1 00:00:01,240 --> 00:00:03,840 Speaker 1: Welcome to the Tutor Dixon Podcast. We are going to 2 00:00:04,000 --> 00:00:06,560 Speaker 1: talk about law enforcement today. I know a lot of 3 00:00:06,559 --> 00:00:09,880 Speaker 1: you are going, what is going on right now? We 4 00:00:09,960 --> 00:00:12,680 Speaker 1: see all this stuff happening in Minnesota. What is the 5 00:00:12,720 --> 00:00:17,200 Speaker 1: true story behind the deportations and everything that President Trump 6 00:00:17,239 --> 00:00:19,759 Speaker 1: is doing. I decided it would be best to talk 7 00:00:19,800 --> 00:00:23,040 Speaker 1: to doctor John lot about that. He's an economist and 8 00:00:23,079 --> 00:00:27,080 Speaker 1: also a former senior advisor to the Department of Justice 9 00:00:27,680 --> 00:00:31,800 Speaker 1: and the president of the Crime Prevention Research Center. Doctor Lott, 10 00:00:31,800 --> 00:00:33,000 Speaker 1: thank you so much for joining me. 11 00:00:33,720 --> 00:00:35,440 Speaker 2: It's great to talk to you again. Thank you for 12 00:00:35,440 --> 00:00:36,000 Speaker 2: having me on. 13 00:00:36,600 --> 00:00:41,280 Speaker 1: Absolutely so we always talk about the fact that people 14 00:00:41,360 --> 00:00:44,560 Speaker 1: forget Obama was considered the deporter in chief and he 15 00:00:45,400 --> 00:00:48,400 Speaker 1: received that name from his own side. They called him 16 00:00:48,479 --> 00:00:52,159 Speaker 1: the deporter in chief, and they're now saying, well, Donald 17 00:00:52,200 --> 00:00:55,440 Speaker 1: Trump is out of control with what he's doing. So 18 00:00:55,480 --> 00:00:57,800 Speaker 1: I thought I would ask you, can we compare their 19 00:00:57,840 --> 00:00:58,760 Speaker 1: records a little bit? 20 00:01:00,480 --> 00:01:03,920 Speaker 2: Yeah, you know, unfortunately there's really only good data for 21 00:01:04,000 --> 00:01:06,400 Speaker 2: a lot of these questions for the last two years 22 00:01:06,440 --> 00:01:10,399 Speaker 2: of the Obama administration twenty fifteen and twenty sixteen. But 23 00:01:11,120 --> 00:01:14,440 Speaker 2: you know, it's amazing to me how there's really no 24 00:01:14,560 --> 00:01:17,360 Speaker 2: comparisons that go on in the media. You know, you think, 25 00:01:18,319 --> 00:01:20,880 Speaker 2: you know. It seems like the standard that they want 26 00:01:20,880 --> 00:01:23,920 Speaker 2: to hold people too is that there's absolutely no mistakes 27 00:01:23,920 --> 00:01:27,520 Speaker 2: that ever made. And you know, to me, the thing is, well, 28 00:01:27,560 --> 00:01:29,880 Speaker 2: what is the rate of mistakes? How does it compare 29 00:01:30,080 --> 00:01:32,360 Speaker 2: to others? So, for example, a lot of the media 30 00:01:32,920 --> 00:01:36,039 Speaker 2: will focus on this report from pro publica kind of 31 00:01:36,040 --> 00:01:39,480 Speaker 2: a left wing media organization, claiming that one hundred and 32 00:01:39,520 --> 00:01:46,280 Speaker 2: seventy Americans have been accidentally detained by Ice. What they 33 00:01:46,480 --> 00:01:48,560 Speaker 2: leave out of that is that one hundred and thirty 34 00:01:48,560 --> 00:01:52,080 Speaker 2: of those one hundred and seventy were arrested and detained 35 00:01:52,080 --> 00:01:56,280 Speaker 2: by Ice because they had either attacked Ice officers or 36 00:01:56,360 --> 00:02:00,280 Speaker 2: had interfered in some way with the operations there. But 37 00:02:00,320 --> 00:02:03,680 Speaker 2: you still have forty that are there. And if you 38 00:02:03,720 --> 00:02:07,160 Speaker 2: break down the amount of time, most of those are 39 00:02:07,200 --> 00:02:09,760 Speaker 2: held for less than a day, many of those for 40 00:02:09,919 --> 00:02:13,560 Speaker 2: just even an hour or a couple hours just to 41 00:02:13,680 --> 00:02:17,160 Speaker 2: double check things, and then released. There's literally three of 42 00:02:17,160 --> 00:02:21,840 Speaker 2: them that were held for more than forty eight hours. Obviously, 43 00:02:21,880 --> 00:02:25,720 Speaker 2: you don't want anybody to be held who shouldn't be 44 00:02:25,760 --> 00:02:29,080 Speaker 2: held in these things, but you know, when you break 45 00:02:29,080 --> 00:02:31,440 Speaker 2: it down and you look at the fact that there 46 00:02:31,440 --> 00:02:36,520 Speaker 2: were about six hundred thousand illegals who were detained during 47 00:02:36,560 --> 00:02:40,680 Speaker 2: that period of time last year, you're talking about an 48 00:02:40,760 --> 00:02:44,919 Speaker 2: air rate of zero point zero zero six seven percent, 49 00:02:45,520 --> 00:02:49,080 Speaker 2: So you're talking about something that's you know, thousands of 50 00:02:49,160 --> 00:02:54,160 Speaker 2: one percentage points, like one mistake there for every fourteen thousand, 51 00:02:54,360 --> 00:03:01,200 Speaker 2: nine hundred illegals who were detained, as you say, one 52 00:03:01,200 --> 00:03:05,280 Speaker 2: can compare it to the past. Again, this data wasn't 53 00:03:05,320 --> 00:03:10,120 Speaker 2: collected during the Biden administration and only two years for Obama. 54 00:03:10,560 --> 00:03:13,760 Speaker 1: But why why wasn't it collected during the Biden administration? 55 00:03:14,200 --> 00:03:16,960 Speaker 2: I don't know. I have to go and ask the 56 00:03:17,000 --> 00:03:19,960 Speaker 2: people in the Biden administration what they found interesting to 57 00:03:20,040 --> 00:03:27,120 Speaker 2: collect or not on these things. Wow, and so, and 58 00:03:27,200 --> 00:03:31,120 Speaker 2: it is frustrating to do that. But so if you 59 00:03:31,160 --> 00:03:33,720 Speaker 2: look at the two years that we have data for 60 00:03:33,720 --> 00:03:40,640 Speaker 2: for on detentions and who is being accidentally detained under Obama, 61 00:03:41,120 --> 00:03:44,200 Speaker 2: you found that basically he made an error at about 62 00:03:44,240 --> 00:03:48,520 Speaker 2: one of every four thousand illegals compared to one out 63 00:03:48,520 --> 00:03:52,920 Speaker 2: of every fourteen nine hundred illegals under Trump. So that's 64 00:03:53,000 --> 00:03:57,360 Speaker 2: like more than a threefold difference there in terms of 65 00:03:57,800 --> 00:04:03,320 Speaker 2: a higher error rate, and so, you know, and the 66 00:04:03,360 --> 00:04:06,680 Speaker 2: other thing just to keep in mind is that Obama 67 00:04:06,840 --> 00:04:13,160 Speaker 2: also defined detentions and arrest differently than other administrations, So 68 00:04:13,400 --> 00:04:18,040 Speaker 2: they would count detentions as people that they caught coming 69 00:04:18,080 --> 00:04:21,720 Speaker 2: across the border and then immediately returned. At that point, 70 00:04:22,120 --> 00:04:25,880 Speaker 2: those are unlikely to be American citizens that you're catching 71 00:04:26,440 --> 00:04:29,359 Speaker 2: at that point. It's not too many American citizens try 72 00:04:29,400 --> 00:04:33,080 Speaker 2: to sneak across the border from Mexico and get caught. 73 00:04:33,520 --> 00:04:36,520 Speaker 2: And so the air rate if you were to kind 74 00:04:36,560 --> 00:04:39,599 Speaker 2: of compare apples to apples, but we really can't. I mean, 75 00:04:39,640 --> 00:04:45,760 Speaker 2: maybe seventy percent of the people who were classified as 76 00:04:45,800 --> 00:04:49,279 Speaker 2: detained under the Obama administration, where people who tried to 77 00:04:49,320 --> 00:04:52,320 Speaker 2: sneak across the border, you know, it could have been 78 00:04:52,440 --> 00:04:55,000 Speaker 2: their air rate could have been much much higher than 79 00:04:55,040 --> 00:04:58,719 Speaker 2: more than three times higher for Obama than it was 80 00:04:58,839 --> 00:05:00,520 Speaker 2: for Trump last year. 81 00:05:00,960 --> 00:05:04,760 Speaker 1: Hmm. That's interesting because even when CNN, let's let's not 82 00:05:04,839 --> 00:05:07,760 Speaker 1: forget CNN did that ride along, that kind of came 83 00:05:07,800 --> 00:05:10,080 Speaker 1: back up in the media or at least in social 84 00:05:10,120 --> 00:05:13,800 Speaker 1: media last week. People started to post the images from 85 00:05:13,800 --> 00:05:17,200 Speaker 1: that in the video, in that one video when they 86 00:05:17,200 --> 00:05:20,120 Speaker 1: were riding along they picked up the wrong person and 87 00:05:20,160 --> 00:05:23,200 Speaker 1: they detained him and then and then CNN says, turns 88 00:05:23,200 --> 00:05:25,160 Speaker 1: out the guy that they picked up in the morning 89 00:05:25,640 --> 00:05:28,640 Speaker 1: was not the right person. They were looking for his brother. 90 00:05:28,960 --> 00:05:32,360 Speaker 1: When once they got him detained and they talked to him, 91 00:05:32,400 --> 00:05:34,520 Speaker 1: they worked it out, They figured out we have the 92 00:05:34,520 --> 00:05:37,080 Speaker 1: wrong guy, took him back, went and got his brother. 93 00:05:37,400 --> 00:05:40,440 Speaker 1: So they were reporting on it like it was totally fine. 94 00:05:40,520 --> 00:05:43,280 Speaker 1: You know, they made a mistake, and they say it's 95 00:05:43,320 --> 00:05:47,599 Speaker 1: a chaotic situation, this happens, but they ended up getting 96 00:05:47,600 --> 00:05:50,320 Speaker 1: the right guy. That was the way the media portrayed 97 00:05:50,320 --> 00:05:53,080 Speaker 1: it back then, like this was totally normal. Now the 98 00:05:53,160 --> 00:05:56,760 Speaker 1: media is really, i would say, egging on these protests, 99 00:05:56,839 --> 00:05:59,440 Speaker 1: egging on people to go out and attack ice. And 100 00:05:59,520 --> 00:06:04,719 Speaker 1: these attacks on ice are up like three thousand percent. 101 00:06:05,480 --> 00:06:08,240 Speaker 2: Right, you know, if you look at assaults on ice 102 00:06:08,279 --> 00:06:11,719 Speaker 2: officers in twenty twenty five, they're up one three hundred 103 00:06:11,720 --> 00:06:14,440 Speaker 2: and forty seven percent over what they were in twenty 104 00:06:14,480 --> 00:06:18,880 Speaker 2: twenty four. If you look at car attacks vehicle attacks 105 00:06:18,960 --> 00:06:22,520 Speaker 2: on ice officers, it's up like three thousand, two hundred percent. 106 00:06:23,520 --> 00:06:26,920 Speaker 2: If you look at death threats that ice officers have received, 107 00:06:26,960 --> 00:06:33,279 Speaker 2: it's up like eight thousand percent. You know, it's understandable 108 00:06:33,560 --> 00:06:39,080 Speaker 2: why these ICE officers wear masks. You have dosing that's occurring. 109 00:06:39,600 --> 00:06:42,320 Speaker 2: I mean, one of the hang ups that's occurring in 110 00:06:42,360 --> 00:06:45,239 Speaker 2: the budget debate that's going on right now it looks 111 00:06:45,240 --> 00:06:49,760 Speaker 2: like we're going to head for a budget shutdown after Friday, 112 00:06:50,800 --> 00:06:55,480 Speaker 2: is that Democrats want to be able to put into 113 00:06:55,560 --> 00:07:00,280 Speaker 2: law that ICE officers' identities can be determined. You know 114 00:07:00,320 --> 00:07:04,800 Speaker 2: that they will be wearing some identifying information on them 115 00:07:05,560 --> 00:07:08,080 Speaker 2: that makes it so that their names can be readily 116 00:07:08,120 --> 00:07:13,560 Speaker 2: identified by others, and you know it just you know, 117 00:07:13,640 --> 00:07:18,520 Speaker 2: I have to say, it's amazing how few, relatively few 118 00:07:18,680 --> 00:07:22,720 Speaker 2: errors ICE is making now given how difficult of a 119 00:07:22,840 --> 00:07:25,320 Speaker 2: job that they have, and they have a difficult job 120 00:07:25,360 --> 00:07:28,560 Speaker 2: in many ways, not just from these threats, but also 121 00:07:29,240 --> 00:07:32,040 Speaker 2: the buy An administration did not follow the law when 122 00:07:32,080 --> 00:07:35,040 Speaker 2: it released people into the United States. So, for example, 123 00:07:36,640 --> 00:07:40,760 Speaker 2: technically they're supposed to keep DNA samples to make sure 124 00:07:40,800 --> 00:07:43,760 Speaker 2: that you can identify individuals for those that they released. 125 00:07:43,760 --> 00:07:49,880 Speaker 2: They didn't do that. Surely you remember stories in the 126 00:07:49,960 --> 00:07:54,000 Speaker 2: media about how they would find passports and other identifying 127 00:07:54,040 --> 00:07:58,960 Speaker 2: information for people who are crossing the border dumped in 128 00:07:59,120 --> 00:08:02,960 Speaker 2: large dumps before people cross the border. Well, why are 129 00:08:02,960 --> 00:08:07,960 Speaker 2: they doing that. They're doing that so that immigration officials 130 00:08:08,000 --> 00:08:11,040 Speaker 2: were not able to check to make sure they knew 131 00:08:11,120 --> 00:08:13,960 Speaker 2: the identity of those people who were there. They may 132 00:08:14,000 --> 00:08:18,360 Speaker 2: have given false names in very likely cases. There all 133 00:08:18,400 --> 00:08:22,000 Speaker 2: those things, you know, not knowing for sure who it 134 00:08:22,120 --> 00:08:26,280 Speaker 2: is that has come into the country, making it more 135 00:08:26,280 --> 00:08:29,960 Speaker 2: difficult to identify the person once you've caught them in 136 00:08:30,000 --> 00:08:33,280 Speaker 2: the United States. All those things you would think would 137 00:08:33,320 --> 00:08:36,600 Speaker 2: increase the air rates that you have there, and so 138 00:08:36,679 --> 00:08:40,880 Speaker 2: it just makes it even more kind of impressive the 139 00:08:40,920 --> 00:08:43,280 Speaker 2: low error rates that they seem to have, at least 140 00:08:43,280 --> 00:08:47,440 Speaker 2: compared to I mean dramatically lower compared to what happened 141 00:08:47,520 --> 00:08:50,280 Speaker 2: under the Obama administration, where they didn't have to deal 142 00:08:50,320 --> 00:08:53,280 Speaker 2: with those types of confounding difficulties. 143 00:08:53,800 --> 00:08:57,160 Speaker 1: But what a shocking and dangerous time for us to consider. 144 00:08:58,040 --> 00:09:00,880 Speaker 1: We have to look at the Democrat Party now as 145 00:09:01,480 --> 00:09:04,280 Speaker 1: the party that is truly against law and order. If 146 00:09:04,320 --> 00:09:06,920 Speaker 1: they I mean really against the American people, if they 147 00:09:06,920 --> 00:09:10,040 Speaker 1: are willing to put us through another shutdown, and putting 148 00:09:10,160 --> 00:09:13,400 Speaker 1: us through a shutdown, we know that this shuts down 149 00:09:13,440 --> 00:09:15,920 Speaker 1: all of our agencies. I mean, remember we had air 150 00:09:16,000 --> 00:09:19,760 Speaker 1: travels shut down. This is a disaster to get to 151 00:09:19,800 --> 00:09:22,560 Speaker 1: the point where we aren't paying people to do the 152 00:09:22,640 --> 00:09:25,600 Speaker 1: jobs that the government is required to do for the 153 00:09:25,640 --> 00:09:28,360 Speaker 1: American people. But to think that they would shut the 154 00:09:28,440 --> 00:09:33,400 Speaker 1: government down to reveal the ice officers who are putting 155 00:09:33,480 --> 00:09:36,160 Speaker 1: their lives in danger every day to get these really 156 00:09:36,200 --> 00:09:38,480 Speaker 1: bad people off the streets. And that's the other thing 157 00:09:38,520 --> 00:09:42,480 Speaker 1: that the news media will not talk about. They will 158 00:09:42,480 --> 00:09:44,360 Speaker 1: not talk about the fact that this is the worst 159 00:09:44,440 --> 00:09:47,760 Speaker 1: of the worst. These are rapists, these are murderers, these 160 00:09:47,800 --> 00:09:51,640 Speaker 1: are pedophiles. They won't even acknowledge that they're on the 161 00:09:51,760 --> 00:09:55,800 Speaker 1: side of this debate of total chaos. I mean, how 162 00:09:55,800 --> 00:09:57,880 Speaker 1: do they see that as a good thing? And now 163 00:09:57,960 --> 00:10:03,560 Speaker 1: you've got some of these officials and political commentators saying 164 00:10:03,800 --> 00:10:09,200 Speaker 1: that they're calling for Neuremberg style trials after President Trump 165 00:10:09,280 --> 00:10:12,400 Speaker 1: is out of office, that they want to get control 166 00:10:12,559 --> 00:10:15,360 Speaker 1: and then they want to put everybody who's involved in 167 00:10:15,400 --> 00:10:18,480 Speaker 1: this on trial. And I just want to say, no 168 00:10:18,640 --> 00:10:22,040 Speaker 1: part of me believes that these trials stop with law enforcement. 169 00:10:22,240 --> 00:10:25,800 Speaker 1: And I of course think that that is horrific, but 170 00:10:25,880 --> 00:10:29,079 Speaker 1: I tell you, it goes on to everybody who believes 171 00:10:29,120 --> 00:10:29,880 Speaker 1: in law and order. 172 00:10:30,640 --> 00:10:33,280 Speaker 2: Right. So there are many, so many things that you're 173 00:10:33,320 --> 00:10:37,040 Speaker 2: just bringing up there at the beginning. Let me just 174 00:10:37,080 --> 00:10:40,760 Speaker 2: make one comment that is, it's not just American citizens 175 00:10:40,800 --> 00:10:47,200 Speaker 2: who are being heard. People tend to commit crimes against 176 00:10:47,240 --> 00:10:49,959 Speaker 2: those who are similar to themselves. You know, for example, 177 00:10:50,080 --> 00:10:53,319 Speaker 2: ninety percent of blacks are murdered by other blacks, about 178 00:10:53,360 --> 00:10:57,080 Speaker 2: eighty five percent of Hispanics are murdered by other Hispanics. 179 00:10:57,640 --> 00:11:03,040 Speaker 2: Illegals tend to disproport commit crimes against other illegals. So 180 00:11:03,440 --> 00:11:05,920 Speaker 2: you know, even if you believe them that they care 181 00:11:06,000 --> 00:11:12,080 Speaker 2: about illegal aliens generally, presumably they care about illegal aliens 182 00:11:12,160 --> 00:11:15,720 Speaker 2: who aren't committing crimes, who are victims of crimes there. 183 00:11:16,320 --> 00:11:20,040 Speaker 2: And yet you know, leaving these illegals in the country 184 00:11:21,000 --> 00:11:24,040 Speaker 2: means that they're more likely to be victims just like others. 185 00:11:24,640 --> 00:11:28,320 Speaker 2: You know, I recently did some work looking at New 186 00:11:28,400 --> 00:11:33,319 Speaker 2: York State, and not only do you find that illegal 187 00:11:33,360 --> 00:11:38,120 Speaker 2: aliens are disproportionately committing crimes, they make about fourteen percent 188 00:11:38,720 --> 00:11:42,760 Speaker 2: of the incarcerated population in the state, which is a 189 00:11:42,880 --> 00:11:47,040 Speaker 2: huge underestimate of their share there, simply because it doesn't 190 00:11:47,120 --> 00:11:49,920 Speaker 2: take into account that New York is not helping ice 191 00:11:49,960 --> 00:11:57,199 Speaker 2: identify whether individuals in their jails and prison systems are illegals. Also, ICE, 192 00:11:57,520 --> 00:12:00,400 Speaker 2: as you know, will pick up people when they're in 193 00:12:00,480 --> 00:12:04,640 Speaker 2: county courthouses, so they never make it into the jails 194 00:12:04,720 --> 00:12:07,320 Speaker 2: or the prison systems that are there. There's a couple 195 00:12:07,440 --> 00:12:09,839 Speaker 2: month period of time just in New York City last 196 00:12:09,880 --> 00:12:13,120 Speaker 2: year where CBS reports at about four hundred and sixty 197 00:12:13,480 --> 00:12:18,040 Speaker 2: such individuals were detained at courthouses by ICE. You know 198 00:12:18,080 --> 00:12:21,280 Speaker 2: that God only knows how many thousands you're talking about 199 00:12:21,320 --> 00:12:23,760 Speaker 2: over the course of a year for the entire state 200 00:12:24,520 --> 00:12:28,800 Speaker 2: that's there. But it turns out that that's about three 201 00:12:28,880 --> 00:12:33,760 Speaker 2: point four times their highest estimated share of the general 202 00:12:33,800 --> 00:12:38,439 Speaker 2: population there. So legal aliens, despite the fourteen percent being 203 00:12:38,480 --> 00:12:43,600 Speaker 2: a big underestimate of their share of criminals, are way 204 00:12:43,800 --> 00:12:49,080 Speaker 2: over represented there. And that also doesn't take into account 205 00:12:49,120 --> 00:12:55,959 Speaker 2: that last year, New York released about seven thousand criminals 206 00:12:55,960 --> 00:12:59,480 Speaker 2: who had been convicted from either prisons or jails. You know, 207 00:12:59,520 --> 00:13:03,559 Speaker 2: a couple had been convicted for murder, hundreds had been 208 00:13:03,640 --> 00:13:08,320 Speaker 2: convicted for rape, including child rape. They released them without 209 00:13:08,440 --> 00:13:12,800 Speaker 2: notifying ICE that they were releasing those individuals, And so 210 00:13:13,400 --> 00:13:17,080 Speaker 2: these were people who had been convicted by New York 211 00:13:17,120 --> 00:13:22,400 Speaker 2: state courts as beyond a reasonable doubt as being criminals 212 00:13:22,559 --> 00:13:27,440 Speaker 2: and committing violent and other horrible crimes, were released back 213 00:13:27,480 --> 00:13:30,360 Speaker 2: into the population. You know, if they had the normal 214 00:13:30,400 --> 00:13:34,160 Speaker 2: recidivism rate, which is about eighty five percent over five years, 215 00:13:34,640 --> 00:13:38,400 Speaker 2: God only knows how many more crimes those individuals would 216 00:13:38,440 --> 00:13:42,560 Speaker 2: have been committing, and again against all sorts of people, 217 00:13:42,559 --> 00:13:47,760 Speaker 2: but also probably disproportionately against illegals that are there. So 218 00:13:48,400 --> 00:13:52,560 Speaker 2: you know, one final thing and that is you know, 219 00:13:54,160 --> 00:13:56,320 Speaker 2: I think it was the weekend before this last one 220 00:13:56,480 --> 00:14:03,320 Speaker 2: where Christinom, Secretary of the Department of Homeland Security, was 221 00:14:03,400 --> 00:14:07,560 Speaker 2: on Face the Nation with Margaret Brennan and they had 222 00:14:07,600 --> 00:14:10,800 Speaker 2: a debate about how many what percent of the people 223 00:14:10,840 --> 00:14:15,040 Speaker 2: that they were picking up had criminal records, and Christin 224 00:14:15,080 --> 00:14:20,560 Speaker 2: Noams said that it was seventy percent, and Margaret Brennan said, no, 225 00:14:20,600 --> 00:14:23,520 Speaker 2: it's only forty seven percent according to their records. But 226 00:14:24,040 --> 00:14:26,720 Speaker 2: you know, it's just interesting to see how the media 227 00:14:26,840 --> 00:14:30,280 Speaker 2: just doesn't even listen to precisely what Christin Home was saying. 228 00:14:30,320 --> 00:14:35,680 Speaker 2: Because Christy Nolan was saying people who had committed or 229 00:14:35,760 --> 00:14:39,560 Speaker 2: been charged with crimes either in the United States or 230 00:14:39,680 --> 00:14:43,520 Speaker 2: their home countries. It just gives an example of the 231 00:14:43,600 --> 00:14:46,720 Speaker 2: bias there because Margaret Brennan, I don't know, maybe she 232 00:14:46,760 --> 00:14:49,720 Speaker 2: doesn't even know exactly what the numbers are that she 233 00:14:49,920 --> 00:14:52,520 Speaker 2: was given to go and talk about. But the forty 234 00:14:52,560 --> 00:14:56,200 Speaker 2: seven percent that she was talking about only dealt with 235 00:14:56,840 --> 00:15:01,640 Speaker 2: crimes committed or charged in the the United States, And 236 00:15:02,320 --> 00:15:04,800 Speaker 2: you know, I don't know if somebody's been convicted of 237 00:15:04,920 --> 00:15:08,720 Speaker 2: murder or rape or something like that in their home country. 238 00:15:09,240 --> 00:15:12,760 Speaker 2: It seems like that's something we should take into consideration there, 239 00:15:13,280 --> 00:15:15,680 Speaker 2: and it seems to me it's part of their criminal record. 240 00:15:15,720 --> 00:15:20,160 Speaker 2: And so you know, as I say, maybe Margaret Brennan 241 00:15:20,240 --> 00:15:24,240 Speaker 2: didn't understand kind of what the forty seven percent was 242 00:15:24,320 --> 00:15:27,760 Speaker 2: that she was dealing with. But you know, seventy percent, 243 00:15:28,000 --> 00:15:30,640 Speaker 2: that's a lot of people, and it's not like they're 244 00:15:30,640 --> 00:15:33,120 Speaker 2: going out of their way to go and get the 245 00:15:33,160 --> 00:15:36,920 Speaker 2: other thirty percent. But the problem is is that if 246 00:15:36,960 --> 00:15:40,600 Speaker 2: they go and they stop a car with an illegal 247 00:15:40,640 --> 00:15:43,560 Speaker 2: alien who is a criminal record in there, and there's 248 00:15:43,720 --> 00:15:47,320 Speaker 2: another illegal alien in the vehicle there, they'll pick them 249 00:15:47,360 --> 00:15:49,640 Speaker 2: both up and detain them. 250 00:15:50,040 --> 00:15:52,800 Speaker 1: Let's take a quick commercial break. We'll continue next on 251 00:15:52,840 --> 00:15:59,640 Speaker 1: a Tutor Dixon podcast. You're being very generous to Margaret 252 00:15:59,640 --> 00:16:02,880 Speaker 1: Brennam by saying maybe she didn't know, maybe she wasn't 253 00:16:02,920 --> 00:16:05,640 Speaker 1: trying to manipulate it. And I say that because I 254 00:16:05,800 --> 00:16:09,640 Speaker 1: feel as though the mainstream media has just completely turned 255 00:16:09,680 --> 00:16:12,400 Speaker 1: on the American people. I mean, we just got through 256 00:16:12,440 --> 00:16:16,960 Speaker 1: an election where Marjorie Taylor Green stood up during the 257 00:16:17,160 --> 00:16:19,560 Speaker 1: State of the Union and said to Joe Biden, say 258 00:16:19,640 --> 00:16:22,360 Speaker 1: Lake and Riley, say her name. He didn't even know it, 259 00:16:22,440 --> 00:16:26,280 Speaker 1: he couldn't even pronounce it correctly. I mean, we talked 260 00:16:26,280 --> 00:16:29,880 Speaker 1: about Jocelyn nunger Ay, we talked about all these rachel Morin, 261 00:16:29,920 --> 00:16:31,880 Speaker 1: you know, all these young women who are lost, and 262 00:16:31,960 --> 00:16:36,640 Speaker 1: it seems disproportionately to be women who are lost when 263 00:16:37,000 --> 00:16:41,920 Speaker 1: these criminals commit these horrific crimes. And yet it's women 264 00:16:42,200 --> 00:16:46,400 Speaker 1: who are also defending these people on TV. And I 265 00:16:46,520 --> 00:16:49,960 Speaker 1: really cannot understand how we got to the point where 266 00:16:50,520 --> 00:16:53,960 Speaker 1: an American criminal is bad and she'd be put in jail. 267 00:16:54,480 --> 00:16:57,680 Speaker 1: An American rapist is someone we are not happy about, 268 00:16:58,040 --> 00:17:03,640 Speaker 1: but in a illegal or a rapist from another country, 269 00:17:03,680 --> 00:17:07,320 Speaker 1: if they can't handle the word illegal, is someone we 270 00:17:07,359 --> 00:17:10,399 Speaker 1: want to protect them. When did this How did this start? 271 00:17:11,800 --> 00:17:17,320 Speaker 2: Right? But look, basically it's the most vulnerable people in 272 00:17:17,359 --> 00:17:20,320 Speaker 2: our society generally who are the most likely victims of 273 00:17:20,400 --> 00:17:25,720 Speaker 2: violent crime. Criminals. I was chief economist for the US 274 00:17:25,720 --> 00:17:30,160 Speaker 2: Sentencing Commission in Washington. I must have read a thousand 275 00:17:30,200 --> 00:17:34,840 Speaker 2: trial transcripts. And you know, criminals may not be the 276 00:17:34,840 --> 00:17:38,199 Speaker 2: brightest people, but they aren't stupid if they can go 277 00:17:38,240 --> 00:17:41,400 Speaker 2: and commit crime more easily, you know, So like you'd 278 00:17:41,440 --> 00:17:46,200 Speaker 2: have you'd read a trial transcript where you'd have somebody 279 00:17:46,240 --> 00:17:49,600 Speaker 2: would turn state's evidence again, one robber would turn states 280 00:17:49,680 --> 00:17:53,400 Speaker 2: evidence and testify against another robber there, and they'd ask 281 00:17:53,480 --> 00:17:55,400 Speaker 2: them the same types of questions, how did you pick 282 00:17:55,440 --> 00:17:58,000 Speaker 2: the target you did? And he'll say, well, we've thought 283 00:17:58,040 --> 00:18:00,800 Speaker 2: about going after the drug dealer down this because he 284 00:18:00,840 --> 00:18:03,880 Speaker 2: has lots of money, but he also has lots of guns. 285 00:18:04,680 --> 00:18:07,480 Speaker 2: We talked about going after a cab driver, but a 286 00:18:07,480 --> 00:18:09,639 Speaker 2: lot of the cab drivers are armed, and that seemed 287 00:18:09,720 --> 00:18:13,119 Speaker 2: kind of stupid. And then we saw this small woman 288 00:18:13,320 --> 00:18:16,600 Speaker 2: walking alone in a parking lot late at night, and 289 00:18:16,640 --> 00:18:19,240 Speaker 2: she looked like an easy target, and so we went 290 00:18:19,280 --> 00:18:21,840 Speaker 2: after her. And so you know, if they can get 291 00:18:21,880 --> 00:18:24,800 Speaker 2: the job done with less risk to themselves, you know 292 00:18:25,040 --> 00:18:28,159 Speaker 2: they're going to go and do that. And so you know, 293 00:18:30,440 --> 00:18:34,080 Speaker 2: basically you have two groups of people. You have basically 294 00:18:34,119 --> 00:18:36,959 Speaker 2: the ones who are most likely victims of violent crime, 295 00:18:37,000 --> 00:18:40,000 Speaker 2: and that overwhelmingly tends to be poor blacks who live 296 00:18:40,040 --> 00:18:43,159 Speaker 2: in high crime urban areas and people who are relatively 297 00:18:43,160 --> 00:18:47,280 Speaker 2: weaker physically, women and the elderly. You know. The interesting 298 00:18:47,320 --> 00:18:49,560 Speaker 2: thing there was a survey a little while ago for 299 00:18:49,720 --> 00:18:55,680 Speaker 2: Chicago asking people there if they wanted Trump to do 300 00:18:55,720 --> 00:18:58,200 Speaker 2: for Chicago what he had done in Washington, d c. 301 00:18:59,080 --> 00:19:03,680 Speaker 2: And blacks and Hispanics were in favor of Trump doing that. 302 00:19:04,160 --> 00:19:09,000 Speaker 2: The people who were against it were basically whites who 303 00:19:09,000 --> 00:19:12,640 Speaker 2: were very strongly against it. Particularly well to do whites, 304 00:19:14,000 --> 00:19:16,480 Speaker 2: you know, particularly liberals, I mean, but just whites as 305 00:19:16,480 --> 00:19:20,560 Speaker 2: a whole were strongly against that thing. 306 00:19:21,280 --> 00:19:25,560 Speaker 1: But well, you see a lot of crime right exactly. 307 00:19:25,600 --> 00:19:29,480 Speaker 2: The people who aren't being affected by the crime, you know, 308 00:19:29,640 --> 00:19:32,040 Speaker 2: it's a luxury. They can go and say, fine, we 309 00:19:32,080 --> 00:19:35,639 Speaker 2: don't need to have law enforcement here. You know, what 310 00:19:35,720 --> 00:19:40,560 Speaker 2: I will say is this isn't rocket science for reducing crime. 311 00:19:42,440 --> 00:19:45,480 Speaker 2: It's the basic idea, just as I was describing before, 312 00:19:45,600 --> 00:19:49,480 Speaker 2: that criminals respond to incentives in terms of deciding who 313 00:19:49,520 --> 00:19:52,480 Speaker 2: to pick for a crime victim. If you make it 314 00:19:52,600 --> 00:19:55,480 Speaker 2: riskier for criminals to commit crime with things like higher 315 00:19:55,520 --> 00:20:00,119 Speaker 2: rest rates, higher conviction rates, longer prison sentences, or you 316 00:20:00,160 --> 00:20:02,639 Speaker 2: can also make it riskier by allowing victims to be 317 00:20:02,680 --> 00:20:05,160 Speaker 2: able to go and defend themselves, for example, with a gun. 318 00:20:05,760 --> 00:20:09,040 Speaker 2: All those things make it riskier for criminals to make crime, 319 00:20:09,119 --> 00:20:11,520 Speaker 2: you get less crime. The one thing I will say 320 00:20:11,600 --> 00:20:14,359 Speaker 2: is that Democrats at least tend to be very consistent 321 00:20:14,640 --> 00:20:16,919 Speaker 2: on this stuff. They don't want to make it risky 322 00:20:17,000 --> 00:20:19,919 Speaker 2: in terms of higher rest rates or conviction rates or 323 00:20:19,960 --> 00:20:22,880 Speaker 2: longer prison sentences. And they also don't want to let 324 00:20:22,960 --> 00:20:26,199 Speaker 2: victims be able to go and defend themselves, So they 325 00:20:26,240 --> 00:20:29,320 Speaker 2: don't want to make it risky for criminals in that 326 00:20:29,359 --> 00:20:35,000 Speaker 2: way either. But you know, the thing is, it's the 327 00:20:35,160 --> 00:20:38,320 Speaker 2: very people that the Democrats claim that they care about, 328 00:20:38,680 --> 00:20:42,639 Speaker 2: the poor, minorities, women, who are harmed by this. So 329 00:20:42,720 --> 00:20:47,080 Speaker 2: you know, when Trump federalized law enforcement in DC, you 330 00:20:47,119 --> 00:20:49,719 Speaker 2: had a number of Democrats who came out and claimed 331 00:20:49,720 --> 00:20:52,480 Speaker 2: that Trump was racist because the only reason why he 332 00:20:52,560 --> 00:20:56,680 Speaker 2: was doing this was because DC's a heavily minority heavy 333 00:20:56,760 --> 00:21:03,480 Speaker 2: black city. You know, when Trump did that, you went 334 00:21:03,640 --> 00:21:08,359 Speaker 2: eighteen days without a single murder occurring in Washington, d C. 335 00:21:09,440 --> 00:21:12,480 Speaker 2: The latest data I have is from twenty twenty one, 336 00:21:12,680 --> 00:21:16,720 Speaker 2: indicating that at that time, ninety six percent of the 337 00:21:16,760 --> 00:21:21,600 Speaker 2: people who were murdered in DC were blacks. Well, if 338 00:21:21,640 --> 00:21:25,000 Speaker 2: you go for eighteen days in a row in a 339 00:21:25,359 --> 00:21:29,480 Speaker 2: city that had a very high murder rate, whose lives 340 00:21:29,480 --> 00:21:33,080 Speaker 2: do you think you're saving? You know, when ninety six 341 00:21:33,119 --> 00:21:36,160 Speaker 2: percent of the murder victims are black, it's pretty clear 342 00:21:36,240 --> 00:21:39,199 Speaker 2: whose lives you're saving as a result of that. And 343 00:21:39,240 --> 00:21:42,159 Speaker 2: it's not just that, you know, it's not just the 344 00:21:42,240 --> 00:21:45,480 Speaker 2: direct victims of crime in terms of rapes and robberies 345 00:21:45,560 --> 00:21:48,760 Speaker 2: and egg vat assaults, that's there, but it's the indirect 346 00:21:49,000 --> 00:21:54,440 Speaker 2: victims you have who owns disproportionately the businesses in those 347 00:21:54,480 --> 00:21:57,960 Speaker 2: parts of the city. Businesses go out of business when 348 00:21:58,000 --> 00:22:01,720 Speaker 2: you have high crime, okay, or they. 349 00:22:01,040 --> 00:22:04,480 Speaker 1: Believe that we're dealing with this in Minneapolis again and 350 00:22:04,520 --> 00:22:08,560 Speaker 1: that this guy got re elected as mayor because I think, 351 00:22:08,960 --> 00:22:11,919 Speaker 1: how can you watch your city burn once? How can 352 00:22:11,960 --> 00:22:15,960 Speaker 1: you watch total chaos breakout and the cheers from the 353 00:22:16,040 --> 00:22:19,159 Speaker 1: people who are elected. I mean Tim Walls when he 354 00:22:19,320 --> 00:22:22,719 Speaker 1: was running for president, his wife said, you know, I 355 00:22:22,840 --> 00:22:25,480 Speaker 1: opened the windows of the Governor's mansion so I could 356 00:22:25,480 --> 00:22:28,840 Speaker 1: smell the tires burning. I mean, these people love chaos. 357 00:22:28,840 --> 00:22:31,520 Speaker 1: You've got a new state rep in I think it's 358 00:22:31,600 --> 00:22:37,200 Speaker 1: Virginia who wants to consider an assault weapon essentially any gun. 359 00:22:37,240 --> 00:22:39,400 Speaker 1: The way he has defined an assault weapon is any 360 00:22:39,640 --> 00:22:42,920 Speaker 1: any gun, and he wants to immediately make them illegal. 361 00:22:42,960 --> 00:22:45,000 Speaker 1: And he has drafted a bill, and he was bringing 362 00:22:45,040 --> 00:22:49,280 Speaker 1: that to the to the State of Virginia and trying 363 00:22:49,280 --> 00:22:51,439 Speaker 1: to the Commonwealth of Virginia and trying to say that 364 00:22:51,520 --> 00:22:54,119 Speaker 1: this is going to be a new law. And people 365 00:22:54,119 --> 00:22:56,800 Speaker 1: in Virginia are saying, oh my gosh, overnight, I could 366 00:22:56,800 --> 00:22:57,399 Speaker 1: be a felon. 367 00:22:57,960 --> 00:23:06,800 Speaker 2: Right. Well, election have consequences there, you know, And I 368 00:23:06,840 --> 00:23:11,440 Speaker 2: know Governor Younkin over the past two years had vetoed 369 00:23:11,480 --> 00:23:14,800 Speaker 2: something like twenty four gun control bills that had passed 370 00:23:14,800 --> 00:23:19,280 Speaker 2: through the legislature. The Democrats at the time just had 371 00:23:19,359 --> 00:23:21,639 Speaker 2: like a one vote margin in both the House and 372 00:23:21,680 --> 00:23:24,280 Speaker 2: the Senate, but they were still able to pass all 373 00:23:24,359 --> 00:23:29,639 Speaker 2: those things. At this point, you know, they have a 374 00:23:29,800 --> 00:23:34,040 Speaker 2: huge majority in the state House of Delegates after the election. 375 00:23:34,960 --> 00:23:38,440 Speaker 2: It's still close in the Senate, but you know they're 376 00:23:38,440 --> 00:23:41,560 Speaker 2: going to be able to pass basically almost everything they 377 00:23:41,560 --> 00:23:43,439 Speaker 2: want to pass. It's going to be up to the 378 00:23:43,440 --> 00:23:49,120 Speaker 2: Supreme Court to determine whether or not, you know, what's 379 00:23:49,200 --> 00:23:52,400 Speaker 2: going to be held constitutional or not. And hopefully things 380 00:23:52,440 --> 00:23:55,000 Speaker 2: like the assault weapons ban will eventually make it up 381 00:23:55,000 --> 00:23:57,879 Speaker 2: to the Supreme Court. But you know, there's one thing, 382 00:23:58,600 --> 00:24:01,119 Speaker 2: you know, at the beginning of your comments there about 383 00:24:01,359 --> 00:24:05,200 Speaker 2: kind of the decisions that local officials make in terms 384 00:24:05,240 --> 00:24:08,800 Speaker 2: of law enforcement. I have to say these two deaths, 385 00:24:09,800 --> 00:24:14,800 Speaker 2: Renee Good and Alex Pretty, a large portion of the 386 00:24:14,840 --> 00:24:21,000 Speaker 2: responsibility for their deaths rests with local officials in Minneapolis. 387 00:24:21,440 --> 00:24:23,879 Speaker 2: So and the reason is is that, you know, you 388 00:24:23,920 --> 00:24:27,440 Speaker 2: look in the rest of the country, you don't see 389 00:24:27,760 --> 00:24:33,760 Speaker 2: these types of people impeding ice officers getting the way, 390 00:24:33,880 --> 00:24:38,440 Speaker 2: blocking them. And there's a simple reason why they're able 391 00:24:38,480 --> 00:24:43,359 Speaker 2: to do that in Minnesota is that's because law enforcement 392 00:24:43,400 --> 00:24:47,080 Speaker 2: there is not acting to protect ice. So, for example, 393 00:24:47,200 --> 00:24:50,439 Speaker 2: Pretty apparently a week before he had gotten into a 394 00:24:50,560 --> 00:24:57,320 Speaker 2: violent encounter with ice officers. Apparently, at least the claim 395 00:24:57,440 --> 00:25:02,199 Speaker 2: is he had broken a rib, but at least it 396 00:25:02,240 --> 00:25:05,840 Speaker 2: was a sufficiently violent encounter for him to go and 397 00:25:05,880 --> 00:25:10,359 Speaker 2: break a rib. Now, getting into a violent encounter with 398 00:25:11,119 --> 00:25:15,200 Speaker 2: a federal law enforcement officer as a felony, and if 399 00:25:15,200 --> 00:25:17,919 Speaker 2: he had been arrested, if there had been law enforcement 400 00:25:17,960 --> 00:25:20,239 Speaker 2: there the rest him, I mean to me, you know, 401 00:25:20,440 --> 00:25:23,119 Speaker 2: we mentioned earlier one hundred and thirty of these one 402 00:25:23,240 --> 00:25:27,200 Speaker 2: hundred and seventy Americans who had been detained by ICE 403 00:25:27,600 --> 00:25:32,479 Speaker 2: were detained because they had either assaulted or interfered with 404 00:25:32,640 --> 00:25:37,679 Speaker 2: Ice officers. You know, that seems awfully small to me 405 00:25:38,000 --> 00:25:40,640 Speaker 2: compared to the number of videos and other things I've 406 00:25:40,680 --> 00:25:43,679 Speaker 2: seen in terms of the amount of interferences there. You know, 407 00:25:44,280 --> 00:25:47,920 Speaker 2: Renee Good apparently she had been using her vehicle all 408 00:25:48,040 --> 00:25:51,440 Speaker 2: day long to go and block ice officers. It was 409 00:25:51,520 --> 00:25:55,120 Speaker 2: kind of only at the end of the day that 410 00:25:55,280 --> 00:25:58,359 Speaker 2: Ice finally had had enough that they went over the 411 00:25:58,359 --> 00:26:02,200 Speaker 2: ice officer side of the vehicle asked her to get 412 00:26:02,200 --> 00:26:04,640 Speaker 2: out because he was going to arrest her at that point, 413 00:26:05,000 --> 00:26:07,119 Speaker 2: And it was at that point that she drove her 414 00:26:07,240 --> 00:26:09,960 Speaker 2: vehicle into the other Ice officer who was standing in 415 00:26:10,000 --> 00:26:13,119 Speaker 2: front of the vehicle that was there. But you know, 416 00:26:13,400 --> 00:26:16,640 Speaker 2: in Pretty's case, let's say he had been arrested for 417 00:26:16,720 --> 00:26:19,400 Speaker 2: the violent assault that he had done the week before. 418 00:26:20,040 --> 00:26:21,920 Speaker 2: You know, there's a good chance he would have posted 419 00:26:21,960 --> 00:26:25,960 Speaker 2: bond and been out. But if you're released on bond 420 00:26:26,359 --> 00:26:30,080 Speaker 2: for a felony for assault on a law enforcement officers, 421 00:26:30,600 --> 00:26:34,040 Speaker 2: I hope at least you'd think twice before going and 422 00:26:34,080 --> 00:26:39,919 Speaker 2: getting into another skirmish with law enforcement. That's there. You know, 423 00:26:40,080 --> 00:26:43,920 Speaker 2: if Renee Good had been picked up apparently she'd been 424 00:26:43,960 --> 00:26:47,560 Speaker 2: doing this beforehand, not just that day, and had been 425 00:26:47,600 --> 00:26:51,320 Speaker 2: booked multiple times, you know, there's a reasonable chance that 426 00:26:51,720 --> 00:26:53,840 Speaker 2: she wouldn't have been in the position that she was. 427 00:26:53,880 --> 00:26:58,639 Speaker 2: That neither of these individuals might have died if local 428 00:26:58,720 --> 00:27:01,399 Speaker 2: law enforcement had been doing doing its job and had 429 00:27:01,440 --> 00:27:04,880 Speaker 2: been arresting you know, if if they were being arrested, Uh, 430 00:27:05,119 --> 00:27:07,120 Speaker 2: there's a good chance that they wouldn't even been out 431 00:27:07,119 --> 00:27:09,360 Speaker 2: to begin with. I mean, you have places. 432 00:27:09,359 --> 00:27:12,359 Speaker 1: There's a good chance that that interaction wouldn't have happened. 433 00:27:12,359 --> 00:27:14,960 Speaker 1: You know, they would have already been arrested that day. 434 00:27:15,119 --> 00:27:17,800 Speaker 1: And I think that that's that's something that we have 435 00:27:17,920 --> 00:27:21,040 Speaker 1: tried to portray to people. We've tried to explain to people. Look, 436 00:27:21,080 --> 00:27:24,080 Speaker 1: you have a governor who has said, go out in 437 00:27:24,119 --> 00:27:27,040 Speaker 1: the streets, record them, We're going to prosecute them later. 438 00:27:27,160 --> 00:27:29,640 Speaker 1: Like you're gonna go get a reward for this. We 439 00:27:29,720 --> 00:27:31,920 Speaker 1: can't we can't document all of. 440 00:27:31,840 --> 00:27:35,520 Speaker 2: This week call the Nazis. You have a governor who 441 00:27:35,600 --> 00:27:40,600 Speaker 2: basically compares what's happening to the Nazis taking Anne Frank, 442 00:27:41,800 --> 00:27:45,639 Speaker 2: you know, and so you know, if I really believed 443 00:27:46,080 --> 00:27:48,680 Speaker 2: the people were Nazis there, you know, And this gets 444 00:27:48,680 --> 00:27:53,520 Speaker 2: back to our comparison with Obama. You know, there's nobody 445 00:27:53,800 --> 00:27:56,639 Speaker 2: who you know, you mentioned the CNN video kind of 446 00:27:56,720 --> 00:27:58,840 Speaker 2: lotting what was going on at that time. It was 447 00:27:58,880 --> 00:28:02,080 Speaker 2: the complete opposite. Nobody's going out there and saying that 448 00:28:02,200 --> 00:28:07,959 Speaker 2: even though the Obama administration was detaining American citizens at 449 00:28:08,000 --> 00:28:13,840 Speaker 2: a much much higher rate than Trump did this last year, 450 00:28:14,880 --> 00:28:19,040 Speaker 2: nobody's going out there and calling in Nazis or even 451 00:28:19,080 --> 00:28:22,280 Speaker 2: thought of anything even remotely similar in terms of names. 452 00:28:22,680 --> 00:28:25,439 Speaker 1: Let's take a quick commercial break. We'll continue next on 453 00:28:25,480 --> 00:28:31,880 Speaker 1: the Tutor Dixon podcast. The left really believes that this 454 00:28:31,960 --> 00:28:36,800 Speaker 1: is their turning point for the midterm elections. They used 455 00:28:36,880 --> 00:28:40,080 Speaker 1: this in twenty twenty, and that's a sad thing to me. 456 00:28:40,200 --> 00:28:43,200 Speaker 1: I don't think that the people in power are actually 457 00:28:43,320 --> 00:28:47,000 Speaker 1: passionate about the people who are being deported. I think 458 00:28:47,040 --> 00:28:50,160 Speaker 1: they use this as an inflection point to say, Okay, 459 00:28:50,200 --> 00:28:53,160 Speaker 1: we can turn the election toward us, we can gain 460 00:28:53,240 --> 00:28:55,880 Speaker 1: power back, and that you don't see that on the 461 00:28:55,880 --> 00:29:00,000 Speaker 1: other side, you don't see this manipulation cashion. 462 00:28:59,560 --> 00:29:01,560 Speaker 2: In one way, I've come to believe, you know, the 463 00:29:01,640 --> 00:29:05,200 Speaker 2: question in my mind is why do you fight against 464 00:29:05,360 --> 00:29:10,240 Speaker 2: supporting illegal aliens who your own state has convicted of 465 00:29:10,360 --> 00:29:16,360 Speaker 2: violent crimes and you know, you know, just release child 466 00:29:16,480 --> 00:29:20,240 Speaker 2: rapists back onto the street. You know, people have a 467 00:29:20,280 --> 00:29:23,040 Speaker 2: long history of child rape or other things. And I 468 00:29:23,080 --> 00:29:25,760 Speaker 2: think part of it has to do with the census, 469 00:29:27,120 --> 00:29:31,280 Speaker 2: you know, you have I've seen estimates recently that California 470 00:29:31,360 --> 00:29:35,160 Speaker 2: may have six congressional seats that they otherwise wouldn't have 471 00:29:35,200 --> 00:29:38,840 Speaker 2: gotten because of illegal aliens in the state. All about that, 472 00:29:39,960 --> 00:29:43,240 Speaker 2: and so you know, maybe more than that. You know, 473 00:29:43,320 --> 00:29:45,960 Speaker 2: this is based on the estimates of the number of 474 00:29:46,000 --> 00:29:48,480 Speaker 2: illegal aliens in different states, which I think is a 475 00:29:48,520 --> 00:29:53,520 Speaker 2: clear underestimate of the total in those states. But you know, 476 00:29:54,360 --> 00:29:56,960 Speaker 2: and also they get money from the federal government based 477 00:29:57,000 --> 00:29:59,960 Speaker 2: on how many bodies they have there, whether they're legal 478 00:30:00,600 --> 00:30:05,960 Speaker 2: Americans or illegals, and so you know, I think sanctuary 479 00:30:06,040 --> 00:30:11,880 Speaker 2: states kind of fired depending on being magnets both for 480 00:30:11,960 --> 00:30:14,800 Speaker 2: all types of illegals. And to me, the interesting thing 481 00:30:14,920 --> 00:30:20,239 Speaker 2: is they claim that very few illegals commit crime, and 482 00:30:20,560 --> 00:30:24,200 Speaker 2: as we talked about before, I think the data clearly 483 00:30:24,240 --> 00:30:27,760 Speaker 2: shows the opposite's true. But if they really believe that, 484 00:30:28,280 --> 00:30:32,480 Speaker 2: if they really believed that few illegals commit crimes, then 485 00:30:32,920 --> 00:30:36,440 Speaker 2: it wouldn't affect their congressional representation very much. It wouldn't 486 00:30:36,440 --> 00:30:38,760 Speaker 2: affect the money that they get very much if they 487 00:30:38,800 --> 00:30:42,360 Speaker 2: weren't allowed those to get deported. You know, and I 488 00:30:42,400 --> 00:30:44,840 Speaker 2: was mentioned before in New York State. I basically did 489 00:30:45,200 --> 00:30:50,320 Speaker 2: some simple back of the envelope calculations the detainers that 490 00:30:50,440 --> 00:30:53,640 Speaker 2: ICE has had for New York State. It doesn't break 491 00:30:53,640 --> 00:30:56,040 Speaker 2: it down with whether the person's in prison or in 492 00:30:56,120 --> 00:31:00,880 Speaker 2: jails and their different costs of imprisonment in those two places. 493 00:31:01,800 --> 00:31:04,240 Speaker 2: But if you assume that they're all in prison, which 494 00:31:04,280 --> 00:31:07,680 Speaker 2: is a lower cost, it basically costs New York State 495 00:31:07,720 --> 00:31:10,360 Speaker 2: about a billion dollar over a billion dollars a year 496 00:31:10,480 --> 00:31:13,480 Speaker 2: minimum to go and house those people. And so you 497 00:31:13,560 --> 00:31:16,800 Speaker 2: have to ask yourself, a billion dollars, I mean, the 498 00:31:16,880 --> 00:31:20,360 Speaker 2: state simply could turn them over to ICE and save 499 00:31:20,400 --> 00:31:23,200 Speaker 2: a billion dollars a year. Why don't they do that? 500 00:31:23,960 --> 00:31:26,520 Speaker 2: And you know, so it's not just the fact that 501 00:31:26,560 --> 00:31:31,240 Speaker 2: they release these individuals without notifying ICE into the general population, 502 00:31:31,960 --> 00:31:35,800 Speaker 2: that they serve as basically a magnet because people know 503 00:31:35,880 --> 00:31:38,440 Speaker 2: that there are certain states or cities that they can 504 00:31:38,480 --> 00:31:42,160 Speaker 2: go to in local law enforcement won't turn them over 505 00:31:42,280 --> 00:31:44,400 Speaker 2: to ICE. So that serves as a magnet. 506 00:31:45,080 --> 00:31:47,640 Speaker 1: Well, and I think that is key. That's something that 507 00:31:47,680 --> 00:31:52,600 Speaker 1: people don't understand. Sanctuary cities. They use very nice terminology. 508 00:31:52,720 --> 00:31:55,640 Speaker 1: Sanctuary cities are a place where someone who has committed 509 00:31:55,640 --> 00:31:58,520 Speaker 1: a crime and is not a legal citizen can hide. 510 00:31:58,800 --> 00:32:01,680 Speaker 1: That is all it is. It is not a sanctuary 511 00:32:01,800 --> 00:32:04,520 Speaker 1: for people who are law abiding, who want to live 512 00:32:04,520 --> 00:32:07,000 Speaker 1: in this country, who want to become Americans. It is 513 00:32:07,040 --> 00:32:09,160 Speaker 1: where the worst of the worst go to hide, and 514 00:32:09,320 --> 00:32:14,880 Speaker 1: these politicians are protecting them. And I mean, this is 515 00:32:14,920 --> 00:32:18,120 Speaker 1: what we've been uncovering is it does add to their 516 00:32:18,160 --> 00:32:21,600 Speaker 1: census numbers, it does add to their representation in Washington, 517 00:32:22,160 --> 00:32:25,040 Speaker 1: it does help them gain power, and we're seeing I mean, 518 00:32:25,080 --> 00:32:26,600 Speaker 1: we just had someone on the other day that was 519 00:32:26,640 --> 00:32:30,880 Speaker 1: telling us that even birthright citizenship is allowing people in 520 00:32:30,960 --> 00:32:33,720 Speaker 1: other countries to vote, and there's a whole birth tourism 521 00:32:33,800 --> 00:32:36,160 Speaker 1: issue that we're dealing with. So I mean, I believe 522 00:32:36,200 --> 00:32:38,680 Speaker 1: what you're saying. I think that we have a real problem. 523 00:32:38,960 --> 00:32:41,800 Speaker 1: I appreciate the work that you do to go out 524 00:32:41,800 --> 00:32:44,280 Speaker 1: there and support ICE, and I think that's critical for 525 00:32:44,320 --> 00:32:46,680 Speaker 1: all of us right now to continue that to make 526 00:32:46,720 --> 00:32:49,400 Speaker 1: sure that people understand that our officers are putting their 527 00:32:49,440 --> 00:32:53,080 Speaker 1: lives in the line every day and it's not just 528 00:32:53,400 --> 00:32:56,800 Speaker 1: not fair, it's not right for them to be up 529 00:32:56,840 --> 00:32:59,479 Speaker 1: against elected officials who are telling people to go out 530 00:32:59,520 --> 00:33:00,440 Speaker 1: and get in their faces. 531 00:33:01,000 --> 00:33:03,320 Speaker 2: Well, thank you very much for having me on. People 532 00:33:03,360 --> 00:33:06,560 Speaker 2: can find more information on all the points that we've 533 00:33:06,600 --> 00:33:10,040 Speaker 2: been talking about on our website at crimeresearch dot org, 534 00:33:10,440 --> 00:33:14,120 Speaker 2: crime research dot org and all the links to the 535 00:33:14,200 --> 00:33:18,040 Speaker 2: underlying data so that they can check it out themselves. 536 00:33:17,640 --> 00:33:20,440 Speaker 1: And do that because that helps you to be intelligent 537 00:33:20,480 --> 00:33:22,360 Speaker 1: when you talk about this, because you are going to 538 00:33:22,400 --> 00:33:24,440 Speaker 1: talk about it, whether you like it or not. Someone's 539 00:33:24,480 --> 00:33:25,800 Speaker 1: going to bring it up and you just want to 540 00:33:25,800 --> 00:33:28,720 Speaker 1: have those facts to back you up. Doctor John Lott, 541 00:33:28,720 --> 00:33:30,320 Speaker 1: thank you so much for coming on today. 542 00:33:30,680 --> 00:33:32,840 Speaker 2: Well, it's great talking to you again. Thanks for having 543 00:33:32,840 --> 00:33:33,120 Speaker 2: me on. 544 00:33:33,640 --> 00:33:35,680 Speaker 1: Yeah, good talking to you too, and thank you all 545 00:33:35,720 --> 00:33:38,040 Speaker 1: for listening. As always, you can get your podcast this 546 00:33:38,120 --> 00:33:41,080 Speaker 1: podcast wherever you get your podcasts. You can also watch 547 00:33:41,120 --> 00:33:44,240 Speaker 1: the full video on Rumble and YouTube at Tutor Dixon, 548 00:33:44,400 --> 00:33:46,480 Speaker 1: but just make sure you join us and have a 549 00:33:46,520 --> 00:33:47,040 Speaker 1: blessed day.