00:17:39,716 --> 00:17:43,876 Speaker 1: I fell for Rowan University in New Jersey. I love Rowin, 277 00:17:44,596 --> 00:17:48,036 Speaker 1: But Rowan is ranked one hundred and eighty seventh in 278 00:17:48,116 --> 00:17:53,596 Speaker 1: the National University's list dismal mediocre, and why because its 279 00:17:53,636 --> 00:17:58,436 Speaker 1: peer assessment score is a forgettable two point four? How 280 00:17:58,476 --> 00:18:01,636 Speaker 1: on earth have the University presidence of America come to 281 00:18:01,676 --> 00:18:05,836 Speaker 1: the collective decision that they hate Rowan University way way 282 00:18:05,836 --> 00:18:09,396 Speaker 1: down in South Jersey. I call up Ali hush Mind, 283 00:18:09,636 --> 00:18:13,676 Speaker 1: the school's president. How many university presidents have visited Roan 284 00:18:13,716 --> 00:18:16,116 Speaker 1: in the last five years from other colleges. 285 00:18:16,236 --> 00:18:21,756 Speaker 8: Oh, two or three, one from Canada, one came who 286 00:18:21,916 --> 00:18:24,996 Speaker 8: was part of an accreditation and I believe another one 287 00:18:25,076 --> 00:18:25,556 Speaker 8: was a friend. 288 00:18:26,556 --> 00:18:30,956 Speaker 1: That's it. Yes, So when they're giving you a score, 289 00:18:31,196 --> 00:18:34,036 Speaker 1: on what basis are they using forgiving you? How do 290 00:18:34,116 --> 00:18:35,476 Speaker 1: they know anything at all about Roan? 291 00:18:35,916 --> 00:18:36,636 Speaker 7: Again, I don't know. 292 00:18:36,756 --> 00:18:39,156 Speaker 8: I can only speak for myself. I can assure you 293 00:18:39,196 --> 00:18:43,876 Speaker 8: that I really don't know much about the institutions that 294 00:18:43,876 --> 00:18:45,636 Speaker 8: I'm asked to rank or score. 295 00:18:45,716 --> 00:18:47,276 Speaker 3: I just don't have enough tools. 296 00:18:48,396 --> 00:18:52,596 Speaker 1: Now. It's not like university presidents don't know anything about grading. 297 00:18:53,076 --> 00:18:55,956 Speaker 1: They were all teachers themselves once. But when it comes 298 00:18:55,956 --> 00:18:59,516 Speaker 1: to grading schools, it seems like they might just be 299 00:18:59,596 --> 00:19:02,476 Speaker 1: mailing it in. Next, I called up the head of 300 00:19:02,516 --> 00:19:06,116 Speaker 1: admissions at a major university. You've heard of it, trust me, 301 00:19:06,636 --> 00:19:08,516 Speaker 1: but I can't tell you what it is. And we 302 00:19:08,596 --> 00:19:11,756 Speaker 1: altered the voice to protect this person's identity. Of course 303 00:19:11,796 --> 00:19:15,076 Speaker 1: we did. We had to look how US News treated 304 00:19:15,116 --> 00:19:19,276 Speaker 1: read college. My source told me to address them only 305 00:19:19,756 --> 00:19:20,316 Speaker 1: as dean. 306 00:19:20,996 --> 00:19:25,556 Speaker 9: I am certain and I am far more qualified to 307 00:19:25,556 --> 00:19:28,796 Speaker 9: be a member of the Baseball Writers Association of America 308 00:19:28,996 --> 00:19:31,356 Speaker 9: and vote on the Hall of Fame than I am 309 00:19:31,516 --> 00:19:34,676 Speaker 9: to assess other institutions for the US News and World Report. 310 00:19:35,076 --> 00:19:35,276 Speaker 4: Yeah. 311 00:19:35,476 --> 00:19:35,676 Speaker 9: Yeah. 312 00:19:36,316 --> 00:19:39,476 Speaker 1: I proposed a Dean that we do an exercise. I'd 313 00:19:39,516 --> 00:19:42,556 Speaker 1: name a school at random, and then the two of 314 00:19:42,636 --> 00:19:48,156 Speaker 1: us would try to peer assess it. Florida State. Never 315 00:19:48,196 --> 00:19:57,036 Speaker 1: been there. I've not been there, I think three point two. Syracuse. Yes, 316 00:19:57,636 --> 00:20:00,156 Speaker 1: I I stopped for coffee there once in a way 317 00:20:00,236 --> 00:20:02,756 Speaker 1: driving back to my mom's house in Canada. I don't 318 00:20:02,756 --> 00:20:04,836 Speaker 1: know if that counts. I don't think it does. I think 319 00:20:05,196 --> 00:20:07,796 Speaker 1: I think it counts account experience. I got to say 320 00:20:07,836 --> 00:20:11,476 Speaker 1: experience the weather, but there's no there were no students there. 321 00:20:11,476 --> 00:20:15,276 Speaker 1: It was Christmas. But I will say this, my cousin 322 00:20:15,356 --> 00:20:17,796 Speaker 1: went to Syracuse and had a good time. 323 00:20:19,036 --> 00:20:22,076 Speaker 9: Oh h and so you would rate it based on that. 324 00:20:23,036 --> 00:20:26,196 Speaker 1: Let's give Syracuse some love. Three point nine, No, four 325 00:20:26,236 --> 00:20:32,756 Speaker 1: point zero. University of Washington in Seattle. Yes, you've been there, 326 00:20:33,436 --> 00:20:35,436 Speaker 1: Yes I have. What'd you do when you were there? 327 00:20:38,236 --> 00:20:39,236 Speaker 9: I walked around? 328 00:20:39,436 --> 00:20:40,276 Speaker 1: I think that counts. 329 00:20:41,076 --> 00:20:42,276 Speaker 7: It counts. 330 00:20:42,796 --> 00:20:45,316 Speaker 1: I said to Dean, you can see the mountains from there, 331 00:20:45,436 --> 00:20:50,116 Speaker 1: the space needle. Let's go big. University of Washington at 332 00:20:50,116 --> 00:20:55,516 Speaker 1: Seattle four point two. Have you ever been to William Mary. 333 00:20:56,716 --> 00:20:58,436 Speaker 7: I have yeah. 334 00:20:58,476 --> 00:21:01,796 Speaker 9: I love history, I love colonial Williamsburg. 335 00:21:02,116 --> 00:21:04,436 Speaker 1: Do you remember what score you gave William and Mary. 336 00:21:06,716 --> 00:21:09,436 Speaker 9: I probably gave them a four or five. 337 00:21:09,996 --> 00:21:13,156 Speaker 1: Really you went for five. It's the second oldest college 338 00:21:13,156 --> 00:21:15,356 Speaker 1: in the US. Do you think that affected your judgment 339 00:21:15,396 --> 00:21:15,676 Speaker 1: on that? 340 00:21:17,036 --> 00:21:17,956 Speaker 9: I'm sure it did. 341 00:21:19,196 --> 00:21:21,476 Speaker 1: Dean and I went on for quite some time. We 342 00:21:21,516 --> 00:21:24,356 Speaker 1: had a long chat about Southern Methodist University in Dallas 343 00:21:24,476 --> 00:21:26,796 Speaker 1: and whether or not the great football team the school 344 00:21:26,876 --> 00:21:29,316 Speaker 1: had in the nineteen eighties should count in their favor. 345 00:21:29,876 --> 00:21:36,156 Speaker 1: Dean said no. I said yes. Now was all this 346 00:21:36,196 --> 00:21:40,036 Speaker 1: a helpful exercise? Not really? But then again, now that 347 00:21:40,236 --> 00:21:43,876 Speaker 1: was my conversation with the Wizard of the Rankings, Robert Morse. 348 00:21:44,756 --> 00:21:46,956 Speaker 1: One suggestion that has been made to me by people 349 00:21:46,996 --> 00:21:49,956 Speaker 1: who do the rankings is that the thing they rely 350 00:21:50,076 --> 00:21:54,996 Speaker 1: on to make their reputation scores for other universities is 351 00:21:55,076 --> 00:21:58,476 Speaker 1: the only source they have of reputation scores for the 352 00:21:58,476 --> 00:22:02,916 Speaker 1: other universities, which is the previous year's US News rankings. 353 00:22:03,356 --> 00:22:04,636 Speaker 1: Is this circular? 354 00:22:05,236 --> 00:22:08,956 Speaker 7: If they're telling you that, then that's not our expectation 355 00:22:09,276 --> 00:22:12,796 Speaker 7: of how people are doing their ratings. Versus looking at 356 00:22:12,796 --> 00:22:17,356 Speaker 7: the ranking table and looking at the score. We believe 357 00:22:17,516 --> 00:22:21,956 Speaker 7: that there's more thought going into it than that, but 358 00:22:22,076 --> 00:22:24,956 Speaker 7: we haven't done any kind of social science research to 359 00:22:26,196 --> 00:22:28,196 Speaker 7: prove or disprove that point. 360 00:22:28,276 --> 00:22:32,796 Speaker 1: You haven't done any right, Yeah, they haven't done any 361 00:22:32,876 --> 00:22:38,836 Speaker 1: social science research. Only one person gave me much insight 362 00:22:38,916 --> 00:22:42,116 Speaker 1: into the mechanics of the peer Assessment score, and that 363 00:22:42,236 --> 00:22:46,476 Speaker 1: was Ali Huschmand, president of Rowan. His advice was, you 364 00:22:46,596 --> 00:22:49,676 Speaker 1: have to take matters into your own hands. So what 365 00:22:49,756 --> 00:22:52,916 Speaker 1: does he do? He makes his own hot sauce. And 366 00:22:52,996 --> 00:22:55,676 Speaker 1: he told me that Rowan sends out free samples to 367 00:22:55,916 --> 00:23:00,076 Speaker 1: every college president in the country. That's not too really 368 00:23:00,676 --> 00:23:01,916 Speaker 1: he did, and he. 369 00:23:01,956 --> 00:23:07,156 Speaker 8: Did no that I make hot sauce. Well, that would 370 00:23:07,236 --> 00:23:08,476 Speaker 8: have been that's scoring. 371 00:23:08,556 --> 00:23:08,956 Speaker 5: I hope. 372 00:23:09,516 --> 00:23:11,636 Speaker 1: Yes. I want to know about your hot sauce. What 373 00:23:11,716 --> 00:23:12,676 Speaker 1: kind of hot sauce do you have? 374 00:23:13,196 --> 00:23:13,356 Speaker 4: Oh? 375 00:23:13,436 --> 00:23:16,156 Speaker 8: I make serious, serious hot sauce. But I actually grow 376 00:23:16,236 --> 00:23:19,356 Speaker 8: from seeds all the way to the packaging. And there 377 00:23:19,356 --> 00:23:22,716 Speaker 8: are three levels of heat. The lowest one is called 378 00:23:22,756 --> 00:23:24,596 Speaker 8: Ali's nasty, which is. 379 00:23:24,596 --> 00:23:25,276 Speaker 4: Kind of mind. 380 00:23:26,076 --> 00:23:28,236 Speaker 8: And then the one next to it, it happened, was 381 00:23:28,276 --> 00:23:32,156 Speaker 8: as a heat it's called a nasty delicious, And then 382 00:23:32,196 --> 00:23:37,596 Speaker 8: the one with Carona Reaper is called nasty vicious, and 383 00:23:37,716 --> 00:23:40,316 Speaker 8: I will send you a package the nasty divisious can 384 00:23:40,396 --> 00:23:40,756 Speaker 8: get you. 385 00:23:41,596 --> 00:23:43,876 Speaker 1: But this isn't gonna help your cause. This is gonna 386 00:23:43,916 --> 00:23:46,876 Speaker 1: hurt your cause. If you're if you're giving some some 387 00:23:47,116 --> 00:23:49,676 Speaker 1: university president in the middle of the Midwest, it's like 388 00:23:49,916 --> 00:23:52,396 Speaker 1: it happens to have a little bit of vicious. They're 389 00:23:52,396 --> 00:23:54,116 Speaker 1: gonna they're gonna curse your name. 390 00:23:54,716 --> 00:23:57,836 Speaker 8: Probably will, but I but I figured that no, no 391 00:23:57,916 --> 00:23:59,676 Speaker 8: publicity is about bad publicity. 392 00:24:01,036 --> 00:24:02,716 Speaker 1: Did I try the nasty vicious? 393 00:24:02,996 --> 00:24:03,156 Speaker 2: Oh? 394 00:24:03,276 --> 00:24:05,756 Speaker 1: Yes, I did, on a scale of one to five 395 00:24:06,836 --> 00:24:18,636 Speaker 1: five point oh. In the middle of my investigation of 396 00:24:18,676 --> 00:24:22,236 Speaker 1: the pure assessment score and its many implications, I had 397 00:24:22,276 --> 00:24:25,636 Speaker 1: a conversation with a professor at Duke named Bill Mayu. 398 00:24:26,516 --> 00:24:29,196 Speaker 1: Mayu is friendly with some bond traders, and he was 399 00:24:29,276 --> 00:24:31,556 Speaker 1: talking with some of them one day when they mentioned 400 00:24:31,556 --> 00:24:34,636 Speaker 1: that they were having difficulty with bonds issued by historically 401 00:24:34,676 --> 00:24:38,116 Speaker 1: black colleges HBCUs as they're known. 402 00:24:38,556 --> 00:24:41,596 Speaker 3: If you're a bond trader, you worry about moving the bonds, 403 00:24:41,636 --> 00:24:44,676 Speaker 3: that you have an inventory, and they just mentioned, you know, hey, 404 00:24:44,716 --> 00:24:47,516 Speaker 3: we're having a really hard time placing these HBCU schools 405 00:24:47,996 --> 00:24:50,036 Speaker 3: because people don't want to hold them. 406 00:24:50,716 --> 00:24:53,476 Speaker 1: The way the bond market works is that an institution 407 00:24:53,916 --> 00:24:56,756 Speaker 1: needs money. Let's say a university wants to build a 408 00:24:56,756 --> 00:25:00,956 Speaker 1: dormitory that costs fifty million dollars. The school can't raise 409 00:25:00,956 --> 00:25:02,996 Speaker 1: all that money on its own, so it goes to 410 00:25:03,036 --> 00:25:06,716 Speaker 1: a Wall Street bank, which purchases a bond a promise 411 00:25:06,836 --> 00:25:11,116 Speaker 1: of repayment from the university. Then the bank breaks that 412 00:25:11,236 --> 00:25:14,876 Speaker 1: bond into many hundreds and hundreds of pieces and sells 413 00:25:14,916 --> 00:25:19,436 Speaker 1: those pieces to wealthy investors or insurance companies or hedge funds. 414 00:25:20,236 --> 00:25:22,636 Speaker 1: So in May you hears that banks are struggling to 415 00:25:22,636 --> 00:25:26,436 Speaker 1: sell bonds for historically black colleges, he wonders, is this 416 00:25:26,596 --> 00:25:31,036 Speaker 1: just some apocryphal Wall Street story or is it true? Luckily, 417 00:25:31,396 --> 00:25:34,676 Speaker 1: there's a simple way attests this. The price the bond 418 00:25:34,716 --> 00:25:38,556 Speaker 1: trader charges is called the gross spread. If it's super 419 00:25:38,556 --> 00:25:41,356 Speaker 1: easy to find buyers for the bonds, the gross spread 420 00:25:41,476 --> 00:25:44,636 Speaker 1: is likely to be low. If the trader has difficulty 421 00:25:44,676 --> 00:25:48,476 Speaker 1: finding buyers, the spread can get quite pricey. So if 422 00:25:48,516 --> 00:25:51,156 Speaker 1: the bonds from black schools are harder to move than 423 00:25:51,236 --> 00:25:54,676 Speaker 1: bonds from white schools, the spread should be higher. And 424 00:25:54,796 --> 00:25:58,636 Speaker 1: are they Yes, they are May you and his colleagues 425 00:25:58,676 --> 00:26:04,156 Speaker 1: compared black schools with non HBCUs that were otherwise identical. 426 00:26:04,956 --> 00:26:08,676 Speaker 1: The spreads for the historically black schools were twenty percent 427 00:26:08,836 --> 00:26:12,036 Speaker 1: higher in the bond market. A twenty percent difference in 428 00:26:12,076 --> 00:26:17,836 Speaker 1: spreads is huge. Mayo and his co researchers then went 429 00:26:17,916 --> 00:26:21,596 Speaker 1: one step further. They zeroed in on three states in 430 00:26:21,676 --> 00:26:26,636 Speaker 1: the Deep South, and those three states were so. 431 00:26:26,516 --> 00:26:31,436 Speaker 3: Those are Louisiana, Mississippi, and Alabama. 432 00:26:31,596 --> 00:26:34,356 Speaker 1: And what's the difference in spread in those states? Not 433 00:26:34,436 --> 00:26:39,316 Speaker 1: twenty percent? Thirty seven percent. Mayo and his colleagues have 434 00:26:39,356 --> 00:26:43,036 Speaker 1: given us a scientifically rigorous measurement of just how much 435 00:26:43,036 --> 00:26:46,316 Speaker 1: of a burdened black institutions face in the real world. 436 00:26:47,596 --> 00:26:50,676 Speaker 1: You've put a number on reputation. What is the reputational 437 00:26:50,716 --> 00:26:56,476 Speaker 1: cost of being a school that overwhelmingly accepts and educates 438 00:26:56,876 --> 00:27:00,676 Speaker 1: black kids in Louisiana. The reputation cost is thirty percent. 439 00:27:01,716 --> 00:27:03,476 Speaker 3: That's one way to think about it. But I would 440 00:27:03,516 --> 00:27:05,596 Speaker 3: say it's the racial component of reputation. 441 00:27:07,036 --> 00:27:11,196 Speaker 1: A spread is a reputation in score, isn't it. Investors 442 00:27:11,236 --> 00:27:13,276 Speaker 1: don't know the precise ins and outs of all the 443 00:27:13,316 --> 00:27:16,796 Speaker 1: institutions they're asked to buy how could they. There are 444 00:27:16,916 --> 00:27:19,996 Speaker 1: literally hundreds of thousands of bonds on a market at 445 00:27:19,996 --> 00:27:23,956 Speaker 1: any given time, So the investors proceed on a feeling, 446 00:27:24,956 --> 00:27:27,276 Speaker 1: a feeling about how worthy and how safe and how 447 00:27:27,356 --> 00:27:30,836 Speaker 1: legitimate the institution getting the loan is. You see a 448 00:27:30,836 --> 00:27:33,996 Speaker 1: black school and you say to yourself, I don't value 449 00:27:33,996 --> 00:27:37,396 Speaker 1: that HBCU quite as highly as the white school across town. 450 00:27:38,156 --> 00:27:41,356 Speaker 1: So you give the black school a discount, which is 451 00:27:41,356 --> 00:27:45,276 Speaker 1: what prejudice is, by the way, a discount. The black 452 00:27:45,316 --> 00:27:48,276 Speaker 1: life does not matter as much as the white life. 453 00:27:50,196 --> 00:27:53,236 Speaker 1: And who are these people imposing a discount on black schools. 454 00:27:54,276 --> 00:27:58,076 Speaker 1: They're wealthy, successful people who are simply checking a box. 455 00:27:58,556 --> 00:28:00,796 Speaker 1: I like this bond, I like this one a lot, 456 00:28:01,196 --> 00:28:04,836 Speaker 1: I don't like this one. They are, I suspect, not 457 00:28:04,916 --> 00:28:07,876 Speaker 1: a whole lot different from the college administrators who assign 458 00:28:07,916 --> 00:28:09,676 Speaker 1: a number to their peers for them. The US News 459 00:28:09,756 --> 00:28:14,876 Speaker 1: rankings every year motivated by the same unconscious biases. I 460 00:28:14,996 --> 00:28:17,356 Speaker 1: like the school four point two, I like this one 461 00:28:17,436 --> 00:28:21,036 Speaker 1: a lot four point five. I don't like this one 462 00:28:21,156 --> 00:28:23,996 Speaker 1: two point four, even though I don't really know anything 463 00:28:23,996 --> 00:28:27,516 Speaker 1: about it. So if you were the president of a 464 00:28:27,676 --> 00:28:30,356 Speaker 1: historically black college in one of those States with a 465 00:28:30,396 --> 00:28:34,436 Speaker 1: reputational discount for being black is thirty seven percent. How 466 00:28:34,476 --> 00:28:37,036 Speaker 1: do you think you'd feel about your peer assessment score? 467 00:28:40,156 --> 00:28:43,876 Speaker 1: I thought I'd call Walter Kimbro, president of Dillard University, 468 00:28:44,116 --> 00:28:47,076 Speaker 1: a historically black college in Louisiana, And. 469 00:28:47,036 --> 00:28:48,916 Speaker 6: So when I start to look at the formulas and 470 00:28:48,956 --> 00:28:50,756 Speaker 6: dig into it, I was like, this isn't a real 471 00:28:50,836 --> 00:28:54,196 Speaker 6: good measurement of what we do. In fact, it's a 472 00:28:54,236 --> 00:28:56,116 Speaker 6: measurement of privilege. 473 00:28:56,236 --> 00:29:00,436 Speaker 1: Dillard's reputation score is two point six. That's not good. 474 00:29:01,036 --> 00:29:02,996 Speaker 1: You can't ever get to the top of the US 475 00:29:03,036 --> 00:29:05,996 Speaker 1: News rankings with a peer assessment score of two point six. 476 00:29:06,636 --> 00:29:09,196 Speaker 6: Maybe that sounds defeatis, but I mean. 477 00:29:09,196 --> 00:29:14,036 Speaker 1: It's it's not defeat its it's realistic, verble living it. 478 00:29:14,236 --> 00:29:16,636 Speaker 6: Nobody's going to just go and say this school, with 479 00:29:16,676 --> 00:29:19,516 Speaker 6: all these black people, is great. 480 00:29:19,276 --> 00:29:22,236 Speaker 1: In their haste to compete with Time and Newsweek way 481 00:29:22,236 --> 00:29:25,756 Speaker 1: back when, maybe all US News did was create a 482 00:29:25,796 --> 00:29:28,356 Speaker 1: system that allowed the presidents and deans of every college 483 00:29:28,356 --> 00:29:31,156 Speaker 1: in the country to assign a number to their prejudice 484 00:29:31,796 --> 00:29:41,556 Speaker 1: to disguise mythology as methodology. Next week on Revisionist History, 485 00:29:42,316 --> 00:29:45,556 Speaker 1: we take up the cause of Dillard University, and I 486 00:29:45,676 --> 00:29:48,276 Speaker 1: enlist my old friends at Reed College to help me out. 487 00:29:49,516 --> 00:29:52,316 Speaker 5: So that is how we can get Dillard into the 488 00:29:52,356 --> 00:29:55,596 Speaker 5: tippy top tier of the liberal arts colleges. 489 00:29:56,436 --> 00:30:08,156 Speaker 1: So it's Williams Amherst Dillard swarthwik Yes Division's history is 490 00:30:08,196 --> 00:30:11,596 Speaker 1: produced by mel Belle, Leeman Gesteu and Jacob Smith, with 491 00:30:11,676 --> 00:30:15,836 Speaker 1: Eloise Linton and on An eyem Our. Editor is Julia Barton. 492 00:30:16,116 --> 00:30:20,156 Speaker 1: Original scoring by Luis Kira, mastering by Flonn Williams, and 493 00:30:20,276 --> 00:30:25,396 Speaker 1: engineering by Martin Gonzalez. Fact checking by Amy Gaines. Special 494 00:30:25,436 --> 00:30:30,156 Speaker 1: thanks the Pushkin crew had a fine Carl MCGLIORI, Maya Knick, 495 00:30:30,316 --> 00:30:35,076 Speaker 1: Maggie Taylor, Eric Sandler, Nicol Morano, Jason Gambrell, and of 496 00:30:35,116 --> 00:30:49,516 Speaker 1: course Jacob Weisberg. I'm Malcolm Glaba. If you love this 497 00:30:49,596 --> 00:30:53,716 Speaker 1: show and others from Pushkin Industries, consider becoming a Pushnik. 498 00:30:54,196 --> 00:30:58,596 Speaker 1: Pushnick is a podcast subscription that offers bonus content and 499 00:30:58,836 --> 00:31:02,676 Speaker 1: uninterrupted listening for four dollars and ninety nine cents a month. 500 00:31:03,236 --> 00:31:11,556 Speaker 1: Look for Pushnik exclusively on Apple Podcasts subscriptions with three 501 00:31:11,556 --> 00:31:17,276 Speaker 1: flavors Ali's Nasty, Nasty, Delicious, and Nasty Vicious. Okay, guys, 502 00:31:17,356 --> 00:31:22,516 Speaker 1: but you hold on the websites to do simultaneously. Ye okay, one, two, three, 503 00:31:23,196 --> 00:31:39,676 Speaker 1: God oh, I like that it comes on, Oh, go Ali, 504 00:31:40,156 --> 00:31:42,796 Speaker 1: go Ali, because it's really good. It's good. 505 00:31:43,476 --> 00:31:49,316 Speaker 3: Hold on I okay, it's very spicy for a very long. 506 00:31:49,076 --> 00:31:52,476 Speaker 1: Time, because am I, it's not eating me as hard 507 00:31:52,996 --> 00:31:58,556 Speaker 1: as it did. I'm taking a second bite. Martine's struggling, 508 00:32:02,716 --> 00:32:04,556 Speaker 1: By the way, where's my Harvard hot saice? I don't. 509 00:32:04,556 --> 00:32:07,876 Speaker 1: I don't see any Harvard hot sauce. No one's sending 510 00:32:07,876 --> 00:32:10,356 Speaker 1: me hot sauce from New even, are they. 511 00:32:10,436 --> 00:32:10,476 Speaker 3: No