1 00:00:00,160 --> 00:00:03,240 Speaker 1: Does the Supreme Court have an aversion to math? An 2 00:00:03,400 --> 00:00:05,960 Speaker 1: essay on the website five thirty eight makes a case 3 00:00:06,040 --> 00:00:09,440 Speaker 1: that some Supreme Court justices are reluctant to take math 4 00:00:09,520 --> 00:00:13,480 Speaker 1: and statistics seriously. In a case challenging part as in 5 00:00:13,600 --> 00:00:18,200 Speaker 1: gerrymandering in Wisconsin, gilv. Whitford, Democrats proposed a test, relying 6 00:00:18,239 --> 00:00:21,800 Speaker 1: in part on advanced statistical techniques, including a measure known 7 00:00:21,840 --> 00:00:25,200 Speaker 1: as the efficiency gap, to create a standard to separate 8 00:00:25,320 --> 00:00:29,720 Speaker 1: unconstitutional maps from legitimate ones. Listening to arguments in the 9 00:00:29,760 --> 00:00:32,600 Speaker 1: case in June, it seemed that an aversion to math 10 00:00:32,720 --> 00:00:36,800 Speaker 1: cut across political divides. Here are Chief Justice John Roberts 11 00:00:36,840 --> 00:00:40,680 Speaker 1: and Justice Steven Bryer. It is just not It seems 12 00:00:40,680 --> 00:00:44,239 Speaker 1: a palatable answer to say the ruling was based on 13 00:00:44,320 --> 00:00:46,920 Speaker 1: the fact that e G was greater than seven percent. 14 00:00:47,280 --> 00:00:50,800 Speaker 1: That doesn't sound like language in the Constitution. And it 15 00:00:50,840 --> 00:00:53,800 Speaker 1: may be simply my educational background, but I can only 16 00:00:53,840 --> 00:00:57,880 Speaker 1: describe a sociological compulty book. I think the hard issue 17 00:00:57,880 --> 00:01:01,640 Speaker 1: in this cases are their standards manageable by a court, 18 00:01:01,760 --> 00:01:05,080 Speaker 1: not by some group of social science political x you know, 19 00:01:05,200 --> 00:01:09,160 Speaker 1: computer experts. When I read all that social science stuff 20 00:01:09,360 --> 00:01:11,400 Speaker 1: and the computer stuff, I said, well, what is there 21 00:01:11,440 --> 00:01:14,919 Speaker 1: a way of reducing it to something that's manageable? Joining 22 00:01:14,920 --> 00:01:18,000 Speaker 1: me is Josh Douglas, professor at the University of Kentucky 23 00:01:18,240 --> 00:01:23,600 Speaker 1: Law School. Well, Josh, are the justices allergic to math? Well, 24 00:01:23,640 --> 00:01:26,480 Speaker 1: we'll find out when it comes to this decision, of course, 25 00:01:26,560 --> 00:01:31,240 Speaker 1: But it seems strange that the justices would say they're 26 00:01:31,240 --> 00:01:34,119 Speaker 1: having a version to math in this instance when they 27 00:01:34,160 --> 00:01:37,760 Speaker 1: certainly do use, or at least historically have used social 28 00:01:37,800 --> 00:01:41,920 Speaker 1: science and math formulas in redistioning cases, as well as 29 00:01:42,280 --> 00:01:48,480 Speaker 1: all other sorts of constitutional adjudication. So um, although the 30 00:01:48,520 --> 00:01:51,680 Speaker 1: current crop of justices might feel like in this case 31 00:01:52,080 --> 00:01:55,680 Speaker 1: they the math is going to be complicated, that's historically 32 00:01:56,200 --> 00:02:00,080 Speaker 1: not what the Court has ever really done. Is there 33 00:02:00,120 --> 00:02:02,240 Speaker 1: any way to make a rule in a Gerryman daring 34 00:02:02,320 --> 00:02:07,120 Speaker 1: case without using some kind of formula? I don't think so. 35 00:02:07,280 --> 00:02:09,760 Speaker 1: I mean, because you know, the one of the principal 36 00:02:10,320 --> 00:02:14,040 Speaker 1: areas of redistricting is one person, one vote, this notion 37 00:02:14,080 --> 00:02:17,120 Speaker 1: that everyone's vote is worth the same amount. And the 38 00:02:17,160 --> 00:02:19,360 Speaker 1: way you figure that out is you determine if there's 39 00:02:19,480 --> 00:02:22,880 Speaker 1: the same number of voters in each district. That's math 40 00:02:23,160 --> 00:02:26,360 Speaker 1: that's taking the total number of voters and dividing by 41 00:02:26,400 --> 00:02:30,440 Speaker 1: the number of districts, and that gives you a number 42 00:02:30,639 --> 00:02:33,200 Speaker 1: of how many voters should be in each district to 43 00:02:33,400 --> 00:02:37,160 Speaker 1: ensure that everyone's vote counts the same or roughly. And 44 00:02:37,240 --> 00:02:39,679 Speaker 1: the court, you know, for decades has said, well, you 45 00:02:39,720 --> 00:02:43,160 Speaker 1: should be close to mathematical equality in each district, but 46 00:02:43,200 --> 00:02:46,640 Speaker 1: you can have some level of deviation, and some cases 47 00:02:46,680 --> 00:02:49,320 Speaker 1: have gone around a ten percent level where you can 48 00:02:49,639 --> 00:02:54,800 Speaker 1: be ten percent above or below the average size district 49 00:02:54,880 --> 00:02:57,280 Speaker 1: or what you should be. So that's all math. You know. 50 00:02:57,440 --> 00:03:01,080 Speaker 1: Entering the political thicket with redistricting case is involves all 51 00:03:01,160 --> 00:03:05,560 Speaker 1: those sorts of calculations. Now there's a breaking news crossing 52 00:03:05,560 --> 00:03:09,280 Speaker 1: the Bloomberg terminal. The Supreme Court has dismissed the remaining 53 00:03:09,360 --> 00:03:12,440 Speaker 1: Trump travel band case. The Supreme Court has dismissed the 54 00:03:12,520 --> 00:03:15,320 Speaker 1: last Trump travel band case. Will have more on that 55 00:03:15,760 --> 00:03:19,840 Speaker 1: coming up, Josh. Justice Roberts seemed to be concerned that 56 00:03:20,120 --> 00:03:23,600 Speaker 1: using a formula makes it seem to the public as 57 00:03:23,639 --> 00:03:27,160 Speaker 1: if the Court isn't relying on legal principles, and that 58 00:03:27,560 --> 00:03:33,080 Speaker 1: something would be based on democrats, democrats or Republicans to 59 00:03:33,160 --> 00:03:39,160 Speaker 1: the public. Yeah, you know, I'm not sure what to 60 00:03:39,200 --> 00:03:42,240 Speaker 1: make of that, because I don't think the ruling would 61 00:03:42,240 --> 00:03:44,840 Speaker 1: be the mass says the Democrats win or of the 62 00:03:44,800 --> 00:03:48,360 Speaker 1: Republicans win. The ruling would be that the equal protection 63 00:03:48,480 --> 00:03:53,280 Speaker 1: cause forbids drawing districts that are so skewed toward one 64 00:03:53,320 --> 00:03:56,000 Speaker 1: side or another. How do we know they're skewed? We 65 00:03:56,080 --> 00:04:01,360 Speaker 1: know because the performance of those districts would uh ensure 66 00:04:01,560 --> 00:04:05,240 Speaker 1: one side wins in an election. Um. But that's not math. 67 00:04:05,360 --> 00:04:10,600 Speaker 1: That's dictating the constitutionists the constitution dictating fairness in our elections. 68 00:04:10,600 --> 00:04:13,840 Speaker 1: So I think what the Chief is not doing is 69 00:04:13,920 --> 00:04:17,080 Speaker 1: linking what the math is showing. And it simply the 70 00:04:17,080 --> 00:04:21,479 Speaker 1: mathematical formulas are showing the unfairness, and the unfairness is 71 00:04:21,520 --> 00:04:25,920 Speaker 1: what's apparently unconstitutional. And that's what the public already is 72 00:04:25,960 --> 00:04:27,880 Speaker 1: relying on. I mean, so many of so much of 73 00:04:27,920 --> 00:04:32,080 Speaker 1: the public already thinks redistarcing is unfair, that that the 74 00:04:32,120 --> 00:04:35,080 Speaker 1: politicians are drawing the lines in order to help themselves win. 75 00:04:35,800 --> 00:04:38,520 Speaker 1: Uh So the public gets this. The question is will 76 00:04:38,520 --> 00:04:42,479 Speaker 1: the court understand that this particular formula is one way 77 00:04:42,480 --> 00:04:45,520 Speaker 1: in which to show that on constitutionality. I admit that 78 00:04:45,560 --> 00:04:48,880 Speaker 1: I'm allergic to math and I think many lawyers say 79 00:04:48,920 --> 00:04:50,960 Speaker 1: that I would have gone to business school, but I'm 80 00:04:51,000 --> 00:04:53,719 Speaker 1: allergic to math. So I went to law school, and 81 00:04:53,760 --> 00:04:57,840 Speaker 1: you're the Chief Justice saying maybe it's my background. So 82 00:04:58,480 --> 00:05:01,840 Speaker 1: is there that as well that as lawyers, unless we're 83 00:05:01,839 --> 00:05:05,400 Speaker 1: in certain fields, we're not you know, looking, we're not 84 00:05:05,600 --> 00:05:09,159 Speaker 1: math geniuses. Let's say, yeah, I think that's part of it. 85 00:05:09,200 --> 00:05:12,920 Speaker 1: I mean, certainly my students at the law school seem 86 00:05:13,000 --> 00:05:15,160 Speaker 1: to have an aversion to math, and you know they 87 00:05:15,240 --> 00:05:17,720 Speaker 1: grown when when we have a day on redistricting in 88 00:05:17,839 --> 00:05:20,720 Speaker 1: which I do what I call sixth grade arithmetic, which 89 00:05:20,760 --> 00:05:24,440 Speaker 1: comes from one of these Supreme Court cases on redistricting. 90 00:05:25,000 --> 00:05:28,240 Speaker 1: But the reality is that it's not that complicated the 91 00:05:28,320 --> 00:05:31,520 Speaker 1: math that's involved in these cases. It's fairly simple. You're 92 00:05:31,520 --> 00:05:35,520 Speaker 1: not looking at sovesticated regression now, so you're basically counting 93 00:05:35,600 --> 00:05:39,599 Speaker 1: up vote and doing some division um. And so although 94 00:05:39,880 --> 00:05:42,560 Speaker 1: there may be an initial aversion to the concept of it, 95 00:05:43,040 --> 00:05:45,200 Speaker 1: when you get down into actually doing it, it's not 96 00:05:45,279 --> 00:05:48,279 Speaker 1: that complex. And that's exactly what this efficiency got. It's 97 00:05:48,279 --> 00:05:53,720 Speaker 1: actually not that complex formula. So what about past Supreme courts? 98 00:05:53,760 --> 00:05:58,320 Speaker 1: Have we seen this math aversion in other Supreme courts. 99 00:06:00,200 --> 00:06:03,880 Speaker 1: Certainly there's been some justices who have criticized the Court 100 00:06:03,880 --> 00:06:07,960 Speaker 1: getting involved in redistricting cases. Uh. In in descent, that's 101 00:06:08,040 --> 00:06:11,080 Speaker 1: that's the creat aristhmetic term comes from one of these 102 00:06:11,160 --> 00:06:14,159 Speaker 1: to scents. Um. But I'll say that also, you know, 103 00:06:14,200 --> 00:06:18,000 Speaker 1: a lot of constitutional law has relied on in other areas, 104 00:06:18,120 --> 00:06:21,640 Speaker 1: a lot on social science data or mathematical data. I mean, 105 00:06:21,720 --> 00:06:24,880 Speaker 1: even Brown versus Board of Education. One of the basis 106 00:06:24,920 --> 00:06:29,840 Speaker 1: of that decision saying that separate educational facilities are inherently 107 00:06:29,880 --> 00:06:32,880 Speaker 1: and equal, relying on a lot of social science data. Um. 108 00:06:32,920 --> 00:06:35,320 Speaker 1: And people criticize it at the times as the extent 109 00:06:35,400 --> 00:06:37,880 Speaker 1: of the Court was relying on social science, but that 110 00:06:37,960 --> 00:06:42,240 Speaker 1: was the underlying evidentiary basis for that holding. We look 111 00:06:42,240 --> 00:06:45,919 Speaker 1: at the affirmative action area, and you look at you know, 112 00:06:46,080 --> 00:06:48,640 Speaker 1: admissions for example, a lot of that has to do 113 00:06:48,800 --> 00:06:52,520 Speaker 1: with social science data and uh and compulations about the 114 00:06:52,560 --> 00:06:58,080 Speaker 1: likelihood of admissions, etcetera. So, Um, it's not born for 115 00:06:58,120 --> 00:07:02,560 Speaker 1: the Court to be thinking about social science calculations in 116 00:07:03,320 --> 00:07:06,919 Speaker 1: a variety of its constitutional unication. Maybe just a little 117 00:07:06,920 --> 00:07:10,000 Speaker 1: bit uncomfortable when you're used to dealing with ideology and 118 00:07:10,040 --> 00:07:13,200 Speaker 1: words in the Constitution. We'll see what happens when they 119 00:07:13,240 --> 00:07:16,640 Speaker 1: make this decision in this gerrymandering case. Thanks so much 120 00:07:16,680 --> 00:07:19,920 Speaker 1: for being here on Bloomberg Law. That's Josh Douglas. He's 121 00:07:19,920 --> 00:07:23,960 Speaker 1: a professor at the University of Kentucky Law School. That's 122 00:07:23,960 --> 00:07:26,080 Speaker 1: it for this edition of Bloomberg Law. Will be back 123 00:07:26,120 --> 00:07:29,120 Speaker 1: tomorrow at one pm Wall Street time. We'll have more 124 00:07:29,160 --> 00:07:32,880 Speaker 1: on the Supreme Court dismissing the remaining Trump travel band 125 00:07:32,920 --> 00:07:36,720 Speaker 1: case coming up. Thanks to our producer David Suckerman and 126 00:07:36,760 --> 00:07:40,360 Speaker 1: our technical director Chris trike Comy. You can always find 127 00:07:40,400 --> 00:07:42,800 Speaker 1: the latest legal news at Bloomberg Law dot com and 128 00:07:42,840 --> 00:07:45,600 Speaker 1: Bloomberg BNA dot com, plus a website for the little 129 00:07:45,640 --> 00:07:48,920 Speaker 1: community at Big Law Business dot com. Coming up next, 130 00:07:48,920 --> 00:07:52,040 Speaker 1: Bloomberg Markets with Carol Master, and Carol is here to 131 00:07:52,120 --> 00:07:54,040 Speaker 1: tell us what's in store for us in the next 132 00:07:54,120 --> 00:07:56,520 Speaker 1: couple of hours. Soon we are talking a lot about earnings. 133 00:07:56,520 --> 00:07:59,480 Speaker 1: We're seeing shares of Caterpillar GM Rawlings, who are talking 134 00:07:59,520 --> 00:08:03,000 Speaker 1: about those quarters. And also the Weinstein Company's man in 135 00:08:03,160 --> 00:08:06,920 Speaker 1: shining Armor, Tom Barrick. Why he's helping bail out that company. 136 00:08:07,280 --> 00:08:10,760 Speaker 1: That sounds very interesting. We're all stay tuned. That's Coming 137 00:08:10,840 --> 00:08:14,320 Speaker 1: up on Bloomberg Radio, Bloomberg Markets with Carol Master. This 138 00:08:14,440 --> 00:08:15,040 Speaker 1: is Bloomberg