1 00:00:00,080 --> 00:00:03,320 Speaker 1: Welcome to today's edition of The Clay Travis and buck 2 00:00:03,360 --> 00:00:06,480 Speaker 1: Sexton Show podcast. Third hour of The Clay Travis buck 3 00:00:06,519 --> 00:00:11,000 Speaker 1: Sexton Show gets going right now, everybody wanted to shift 4 00:00:11,080 --> 00:00:13,880 Speaker 1: our focus for a few moments here to the world 5 00:00:14,000 --> 00:00:20,279 Speaker 1: of criminal justice and some very high profile crimes and 6 00:00:20,400 --> 00:00:24,320 Speaker 1: the investigations the aftermath of them right now, that deserves 7 00:00:24,360 --> 00:00:27,760 Speaker 1: some of our attention. And also what's going on with 8 00:00:27,800 --> 00:00:31,760 Speaker 1: the law enforcement apparatus, the prosecutorial arm of various state 9 00:00:31,800 --> 00:00:35,159 Speaker 1: and local governments. I would just know because Clay and 10 00:00:35,200 --> 00:00:37,880 Speaker 1: I are both and there are a number of different 11 00:00:37,920 --> 00:00:40,199 Speaker 1: cases and incidents I want to get to here. But 12 00:00:40,360 --> 00:00:45,320 Speaker 1: to start off with, there is very little movement, very 13 00:00:45,320 --> 00:00:50,360 Speaker 1: little additional detail at this point about that quadruple murder 14 00:00:50,720 --> 00:00:55,960 Speaker 1: in Idaho. One of the victim's parents, according to The 15 00:00:56,040 --> 00:00:59,600 Speaker 1: Daily Mail here, cryptically claim the means of death between 16 00:00:59,640 --> 00:01:03,240 Speaker 1: two of the students don't match, despite cops saying all 17 00:01:03,280 --> 00:01:06,279 Speaker 1: four were stabbed to death. And they also are claiming 18 00:01:06,280 --> 00:01:10,160 Speaker 1: that the Idaho cops ruled out certain people too quickly. 19 00:01:10,959 --> 00:01:15,320 Speaker 1: So that's there's very little additional information on this one, 20 00:01:15,520 --> 00:01:20,280 Speaker 1: and I haven't They've said they don't want people theorizing publicly, 21 00:01:20,360 --> 00:01:22,360 Speaker 1: and maybe that's part of it, but I honestly think 22 00:01:22,400 --> 00:01:25,000 Speaker 1: it's just hard to even have a theory that holds 23 00:01:25,040 --> 00:01:28,160 Speaker 1: together at this point because there's so little information. So 24 00:01:28,200 --> 00:01:31,800 Speaker 1: we're continuing to watch this very closely, and this is 25 00:01:31,840 --> 00:01:37,640 Speaker 1: just one that the whole community of Idaho is feeling. 26 00:01:37,680 --> 00:01:42,440 Speaker 1: This is still quite frightened, honestly in the immediate environs 27 00:01:42,440 --> 00:01:44,840 Speaker 1: of where this happened. So we'll continue to look at that. 28 00:01:45,280 --> 00:01:48,720 Speaker 1: And then also, you know, Clay, there was this eighty 29 00:01:48,800 --> 00:01:54,760 Speaker 1: three year old man who was in a best oh, 30 00:01:54,760 --> 00:01:59,080 Speaker 1: i'm sorry, a home depot and I saw this today. 31 00:01:59,120 --> 00:02:04,120 Speaker 1: It's one of these ks where this guy, Gary Racer, 32 00:02:04,840 --> 00:02:09,720 Speaker 1: eighty three years old, a thief, was just doing what 33 00:02:09,800 --> 00:02:14,280 Speaker 1: we see in so many of these different theft cases. 34 00:02:14,360 --> 00:02:18,640 Speaker 1: He was filling up his cart with the you know, 35 00:02:18,680 --> 00:02:22,040 Speaker 1: with valuable items. He probably had, I don't know, a 36 00:02:22,080 --> 00:02:26,519 Speaker 1: thousand dollars worth of stuff, maybe more. And this eighty 37 00:02:26,560 --> 00:02:28,560 Speaker 1: three year old worker at home deep he say, he's 38 00:02:28,560 --> 00:02:32,880 Speaker 1: a grant, he's a dad, he's a grandfather, and he 39 00:02:33,040 --> 00:02:36,359 Speaker 1: got shoved to the ground by this criminal. It's all 40 00:02:36,400 --> 00:02:40,120 Speaker 1: on video, and he died from his injuries because in 41 00:02:40,240 --> 00:02:42,280 Speaker 1: eighty three year old man. I mean a lot of them. 42 00:02:42,320 --> 00:02:44,800 Speaker 1: It's it's like shoving a small child or you know, 43 00:02:44,840 --> 00:02:47,160 Speaker 1: a baby. If it's somebody who is not able to 44 00:02:47,200 --> 00:02:52,919 Speaker 1: defend themselves, they have much higher incidents of extreme injury 45 00:02:52,600 --> 00:02:55,120 Speaker 1: for any from any kind of a blunt force trauma 46 00:02:55,280 --> 00:03:00,600 Speaker 1: or serious fall. And I hadn't even seen this until today. 47 00:03:01,240 --> 00:03:03,680 Speaker 1: They don't have they have video of the guy. They 48 00:03:03,720 --> 00:03:07,200 Speaker 1: still don't have him in custody. They don't have I 49 00:03:07,200 --> 00:03:09,919 Speaker 1: don't even think they know who the suspect is quite yet. 50 00:03:10,639 --> 00:03:13,040 Speaker 1: But I just think this is indicative of what's happening 51 00:03:13,520 --> 00:03:17,280 Speaker 1: all over the country now, where it's just supposed, it's 52 00:03:17,280 --> 00:03:21,320 Speaker 1: been normalized that people can steal and even be violent 53 00:03:21,639 --> 00:03:25,000 Speaker 1: in the process of that theft, and there's no urgency 54 00:03:25,240 --> 00:03:29,080 Speaker 1: in these democrat run cities to do anything about this. 55 00:03:29,280 --> 00:03:33,440 Speaker 1: What was that It wasn't Costcode, It was another one 56 00:03:33,440 --> 00:03:35,800 Speaker 1: of the major stores. You know, it wasn't Walmart. I 57 00:03:35,800 --> 00:03:39,360 Speaker 1: forget which one. Kmart's gone, right, It wasn't Kmart, Target, 58 00:03:39,520 --> 00:03:43,560 Speaker 1: but Target, thank you. It was Target four hundred million 59 00:03:43,640 --> 00:03:47,760 Speaker 1: dollars of theft last year of theft. Well, I mean, 60 00:03:48,000 --> 00:03:52,560 Speaker 1: it's it's like we're it's like we've decriminalized stealing. That's 61 00:03:52,560 --> 00:03:55,040 Speaker 1: what we have. I mean, you saw I'm sure the 62 00:03:55,160 --> 00:03:58,320 Speaker 1: viral video. I believe it was from the LA area. 63 00:03:58,520 --> 00:04:01,640 Speaker 1: I know it was California of the Apple store being 64 00:04:01,720 --> 00:04:05,960 Speaker 1: robbed on the Friday after Thanksgiving, middle broad daylight. Guys 65 00:04:06,040 --> 00:04:08,000 Speaker 1: just run in. I think they were guys. They had 66 00:04:08,040 --> 00:04:10,760 Speaker 1: masks on, of course, because now you can wear masks 67 00:04:10,760 --> 00:04:13,200 Speaker 1: with impunity, which we talked about for some time was 68 00:04:13,240 --> 00:04:15,280 Speaker 1: going to potentially be a major issue when it came 69 00:04:15,280 --> 00:04:19,000 Speaker 1: to crime. But they had They were grabbing as much 70 00:04:19,040 --> 00:04:22,440 Speaker 1: as they could of the iPhones. They get outside, they're 71 00:04:22,440 --> 00:04:29,080 Speaker 1: not caught, and this is happening everywhere, and the overall 72 00:04:29,160 --> 00:04:33,440 Speaker 1: response to it is, well, some of these left wingers 73 00:04:33,440 --> 00:04:36,880 Speaker 1: just say, remember when they were writing the stories like, hey, really, 74 00:04:36,960 --> 00:04:40,240 Speaker 1: your possessions aren't that important. Other people are entitled to them. 75 00:04:40,400 --> 00:04:42,599 Speaker 1: When they were writing that in San Francisco, as home 76 00:04:42,640 --> 00:04:45,520 Speaker 1: invasions were happening and people were just taking things from 77 00:04:45,520 --> 00:04:49,800 Speaker 1: outside of those homes and carrying them out. This is 78 00:04:50,400 --> 00:04:53,599 Speaker 1: part and parcel of where we've gone with defund the police. 79 00:04:53,600 --> 00:04:55,960 Speaker 1: And I was reading the Wall Street Journal in the 80 00:04:56,000 --> 00:04:58,240 Speaker 1: last couple of days buck they had a graphic I 81 00:04:58,279 --> 00:05:02,320 Speaker 1: think I shared it with you. Murder in the United States. 82 00:05:02,360 --> 00:05:05,800 Speaker 1: The rates obviously we've skyrocketed in murder, but do you 83 00:05:05,839 --> 00:05:10,880 Speaker 1: know that almost all of the increase is Black murders. 84 00:05:11,440 --> 00:05:14,479 Speaker 1: That is, when you look at the rates of murder 85 00:05:14,960 --> 00:05:19,720 Speaker 1: basically for black people, it's back in the nineteen nineties. Again, 86 00:05:19,920 --> 00:05:23,280 Speaker 1: the rates of Hispanic Asian white murder, they haven't really 87 00:05:23,320 --> 00:05:26,360 Speaker 1: budged anywhere near as much. But if you look at 88 00:05:26,400 --> 00:05:30,839 Speaker 1: the graphical data for black people, the rates of murder 89 00:05:30,880 --> 00:05:33,560 Speaker 1: are the same as they were in the early nineties now, 90 00:05:34,200 --> 00:05:38,200 Speaker 1: and as a result, the overall rate of murder in 91 00:05:38,240 --> 00:05:42,080 Speaker 1: this country is skyrocketing. And people it's the third rail. 92 00:05:42,160 --> 00:05:44,120 Speaker 1: They won't touch it on the left side of the 93 00:05:44,120 --> 00:05:49,560 Speaker 1: political equation. But the lasting legacy of the Black Lives 94 00:05:49,600 --> 00:05:53,280 Speaker 1: Matter movement has been that far more Black people are 95 00:05:53,279 --> 00:05:57,240 Speaker 1: being murdered in America than were before BLM started. And 96 00:05:57,320 --> 00:06:01,080 Speaker 1: if you unpack why that has occurred, it's because we 97 00:06:01,279 --> 00:06:05,320 Speaker 1: have created a dynamic where police are the bad guy, 98 00:06:05,800 --> 00:06:10,960 Speaker 1: and the reality is police protect more black lives by 99 00:06:11,040 --> 00:06:15,600 Speaker 1: far than any other aspect of certainly the government in 100 00:06:15,640 --> 00:06:18,840 Speaker 1: the country. And when you tell police they can't do 101 00:06:18,880 --> 00:06:23,560 Speaker 1: their job, the overwhelming victims become black, and that's the 102 00:06:23,640 --> 00:06:26,960 Speaker 1: legacy of BLM. That's the truth. Nobody you'll touch it 103 00:06:26,960 --> 00:06:28,719 Speaker 1: on the left because it's a third rail and that 104 00:06:28,760 --> 00:06:33,160 Speaker 1: would require analyzing and then you can't say, oh, everybody's 105 00:06:33,160 --> 00:06:35,880 Speaker 1: a victim. But that's what's going on. That's where the 106 00:06:35,960 --> 00:06:40,599 Speaker 1: murder rate skyrocket is happening. It's in the black community. Overwhelmingly, 107 00:06:40,680 --> 00:06:43,480 Speaker 1: you are murdered by someone of your own race. And unfortunately, 108 00:06:43,520 --> 00:06:45,839 Speaker 1: as we've talked about Buck, even with that Idaho connection, 109 00:06:46,720 --> 00:06:50,920 Speaker 1: usually victims of murder know the person who is murdering them. 110 00:06:51,040 --> 00:06:54,440 Speaker 1: It's far scarier the idea of random acts of violence. 111 00:06:54,480 --> 00:06:57,800 Speaker 1: But almost always, if you're going to be killed, it's 112 00:06:57,880 --> 00:07:01,279 Speaker 1: someone that you know, and oftentimes the same race as you, 113 00:07:01,360 --> 00:07:05,400 Speaker 1: almost overwhelmingly with your Black, Asian, White, Hispanic. And this 114 00:07:05,480 --> 00:07:08,680 Speaker 1: idea of a perpetrator who doesn't know anybody is is 115 00:07:08,720 --> 00:07:11,400 Speaker 1: top of mind because it's so fear inducing, but it 116 00:07:11,440 --> 00:07:13,920 Speaker 1: isn't the reality, and it's happening all over the country. 117 00:07:14,160 --> 00:07:16,480 Speaker 1: And you know, there's also been a little bit of 118 00:07:16,480 --> 00:07:20,960 Speaker 1: reporting about another crime. So just to be clear, the 119 00:07:21,080 --> 00:07:23,080 Speaker 1: incident with the eighty three year old guy shoved to 120 00:07:23,160 --> 00:07:25,240 Speaker 1: the ground. He died of his injuries from that it 121 00:07:25,320 --> 00:07:28,600 Speaker 1: was eight hundred dollars of pressure washing. Where was this 122 00:07:29,040 --> 00:07:34,360 Speaker 1: line to steal? This was in North Carolina, Hillsboro, North Carolina. Okay, 123 00:07:34,640 --> 00:07:39,040 Speaker 1: and then you have Wauka Shaw. We all remember what 124 00:07:39,080 --> 00:07:43,280 Speaker 1: happened in show. The media made that story disappear very quickly. 125 00:07:43,560 --> 00:07:45,440 Speaker 1: Did anyone even remember there was a mass shooting it? 126 00:07:45,640 --> 00:07:48,080 Speaker 1: I think? Was it at UVA? Recently? No? I don't 127 00:07:48,080 --> 00:07:50,520 Speaker 1: think they do. Does anyone remember any of the mass 128 00:07:50,520 --> 00:07:52,840 Speaker 1: shootings that have occurred in the last two weeks? They 129 00:07:52,960 --> 00:07:57,000 Speaker 1: disappeared very quickly. I wonder why that is the last. 130 00:07:57,120 --> 00:07:59,760 Speaker 1: That's such a good point buck, the last three mass shootings, 131 00:08:00,240 --> 00:08:05,320 Speaker 1: the one in Colorado, everybody blamed anti transgender activist, and 132 00:08:05,360 --> 00:08:07,080 Speaker 1: then as soon as it came out that this guy 133 00:08:07,240 --> 00:08:10,280 Speaker 1: was again I think a nonine. I remember the LGBTQ 134 00:08:10,440 --> 00:08:14,320 Speaker 1: plus community himself story vanished like I haven't even I'm 135 00:08:14,360 --> 00:08:16,960 Speaker 1: not even kidding. I've barely seen a headline about that 136 00:08:17,000 --> 00:08:20,880 Speaker 1: story since that happened. Unfortunately, the UVA shooting was a 137 00:08:20,920 --> 00:08:24,760 Speaker 1: former football player walk on who killed members of his team, 138 00:08:25,080 --> 00:08:28,440 Speaker 1: and then the shooting in Virginia again, right, wasn't the 139 00:08:28,440 --> 00:08:32,000 Speaker 1: shooting in Virginia at the Walmart Chesapeake, Virginia area that's 140 00:08:32,200 --> 00:08:36,160 Speaker 1: also a former employee, but a black guy, mass shootings 141 00:08:36,200 --> 00:08:40,720 Speaker 1: three of them LGBTQ, two black guys. Story vanishes as 142 00:08:40,760 --> 00:08:43,440 Speaker 1: soon as the details come out about who is to blame, 143 00:08:43,559 --> 00:08:47,120 Speaker 1: They're gone. And this Waka Shaw case that happened almost 144 00:08:47,120 --> 00:08:50,200 Speaker 1: exactly a year ago at the Christmas parade vanished almost 145 00:08:50,200 --> 00:08:53,480 Speaker 1: as soon as it happened. Mass murder by somebody with 146 00:08:53,559 --> 00:08:58,200 Speaker 1: a long history of anti white hatred online. You don't 147 00:08:58,240 --> 00:09:00,640 Speaker 1: hear about that very often, do you. Here's how NBC 148 00:09:00,920 --> 00:09:04,160 Speaker 1: News though this is a story about how oh waukash 149 00:09:04,280 --> 00:09:06,800 Speaker 1: is having It's Chris's Parade again. I want you to 150 00:09:06,840 --> 00:09:12,640 Speaker 1: just hear a part of this segment. Play the clip eleven. 151 00:09:12,679 --> 00:09:15,520 Speaker 1: I think it is in Waukashaw, Wisconsin. The town just 152 00:09:15,679 --> 00:09:18,679 Speaker 1: finished marching and its annual Christmas parade. Of course, it 153 00:09:18,760 --> 00:09:21,120 Speaker 1: was one year ago that a man drove a car 154 00:09:21,200 --> 00:09:25,280 Speaker 1: into that crowd, killing six. Tonight, residents returned celebrating the 155 00:09:25,320 --> 00:09:30,120 Speaker 1: lives lost and the town's determination to keep the tradition going. Tonight, 156 00:09:30,320 --> 00:09:34,200 Speaker 1: Waukesh's Christmas Parade is back, bigger and stronger than ever, 157 00:09:34,400 --> 00:09:37,800 Speaker 1: the community turning up in force. One year after tragedy 158 00:09:37,840 --> 00:09:40,480 Speaker 1: struck when a man drove an suv through the parade, 159 00:09:40,640 --> 00:09:45,839 Speaker 1: killing six people and injuring dozens more. A man drove 160 00:09:45,960 --> 00:09:49,920 Speaker 1: an suv through the parade. You hear that, You say, 161 00:09:49,960 --> 00:09:53,720 Speaker 1: do we know anything else about the murderer here? Oh wait, 162 00:09:53,760 --> 00:10:02,440 Speaker 1: hold on a second. The words murder, terrorism, crime, hate crime, motive, white, black, 163 00:10:02,720 --> 00:10:05,240 Speaker 1: None of this was a two minute long national NBC 164 00:10:05,360 --> 00:10:08,079 Speaker 1: news segment play. I went over it twice to make 165 00:10:08,120 --> 00:10:11,920 Speaker 1: sure not a single time were the words murder, terrorism, 166 00:10:12,000 --> 00:10:15,160 Speaker 1: hate crime, motive, white or black used in the entire 167 00:10:15,200 --> 00:10:19,720 Speaker 1: two minute national news piece. I wonder why that is. 168 00:10:19,920 --> 00:10:23,000 Speaker 1: I mean, the guy is he's going away for life 169 00:10:23,040 --> 00:10:27,200 Speaker 1: for six murders. Yeah, it's already over. And yet they 170 00:10:27,200 --> 00:10:29,079 Speaker 1: don't even they don't even say he's a murder. They 171 00:10:29,080 --> 00:10:31,719 Speaker 1: make it seem like he got lost because his GPS 172 00:10:31,840 --> 00:10:36,240 Speaker 1: was malfunctioning. These people are grotesque. Well, remember the headlines 173 00:10:36,320 --> 00:10:40,120 Speaker 1: for a while just said suv plows through as if 174 00:10:40,120 --> 00:10:42,840 Speaker 1: nobody was driving it. That was the way they tried it. Yes, 175 00:10:42,920 --> 00:10:44,720 Speaker 1: it was like it was like the suv was possessed 176 00:10:44,720 --> 00:10:48,000 Speaker 1: by a spirit. And what I would say is and 177 00:10:48,120 --> 00:10:50,559 Speaker 1: this is such a good if you're a kid, you know, 178 00:10:50,600 --> 00:10:53,119 Speaker 1: I know, we got young people out there listening. Sometimes. 179 00:10:53,559 --> 00:10:58,199 Speaker 1: I think media criticism is an incredibly valid thing for 180 00:10:58,240 --> 00:11:01,000 Speaker 1: you to be writing and studying if you were a kid. 181 00:11:01,840 --> 00:11:07,240 Speaker 1: Compare the way that the Buffalo supermarket shooting has been covered. 182 00:11:07,920 --> 00:11:10,680 Speaker 1: Every time you see a story about that one, it's 183 00:11:10,840 --> 00:11:16,000 Speaker 1: white guy targets black the supermarket and black neighborhood tries 184 00:11:16,040 --> 00:11:19,640 Speaker 1: to kill based on race. Compare the way the media 185 00:11:19,760 --> 00:11:23,880 Speaker 1: covered the Buffalo shooting, which is heinous and awful, with 186 00:11:24,280 --> 00:11:28,600 Speaker 1: the Waukesha story. And the point here that is quite 187 00:11:28,600 --> 00:11:35,000 Speaker 1: clear is motive matters. When it is an awful white guy, right, 188 00:11:35,400 --> 00:11:41,079 Speaker 1: awful white guy headline everywhere. When it's an awful person 189 00:11:41,280 --> 00:11:46,280 Speaker 1: of another race, the story very often vanishes or it 190 00:11:46,320 --> 00:11:50,120 Speaker 1: becomes a story almost exclusively about the victims. But just 191 00:11:50,200 --> 00:11:52,680 Speaker 1: I mean, it would be such a fascinating study example, 192 00:11:52,880 --> 00:11:55,520 Speaker 1: and there's people out there who would do media criticism. 193 00:11:55,559 --> 00:11:59,840 Speaker 1: I would love to see a real in depth analysis 194 00:12:00,040 --> 00:12:02,480 Speaker 1: of the way the Buffalo shooting has been covered compared 195 00:12:02,520 --> 00:12:04,560 Speaker 1: to the WALKA Shaw And then you can compare Buffalo 196 00:12:04,600 --> 00:12:07,480 Speaker 1: shooting to the just compare the headlines for the lg 197 00:12:07,640 --> 00:12:09,920 Speaker 1: et Q when it looked like a random white guy, 198 00:12:09,960 --> 00:12:11,880 Speaker 1: I mean, right, head done it compared to when it's 199 00:12:11,880 --> 00:12:15,280 Speaker 1: a member of TQ, you don't even have to try hard. 200 00:12:15,280 --> 00:12:17,200 Speaker 1: In New York. In New York City, for example, New 201 00:12:17,280 --> 00:12:20,439 Speaker 1: York One, which is like the communist the communist local 202 00:12:20,480 --> 00:12:24,679 Speaker 1: news source, they'll run store and any of the honestly 203 00:12:24,720 --> 00:12:29,839 Speaker 1: the non right wing news sources that you could look 204 00:12:29,840 --> 00:12:33,000 Speaker 1: at for New York City will will do the same thing. 205 00:12:33,200 --> 00:12:37,000 Speaker 1: They'll have Oh, there was a suspect this morning in 206 00:12:37,080 --> 00:12:41,160 Speaker 1: an attempted rape of a woman in Prospect Park, Brooklyn. 207 00:12:41,800 --> 00:12:45,120 Speaker 1: The suspect is five foot ten, one hundred and eighty 208 00:12:45,120 --> 00:12:48,840 Speaker 1: pounds wearing a T shirt. And then you'll actually sometimes 209 00:12:48,880 --> 00:12:52,600 Speaker 1: see that there's more detail than that, but they will 210 00:12:52,640 --> 00:12:54,520 Speaker 1: not give it. They won't get the race. In fact, 211 00:12:54,600 --> 00:12:57,839 Speaker 1: sometimes the funniest thing and it's like, you know, not 212 00:12:57,920 --> 00:13:01,400 Speaker 1: really funny, but the oddest thing is when they will 213 00:13:01,440 --> 00:13:04,720 Speaker 1: do that the suspect is five ten, one hundred and 214 00:13:04,760 --> 00:13:08,640 Speaker 1: eighty five pounds wearing a T shirt, but they'll actually 215 00:13:08,640 --> 00:13:10,720 Speaker 1: have a photo of him on the screen because they're 216 00:13:10,760 --> 00:13:15,520 Speaker 1: surveillance camera. But they don't want to say it because 217 00:13:15,600 --> 00:13:19,040 Speaker 1: they think that that's problematic, And you say to yourself, wait, 218 00:13:20,000 --> 00:13:23,560 Speaker 1: we don't make determinating the suspect could be of any background, 219 00:13:23,640 --> 00:13:25,280 Speaker 1: or we just want to know who the suspect is 220 00:13:25,320 --> 00:13:28,840 Speaker 1: so we can find him and keep people safe. Moral 221 00:13:28,880 --> 00:13:31,280 Speaker 1: people don't make judgones about people based upon the individual 222 00:13:31,559 --> 00:13:34,160 Speaker 1: the acts of one individual. So why does the left 223 00:13:34,200 --> 00:13:38,079 Speaker 1: always do this? Well wokeness, Their minds are broken. Identity 224 00:13:38,120 --> 00:13:41,200 Speaker 1: politics requires a victim pyramid, and if the wrong people 225 00:13:41,480 --> 00:13:45,520 Speaker 1: are involved in a story, then they just get ignored. 226 00:13:45,640 --> 00:13:48,400 Speaker 1: Story vanishes. It really is amazing once you start to 227 00:13:48,400 --> 00:13:51,199 Speaker 1: see the narrative. There are only a few days the 228 00:13:51,280 --> 00:13:54,520 Speaker 1: Left to order Tuttle Twins books before the shipping deadline 229 00:13:54,559 --> 00:13:57,160 Speaker 1: if you want to have him before Christmas. Great books 230 00:13:57,200 --> 00:13:59,840 Speaker 1: for kids, but they do so much more, opening up 231 00:13:59,880 --> 00:14:02,680 Speaker 1: interesting discussion about things that really matter for your kids 232 00:14:02,760 --> 00:14:05,880 Speaker 1: future as well as our country. I've got these books 233 00:14:05,960 --> 00:14:08,960 Speaker 1: at my house. 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Welcome back in 250 00:15:01,280 --> 00:15:06,080 Speaker 1: Clay Travis buck Sexton show Monday edition of the program. 251 00:15:06,080 --> 00:15:10,160 Speaker 1: Talking a lot about the Twitter release and the fact 252 00:15:10,320 --> 00:15:12,200 Speaker 1: Buck that there is more to come, and I think 253 00:15:12,240 --> 00:15:14,720 Speaker 1: you hit on it, and certainly I talked about this 254 00:15:14,760 --> 00:15:17,800 Speaker 1: on Fox News over the weekend. The thing to me 255 00:15:17,880 --> 00:15:23,120 Speaker 1: that is the most intriguing about the release of internal 256 00:15:23,160 --> 00:15:26,960 Speaker 1: Twitter deliberations and debate surrounding the censorship of the New 257 00:15:27,040 --> 00:15:31,800 Speaker 1: York Post story is thinking about what the data is 258 00:15:31,840 --> 00:15:34,960 Speaker 1: going to reflect, what the emails are going to show 259 00:15:35,040 --> 00:15:41,280 Speaker 1: us between the Biden administration and the and their friends 260 00:15:41,320 --> 00:15:44,800 Speaker 1: in big tech about COVID because I think the most 261 00:15:44,800 --> 00:15:48,720 Speaker 1: significant censorship that is going to have occurred at anywhere 262 00:15:49,360 --> 00:15:52,640 Speaker 1: is going to be related to anybody out there who 263 00:15:52,720 --> 00:15:55,920 Speaker 1: questioned the COVID shots. Anybody who said, hey, we have 264 00:15:56,000 --> 00:15:59,080 Speaker 1: to open back up schools, anybody who said masks and 265 00:15:59,160 --> 00:16:02,520 Speaker 1: don't work. I would be surprised if there isn't a 266 00:16:02,600 --> 00:16:06,840 Speaker 1: long list of Biden administration attempts for censorship there, and 267 00:16:06,880 --> 00:16:09,400 Speaker 1: we know we've been way ahead. I would argue of 268 00:16:09,400 --> 00:16:12,920 Speaker 1: this story because Alex Berenson provided the receipts of the 269 00:16:12,960 --> 00:16:17,120 Speaker 1: Biden administration effectively getting him removed from Twitter because of 270 00:16:17,160 --> 00:16:20,240 Speaker 1: the data that he was sharing about the COVID shots. Oh, 271 00:16:20,280 --> 00:16:22,200 Speaker 1: there's going to be a lot more than just Barrenson. 272 00:16:22,880 --> 00:16:25,840 Speaker 1: I think you and I might find out some interesting 273 00:16:25,880 --> 00:16:29,760 Speaker 1: stuff about some of the Twitter censorship that has occurred, 274 00:16:30,200 --> 00:16:33,360 Speaker 1: because if you were very I always thought that masking 275 00:16:33,440 --> 00:16:37,160 Speaker 1: was the gateway drug to the rest of the COVID addiction, 276 00:16:37,360 --> 00:16:40,040 Speaker 1: right that once you got people to believe in masking 277 00:16:40,040 --> 00:16:42,280 Speaker 1: in a mask up, all the rest of it was 278 00:16:42,360 --> 00:16:44,880 Speaker 1: just was rudimentary, and all the rest of it fell 279 00:16:44,880 --> 00:16:48,280 Speaker 1: into place. And if you were really opposed to masking, 280 00:16:48,440 --> 00:16:51,000 Speaker 1: you were getting hit by any number of different social 281 00:16:51,000 --> 00:16:54,280 Speaker 1: media platforms, so we know that was happening. My problem 282 00:16:54,320 --> 00:16:56,840 Speaker 1: with all this, Clay is we get to the sow 283 00:16:56,920 --> 00:16:59,840 Speaker 1: what pretty quickly here. Yeah, it's important that we know 284 00:16:59,880 --> 00:17:02,920 Speaker 1: the truth. It's important that the facts get out about 285 00:17:02,920 --> 00:17:06,600 Speaker 1: what the bind administration has done with its power and 286 00:17:07,000 --> 00:17:10,479 Speaker 1: using these companies effectively as agents of the government. These 287 00:17:10,520 --> 00:17:14,280 Speaker 1: are First Amendment violations, but usually the recourse to or 288 00:17:14,320 --> 00:17:16,919 Speaker 1: First Amendent violation is, you know, you go to court 289 00:17:16,960 --> 00:17:19,959 Speaker 1: and you get the court to stop the violator of 290 00:17:20,000 --> 00:17:23,080 Speaker 1: your First Amendment rights from doing what they're doing. You know, 291 00:17:23,080 --> 00:17:24,720 Speaker 1: you get to publish the book or you get to 292 00:17:24,800 --> 00:17:28,800 Speaker 1: air the special or whatever it may be. What real 293 00:17:29,520 --> 00:17:32,520 Speaker 1: payback can there be for people who have been shut 294 00:17:32,560 --> 00:17:36,320 Speaker 1: down by Biden for reasons of politics. You know, you 295 00:17:36,320 --> 00:17:39,240 Speaker 1: could say that they'll get sued or there's some lawsuits. 296 00:17:40,080 --> 00:17:41,639 Speaker 1: Very unlike and first of all, it's not going to 297 00:17:41,680 --> 00:17:44,480 Speaker 1: mean anything about Biden. He's got plenty of federal lawyers 298 00:17:44,480 --> 00:17:46,680 Speaker 1: are going to defend the actual president. Second of all, 299 00:17:47,160 --> 00:17:48,639 Speaker 1: how do you make it right? I don't know that 300 00:17:48,680 --> 00:17:51,480 Speaker 1: we can make it right. That's a really good question. 301 00:17:51,520 --> 00:17:53,400 Speaker 1: I think. By the way, open up phone lines eight 302 00:17:53,480 --> 00:17:56,200 Speaker 1: hundred two A two two eight eight two you can 303 00:17:56,280 --> 00:18:00,119 Speaker 1: react ask us any of those questions surrounding this blockbuster story, 304 00:18:00,840 --> 00:18:04,560 Speaker 1: rising inflation, a violatile stock market, wreaking havoc on retirement accounts. 305 00:18:04,960 --> 00:18:09,040 Speaker 1: Until all this economic turmoil turns around, Phoenix Capital Groups 306 00:18:09,080 --> 00:18:12,720 Speaker 1: suggests you diversify your investments. 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You should only 314 00:18:30,240 --> 00:18:32,359 Speaker 1: invest if you can afford to bear the risk of lass. 315 00:18:32,720 --> 00:18:35,800 Speaker 1: Before making investment decisions, you should carefully consider and review 316 00:18:35,880 --> 00:18:38,480 Speaker 1: all risks. This investment has been audited and involved with 317 00:18:38,520 --> 00:18:41,840 Speaker 1: the sec The website address and phone number first website 318 00:18:41,840 --> 00:18:46,960 Speaker 1: address investing with PHX dot com. That's investing with phx 319 00:18:47,040 --> 00:18:50,320 Speaker 1: dot com. Or call this number three two three Phoenix 320 00:18:50,359 --> 00:18:58,000 Speaker 1: that's three two three, pH Oe Nix. I will be 321 00:18:58,040 --> 00:19:02,480 Speaker 1: getting a lawyer. I will be suing the Democratic National Committee. 322 00:19:02,920 --> 00:19:05,679 Speaker 1: No matter what, whether I win or lose, I am 323 00:19:05,800 --> 00:19:08,640 Speaker 1: going to stand up for the rights that every American 324 00:19:08,800 --> 00:19:13,000 Speaker 1: nuts was so called celebrity. I'm not a celebrity. I'm 325 00:19:13,119 --> 00:19:16,840 Speaker 1: hardly recognizable anymore because my career has been destroyed by 326 00:19:16,920 --> 00:19:20,480 Speaker 1: these very people. And I will sue, and I'm hoping 327 00:19:20,480 --> 00:19:22,800 Speaker 1: other people will sue. And if it turns out there 328 00:19:22,800 --> 00:19:25,600 Speaker 1: a lot of us on this list, whether the DNC's 329 00:19:25,640 --> 00:19:28,960 Speaker 1: targeted us, and I will quote the immortal words of 330 00:19:29,119 --> 00:19:33,080 Speaker 1: Joseph Welch when he attacked Joe McCarthy. But the enemy's 331 00:19:33,119 --> 00:19:37,919 Speaker 1: list he had at long Laster, Have you no shame? 332 00:19:39,640 --> 00:19:42,879 Speaker 1: That was James Woods. You all remember if you were 333 00:19:42,920 --> 00:19:46,520 Speaker 1: watching Tucker's show last week, James Woods called in on 334 00:19:46,600 --> 00:19:51,600 Speaker 1: Friday after the DNS, after the Twitter, well Twitter DNC revelations, 335 00:19:51,920 --> 00:19:55,399 Speaker 1: and you know, Clay, I had the honor of just 336 00:19:55,600 --> 00:19:59,280 Speaker 1: randomly bumping into James in Los Angeles over the summer 337 00:19:59,320 --> 00:20:02,000 Speaker 1: with Carrie, sat down with them for a couple of hours, 338 00:20:02,320 --> 00:20:04,520 Speaker 1: just talked to him. I bumped into him at a hotel. 339 00:20:04,520 --> 00:20:07,560 Speaker 1: We just talked about everything. That guy is first of all, 340 00:20:07,800 --> 00:20:13,840 Speaker 1: very high wattage, very just sharp, smart and and fiercely 341 00:20:14,119 --> 00:20:19,400 Speaker 1: protective of the Constitution, a staunch conservative, really interesting guy 342 00:20:19,440 --> 00:20:22,600 Speaker 1: to talk to and has. He says he's been blackballed 343 00:20:22,640 --> 00:20:25,040 Speaker 1: because he's a conservative. He's been in some he had 344 00:20:25,080 --> 00:20:27,800 Speaker 1: some great roles in the past, hasn't been cast in 345 00:20:27,840 --> 00:20:30,600 Speaker 1: anything in recent in you know, the last decade, really 346 00:20:31,880 --> 00:20:34,080 Speaker 1: and and I think that he's just speaking for a 347 00:20:34,080 --> 00:20:35,920 Speaker 1: lot of people when he says we just got to 348 00:20:35,960 --> 00:20:38,720 Speaker 1: find ways to take the fight to the other side. 349 00:20:38,760 --> 00:20:41,240 Speaker 1: Here James Wood says he's going to sue, which makes 350 00:20:41,720 --> 00:20:45,680 Speaker 1: sense to me. I don't know if lawsuits alone, we'll 351 00:20:45,720 --> 00:20:49,000 Speaker 1: do it, but that doesn't mean, you know, you shouldn't try. 352 00:20:50,280 --> 00:20:52,360 Speaker 1: So We'll have to see how this continues to play out. 353 00:20:52,359 --> 00:20:54,040 Speaker 1: Because I think there's a lot more coming as well. 354 00:20:54,080 --> 00:20:56,320 Speaker 1: I think the next round of revelations will be even 355 00:20:56,359 --> 00:20:58,960 Speaker 1: more damning for the left and for the Biden White 356 00:20:58,960 --> 00:21:02,480 Speaker 1: House well forward. I think some people say, okay, what 357 00:21:02,600 --> 00:21:06,359 Speaker 1: should happen? Elon Musk actually did, and I would encourage 358 00:21:06,359 --> 00:21:09,639 Speaker 1: people if you're interested in hearing from Elon himself. He 359 00:21:09,720 --> 00:21:13,760 Speaker 1: did a multi hour spaces on Twitter. Spaces is where 360 00:21:13,800 --> 00:21:16,960 Speaker 1: you can have an audio conversation, and I actually got 361 00:21:17,000 --> 00:21:19,800 Speaker 1: in there and asked a question of Elon and he 362 00:21:19,840 --> 00:21:21,639 Speaker 1: was doing a great job responding to a lot of 363 00:21:21,640 --> 00:21:25,359 Speaker 1: different questions. But if I could waive a magic wand 364 00:21:25,400 --> 00:21:27,960 Speaker 1: going forward, people say, how do you deal with this 365 00:21:28,080 --> 00:21:31,720 Speaker 1: big tech collusion with the Biden administration. I think every 366 00:21:31,760 --> 00:21:37,120 Speaker 1: time the government makes a request of Twitter for censorship 367 00:21:37,440 --> 00:21:41,040 Speaker 1: or pulling down a tweet or getting anybody banned from Twitter, 368 00:21:41,720 --> 00:21:46,359 Speaker 1: it should be public and sunlight is the great disinfectant. 369 00:21:46,680 --> 00:21:49,000 Speaker 1: But also I think it shows and this would be 370 00:21:49,040 --> 00:21:53,840 Speaker 1: for Democrats or Republicans, independence anyone. It elevates to me 371 00:21:54,040 --> 00:21:58,040 Speaker 1: James Woods to know that the Biden White House is 372 00:21:58,080 --> 00:22:03,680 Speaker 1: obsessing over what James Woods is tweeting, and it diminishes 373 00:22:03,720 --> 00:22:07,760 Speaker 1: the White House. It also shows them as being censorious 374 00:22:07,760 --> 00:22:10,679 Speaker 1: in nature. And I think the number of requests for 375 00:22:10,880 --> 00:22:13,840 Speaker 1: things to be pulled off of social media would diminish 376 00:22:13,960 --> 00:22:17,879 Speaker 1: very quickly if the government had to be attached publicly 377 00:22:18,200 --> 00:22:21,240 Speaker 1: to their requests for censorship, because I think it would 378 00:22:21,280 --> 00:22:24,879 Speaker 1: make any administration look petty and bad to be trying 379 00:22:24,920 --> 00:22:28,280 Speaker 1: to get political rival opinions taken down. So that would 380 00:22:28,320 --> 00:22:31,240 Speaker 1: be one of my solutions going forward. And that's what 381 00:22:31,359 --> 00:22:35,080 Speaker 1: I asked Evon Musk about on Saturday during that open 382 00:22:35,119 --> 00:22:39,879 Speaker 1: public spaces Mike in Mobile, Alabama has some thoughts. We 383 00:22:39,920 --> 00:22:41,240 Speaker 1: want to take some calls. Now, what do you got 384 00:22:41,240 --> 00:22:50,600 Speaker 1: for us? Mike? Mike going once, going twice? Do you 385 00:22:50,600 --> 00:22:53,840 Speaker 1: hear him? I don't know. I think I think Mike 386 00:22:54,000 --> 00:22:56,720 Speaker 1: is not there. I think let's go to Josh in 387 00:22:56,800 --> 00:23:02,320 Speaker 1: North Carolina. Josh, what do you got for us? This 388 00:23:02,400 --> 00:23:05,080 Speaker 1: is a fun game. Let's try Bob in Indianapolis. Let's 389 00:23:05,080 --> 00:23:07,040 Speaker 1: see if we can get one. Let's hit one on 390 00:23:07,080 --> 00:23:12,080 Speaker 1: the names. Hey guys, Um, thanks for having me on. UM. 391 00:23:13,080 --> 00:23:15,840 Speaker 1: I just want to address your comments about you know, 392 00:23:15,920 --> 00:23:19,399 Speaker 1: talking about the twenty twenty election and how you know 393 00:23:19,440 --> 00:23:23,520 Speaker 1: candidates lose. Uh. First of all, you seem to be 394 00:23:23,560 --> 00:23:28,480 Speaker 1: promoting this idea, you know, that definition of insanity. We 395 00:23:28,560 --> 00:23:30,320 Speaker 1: just keep doing the same thing over and over again 396 00:23:30,320 --> 00:23:33,960 Speaker 1: and expecting a different result. If if these elections do 397 00:23:34,160 --> 00:23:40,960 Speaker 1: not get fixed, We're okay. What happened? Bob? I mean, 398 00:23:41,080 --> 00:23:43,240 Speaker 1: I'm just like, what what do you think happened in 399 00:23:43,280 --> 00:23:47,280 Speaker 1: twenty twenty? That? Uh, that means that that we have 400 00:23:47,359 --> 00:23:50,280 Speaker 1: to change what happens. Let's jump ahead to what you 401 00:23:50,320 --> 00:23:55,399 Speaker 1: said about carry Lake and hey, if the refs were crooked, uh, 402 00:23:55,480 --> 00:23:57,959 Speaker 1: you know, hey, you just gotta focus on winning the 403 00:23:58,000 --> 00:24:00,800 Speaker 1: next game. You know that only makes sense if the 404 00:24:00,840 --> 00:24:06,080 Speaker 1: crooked refs aren't, you know, there for the next game. Well, 405 00:24:06,080 --> 00:24:07,560 Speaker 1: hold on, let me talk to you about Look, I 406 00:24:07,560 --> 00:24:09,680 Speaker 1: think they Let me just explain Carry Lake. I think 407 00:24:09,720 --> 00:24:13,680 Speaker 1: Carry Lake is the best candidate that ran for Republicans 408 00:24:14,119 --> 00:24:17,120 Speaker 1: as a non incumbent in twenty twenty two. But if 409 00:24:17,160 --> 00:24:21,600 Speaker 1: you look at the down ballot data in Arizona, everyone 410 00:24:21,760 --> 00:24:25,320 Speaker 1: was winning down ballot the people who focused on twenty 411 00:24:25,400 --> 00:24:28,240 Speaker 1: twenty and she did focus on twenty twenty a lot 412 00:24:28,840 --> 00:24:32,000 Speaker 1: Republican voters. Let me repeat this because this is important. 413 00:24:32,520 --> 00:24:38,280 Speaker 1: Republican voters flip their ticket. What's frustrating to me about 414 00:24:38,280 --> 00:24:41,440 Speaker 1: the twenty twenty two elections is if you go look 415 00:24:41,480 --> 00:24:47,040 Speaker 1: at the data in Nevada, in Arizona, in Georgia, in Pennsylvania, 416 00:24:47,200 --> 00:24:50,920 Speaker 1: in all of the races that Republicans lost which were competitive, 417 00:24:51,720 --> 00:24:56,920 Speaker 1: we didn't lose because of Democrats. We lost because Republican 418 00:24:57,080 --> 00:25:03,240 Speaker 1: voters split their tickets over overwhelmingly, far more outen than Democrats. 419 00:25:03,280 --> 00:25:05,359 Speaker 1: Did and win. Buck, you look at the data on 420 00:25:05,440 --> 00:25:09,240 Speaker 1: why they did that. A lot of Republican voters are 421 00:25:09,320 --> 00:25:12,880 Speaker 1: upset about the focus on twenty twenty and said I'm 422 00:25:12,920 --> 00:25:15,680 Speaker 1: going to split my ticket and vote I think otherwise. Okay, 423 00:25:15,680 --> 00:25:18,919 Speaker 1: and this is really important. We're sitting here saying you 424 00:25:19,040 --> 00:25:21,440 Speaker 1: have to deal with Manlin ballots, you have to deal 425 00:25:21,520 --> 00:25:28,040 Speaker 1: with universal registration, you have to deal with being earlier, 426 00:25:28,359 --> 00:25:32,199 Speaker 1: yea earlier, right right, you have to actually do these things. 427 00:25:32,760 --> 00:25:35,320 Speaker 1: But what we're talking about with the focus on twenty twenty, 428 00:25:35,359 --> 00:25:38,399 Speaker 1: it's not don't learn from twenty twenty. What twenty twenty 429 00:25:38,400 --> 00:25:41,719 Speaker 1: two showed us is saying we won and then not 430 00:25:41,800 --> 00:25:44,240 Speaker 1: doing anything to make sure you win the next time 431 00:25:44,440 --> 00:25:48,240 Speaker 1: is a recipe for losing. Meaning the focus on we 432 00:25:48,400 --> 00:25:51,240 Speaker 1: actually won, so we don't have to do anything differently, 433 00:25:51,440 --> 00:25:53,840 Speaker 1: and maybe there'll be some plan that will actually deliver 434 00:25:53,960 --> 00:25:55,840 Speaker 1: us the election that has already been called, that we 435 00:25:55,880 --> 00:25:59,920 Speaker 1: already did not win. That is counterproductive focusing on what 436 00:26:00,160 --> 00:26:03,359 Speaker 1: could be done differently or what needs to be changed, 437 00:26:03,400 --> 00:26:05,520 Speaker 1: whether it's a function of law, something you have to 438 00:26:05,520 --> 00:26:06,840 Speaker 1: do in the court, something you have to do the 439 00:26:06,840 --> 00:26:10,680 Speaker 1: state legislature, that has to be done in advance of 440 00:26:10,720 --> 00:26:13,359 Speaker 1: the next election based on what happened in the election. 441 00:26:13,560 --> 00:26:16,240 Speaker 1: So our point is not I mean, I'll speak for myself. 442 00:26:16,240 --> 00:26:18,760 Speaker 1: My point is not that you ignr No. The point 443 00:26:18,840 --> 00:26:20,560 Speaker 1: is you have to look at what can be done 444 00:26:20,720 --> 00:26:24,040 Speaker 1: as a result of and not say, well, because the 445 00:26:24,080 --> 00:26:26,520 Speaker 1: attitude that we won, so we'll just do the same 446 00:26:26,560 --> 00:26:28,879 Speaker 1: thing and we'll win the next time. That was what 447 00:26:28,920 --> 00:26:31,520 Speaker 1: people thought in twenty twenty two and it was wrong. Yes, 448 00:26:31,840 --> 00:26:34,159 Speaker 1: And also I want to respond to this justin and 449 00:26:34,280 --> 00:26:39,560 Speaker 1: round Rock, Texas. What's your question? Justin? Hey, So my 450 00:26:39,680 --> 00:26:44,439 Speaker 1: question is basically, so technically Trump had his tweets, I 451 00:26:44,440 --> 00:26:47,159 Speaker 1: don't necessarily agree with them, but one of my questions is, 452 00:26:47,760 --> 00:26:50,000 Speaker 1: let's just say a court would hear it, which we 453 00:26:50,080 --> 00:26:54,720 Speaker 1: pretty much know wouldn't. Is there any recourse to being 454 00:26:54,760 --> 00:26:57,440 Speaker 1: able to turn over a bunch of seats that were 455 00:26:57,560 --> 00:27:01,720 Speaker 1: quote unquote stolen. No, there is, Thanks for the call. 456 00:27:02,160 --> 00:27:05,680 Speaker 1: Anyone who is telling you that the courts are going 457 00:27:05,760 --> 00:27:09,320 Speaker 1: to change any of the outcomes in any of the 458 00:27:09,400 --> 00:27:15,120 Speaker 1: elections is, in my opinion, totally selling you a bill 459 00:27:15,119 --> 00:27:21,120 Speaker 1: of goods. Legally, there is not going to be anything 460 00:27:21,200 --> 00:27:24,320 Speaker 1: that occurs like Donald Trump is not miraculously going to 461 00:27:24,440 --> 00:27:27,240 Speaker 1: end up being president and Joe Biden is not going 462 00:27:27,280 --> 00:27:30,119 Speaker 1: to be removed. Anyone who is telling you that is 463 00:27:30,240 --> 00:27:33,960 Speaker 1: lying to you. That's the truth. Now, you can wish 464 00:27:34,000 --> 00:27:38,000 Speaker 1: that it would happen. You can stay, as Buck was saying, 465 00:27:38,320 --> 00:27:42,120 Speaker 1: learn from twenty twenty and twenty twenty two, and try 466 00:27:42,160 --> 00:27:44,800 Speaker 1: to kick ass as a result in twenty twenty four. 467 00:27:45,480 --> 00:27:50,400 Speaker 1: But the courts are not going to get involved. And suddenly, 468 00:27:50,480 --> 00:27:52,560 Speaker 1: first of all, they don't have the authority to do this, 469 00:27:52,800 --> 00:27:54,639 Speaker 1: and also crazy, how do we all of a sudden 470 00:27:54,720 --> 00:28:00,439 Speaker 1: think that the courts are necessarily even fair hand ended 471 00:28:00,560 --> 00:28:03,119 Speaker 1: and friends of the constitution, folks, I mean, you know, 472 00:28:03,320 --> 00:28:06,360 Speaker 1: putting a lot of faith in Remember the Ninth Circuit, 473 00:28:06,440 --> 00:28:09,600 Speaker 1: Remember all the universal injunctions against Donald Trump when he 474 00:28:09,640 --> 00:28:12,439 Speaker 1: was president. One federal judge of the Ninth Circuit would say, no, 475 00:28:12,520 --> 00:28:15,520 Speaker 1: Trump can't do that policy. I mean, if you're arresting 476 00:28:15,600 --> 00:28:19,080 Speaker 1: at all on the courts, you know you're you're hoping 477 00:28:19,119 --> 00:28:21,960 Speaker 1: again really lucky. Well, just think about it this way. 478 00:28:22,119 --> 00:28:27,080 Speaker 1: In twenty eighteen, there were looney been Democrats who were 479 00:28:27,119 --> 00:28:30,240 Speaker 1: saying Trump's gonna get arrested in the Oval office. He's 480 00:28:30,280 --> 00:28:35,119 Speaker 1: gonna get marched out. He's a Russian collusion, you know, 481 00:28:35,359 --> 00:28:38,880 Speaker 1: involved in all this stuff. They were crazy, right. If 482 00:28:38,920 --> 00:28:42,800 Speaker 1: your presumption or anyone that is telling you this, your 483 00:28:42,920 --> 00:28:46,000 Speaker 1: presumption is that suddenly Joe Biden is going to get 484 00:28:46,600 --> 00:28:48,520 Speaker 1: taken out of the Oval office and they're just gonna 485 00:28:48,560 --> 00:28:52,800 Speaker 1: miraculously put Trump in, that is crazy talk. And you 486 00:28:52,840 --> 00:28:57,120 Speaker 1: shouldn't be embracing crazy talk now. You should be I 487 00:28:57,160 --> 00:29:00,560 Speaker 1: think looking at the data of twenty two and saying, 488 00:29:01,040 --> 00:29:03,920 Speaker 1: what can we learn from twenty two? To bucks point, 489 00:29:04,040 --> 00:29:08,720 Speaker 1: Democrats have gotten way better in Pennsylvania at harvesting ballots, 490 00:29:08,760 --> 00:29:12,680 Speaker 1: at getting absentee ballots, at mail ballots, at voting long 491 00:29:12,760 --> 00:29:16,800 Speaker 1: before election day, and Republicans are going to have to 492 00:29:17,080 --> 00:29:20,560 Speaker 1: up the game by twenty four to compete in many 493 00:29:20,640 --> 00:29:23,600 Speaker 1: of these states. And look, we'll have a long process 494 00:29:23,680 --> 00:29:25,240 Speaker 1: by which we're going to have a lot of people 495 00:29:25,320 --> 00:29:27,280 Speaker 1: running to see who the nominees are going to be 496 00:29:27,360 --> 00:29:30,920 Speaker 1: in twenty four. But my advice would be, if you 497 00:29:31,000 --> 00:29:36,160 Speaker 1: want to win, the data from twenty two overwhelmingly reflects 498 00:29:36,200 --> 00:29:39,120 Speaker 1: that if you are focused on twenty two, you get 499 00:29:39,120 --> 00:29:42,040 Speaker 1: your ass kicked. In competitive elections, you just do do 500 00:29:42,080 --> 00:29:44,440 Speaker 1: you want to win? I want to sit around and 501 00:29:44,480 --> 00:29:49,000 Speaker 1: make old arguments as a general as a general rule, 502 00:29:50,560 --> 00:29:52,720 Speaker 1: why would we not want to have a discussion as 503 00:29:52,720 --> 00:29:55,880 Speaker 1: a party and as a conservative movement about let's again, 504 00:29:55,920 --> 00:29:57,800 Speaker 1: let's just say Trump is the nominee, about the most 505 00:29:57,840 --> 00:30:01,320 Speaker 1: effective Trump campaign possible. And I think maybe part of 506 00:30:01,360 --> 00:30:03,640 Speaker 1: the meaning how do we help him win, how do 507 00:30:03,680 --> 00:30:06,200 Speaker 1: we help him get back in the Oval office? How 508 00:30:06,200 --> 00:30:08,680 Speaker 1: do we make it so that he's able to finish 509 00:30:08,720 --> 00:30:11,320 Speaker 1: the job of the four years? Why would we not 510 00:30:11,400 --> 00:30:13,560 Speaker 1: have that conversation? And I think a little bit of 511 00:30:13,600 --> 00:30:18,360 Speaker 1: it comes from, well, because he actually won in twenty twenty, 512 00:30:18,400 --> 00:30:20,920 Speaker 1: there's no need for that conversation. And I just don't 513 00:30:20,920 --> 00:30:22,800 Speaker 1: think that's the right way to approach it. I don't 514 00:30:22,800 --> 00:30:24,280 Speaker 1: know what else to say. I just I think that's 515 00:30:24,600 --> 00:30:26,720 Speaker 1: I think that's not helpful to the country. I think 516 00:30:26,720 --> 00:30:29,560 Speaker 1: it's not helpful to Donald Trump. I think you know 517 00:30:29,880 --> 00:30:32,600 Speaker 1: you want, Claire. You come from the sports world. If 518 00:30:32,600 --> 00:30:35,200 Speaker 1: your team loses the Super Bowl, when they're up again 519 00:30:35,200 --> 00:30:37,120 Speaker 1: to the next super Bowl, you probably want to talk 520 00:30:37,120 --> 00:30:38,920 Speaker 1: about what could have gone differently in the super Bowl 521 00:30:39,000 --> 00:30:40,680 Speaker 1: so that they win the next super Bowl. Yeah, because 522 00:30:40,680 --> 00:30:44,360 Speaker 1: you're right, if you spend all of your time talking 523 00:30:44,360 --> 00:30:46,560 Speaker 1: about a call that was made that cost you the 524 00:30:46,600 --> 00:30:48,960 Speaker 1: previous game. Then you're gonna get your ass kicked in 525 00:30:49,000 --> 00:30:54,200 Speaker 1: the next game. And so this obsession with past redress 526 00:30:55,160 --> 00:30:58,520 Speaker 1: is to me a way to ensure that you keep losing. 527 00:30:58,680 --> 00:31:02,160 Speaker 1: And look twenty two. I think that's the number one 528 00:31:02,240 --> 00:31:07,280 Speaker 1: takeaway in competitive states, the more candidate Republican candidates who 529 00:31:07,320 --> 00:31:13,200 Speaker 1: focused on the future, Rhonda Santis, Brian Kemp, Greg Abbott dominated. Look, 530 00:31:14,000 --> 00:31:15,800 Speaker 1: we're about to have We're about to have a Trump 531 00:31:15,840 --> 00:31:19,080 Speaker 1: backed Senate candidate in Georgia in a runoff in a 532 00:31:19,160 --> 00:31:21,720 Speaker 1: state to Kemp won by eight points. We're about to 533 00:31:21,720 --> 00:31:25,200 Speaker 1: see how that goes down. And I want Herschel to win, 534 00:31:25,240 --> 00:31:27,080 Speaker 1: and all of you need to get out there and vote. 535 00:31:27,120 --> 00:31:31,800 Speaker 1: But so far, seven out of the eight statewide Republicans 536 00:31:31,840 --> 00:31:35,040 Speaker 1: have won. Herschel is the eighth. I hope that tomorrow 537 00:31:35,080 --> 00:31:37,000 Speaker 1: he's gonna win. I was supposed to be speaking at 538 00:31:37,000 --> 00:31:39,880 Speaker 1: his rally tonight. I can't get down there because of 539 00:31:40,280 --> 00:31:43,760 Speaker 1: air travel conditions. The uh the I don't know, the 540 00:31:43,800 --> 00:31:45,800 Speaker 1: elevations too low to allow you to take off in 541 00:31:45,920 --> 00:31:48,960 Speaker 1: land in Atlanta and plains them tell about but think 542 00:31:48,960 --> 00:31:51,360 Speaker 1: about it. Look at the data. Don't bury your hand 543 00:31:51,360 --> 00:31:54,800 Speaker 1: in the sist I'm so hopeful for Herschel. I'm hopeful. Yes, 544 00:31:54,960 --> 00:31:57,200 Speaker 1: don't bury your head in the sand. Herschel. If if 545 00:31:57,240 --> 00:32:00,160 Speaker 1: Republicans show up, Herschel's gonna win. Republicans have to show 546 00:32:00,200 --> 00:32:02,480 Speaker 1: up tomorrow. He's gonna win. They don't, he's gonna lose. 547 00:32:02,520 --> 00:32:05,080 Speaker 1: I mean, that's the reality. Look, we want to make 548 00:32:05,120 --> 00:32:08,840 Speaker 1: sure that you have an incredible offer. Right now and 549 00:32:08,960 --> 00:32:13,120 Speaker 1: right now, My Pillow has got a phenomenal offer for 550 00:32:13,200 --> 00:32:17,680 Speaker 1: you from the Great Area of Giza. These are the 551 00:32:17,720 --> 00:32:22,240 Speaker 1: best sheets you can buy. You can get under thirty 552 00:32:22,280 --> 00:32:26,120 Speaker 1: dollars a set, softest cotton you've ever experienced. I sleep 553 00:32:26,160 --> 00:32:28,560 Speaker 1: on these things and they are amazing. 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Go to my pillow 560 00:32:47,960 --> 00:32:51,560 Speaker 1: dot com click on the Radio Listeners Specials to check 561 00:32:51,600 --> 00:32:54,959 Speaker 1: out the flash sail on the Giza dream sheets go today. 562 00:32:57,040 --> 00:33:01,959 Speaker 1: Did you see this crazy video Clay of the I 563 00:33:01,960 --> 00:33:04,320 Speaker 1: mean it's it's all on the you know, you have 564 00:33:04,440 --> 00:33:06,760 Speaker 1: these front door cams now so you get all this footage. 565 00:33:07,280 --> 00:33:09,240 Speaker 1: So I mean this was it was a you know, 566 00:33:09,720 --> 00:33:12,120 Speaker 1: serious risk to this. This little girl, five year old 567 00:33:12,120 --> 00:33:16,560 Speaker 1: girl was attacked by a raccoon in Ashford, Connecticut over 568 00:33:16,600 --> 00:33:19,520 Speaker 1: the weekend. I'm not sure if they've been able to 569 00:33:19,560 --> 00:33:25,080 Speaker 1: test yet if the raccoon had rabies, but the mom 570 00:33:25,320 --> 00:33:30,360 Speaker 1: on video goes full mom mode, just grabs this raccoon 571 00:33:31,160 --> 00:33:34,440 Speaker 1: just like one, hands it, make sure that her her 572 00:33:34,520 --> 00:33:36,880 Speaker 1: daughter can get inside the house safe, and then she 573 00:33:36,960 --> 00:33:40,280 Speaker 1: kind of winds up and has to toss it across 574 00:33:40,320 --> 00:33:43,440 Speaker 1: the yard. You know, sometimes I think raccoons or can 575 00:33:43,480 --> 00:33:48,840 Speaker 1: be kind of cute but trash pandas to some. But um, 576 00:33:49,840 --> 00:33:53,320 Speaker 1: when they're rabbit, it's they're scary. They get real real aggressive. 577 00:33:54,800 --> 00:33:57,640 Speaker 1: Have you ever been in a situation where you've seen 578 00:33:57,760 --> 00:34:01,360 Speaker 1: an animal and suspected that it was rabbit. I so 579 00:34:01,760 --> 00:34:05,120 Speaker 1: I began my radio career at the Blaze, and my 580 00:34:05,160 --> 00:34:08,040 Speaker 1: friend Dom Feodor, who may be listening, invited me to 581 00:34:08,040 --> 00:34:09,880 Speaker 1: to his cabin in the wood stay with him and 582 00:34:09,920 --> 00:34:12,480 Speaker 1: his family for a week and many years ago, and 583 00:34:12,520 --> 00:34:14,680 Speaker 1: I and I swear, I pull up to the front door. 584 00:34:14,880 --> 00:34:17,359 Speaker 1: This is in New York. Oh no, this is up 585 00:34:17,360 --> 00:34:20,120 Speaker 1: in Michigan. This is up a rural Michigan, up in 586 00:34:20,160 --> 00:34:22,319 Speaker 1: the woods. And I pull up to his to his 587 00:34:22,400 --> 00:34:25,200 Speaker 1: front door, and you know, I've got like the rolling bag. 588 00:34:25,280 --> 00:34:26,919 Speaker 1: I mean, I really look like this, like the city kid, 589 00:34:26,960 --> 00:34:28,719 Speaker 1: you know, like we're it's a cabin, my man, it's 590 00:34:28,719 --> 00:34:30,839 Speaker 1: on a lake. It's a cabin. And I go up 591 00:34:31,200 --> 00:34:33,319 Speaker 1: and he's got a great I love dogs, and he's 592 00:34:33,360 --> 00:34:36,160 Speaker 1: got a labrador that comes out to greet me, a 593 00:34:36,280 --> 00:34:39,320 Speaker 1: black lab great dog. And I'm I'm sort of getting 594 00:34:39,360 --> 00:34:40,600 Speaker 1: you know, I'm like, oh, look at the cute dog. 595 00:34:40,800 --> 00:34:44,000 Speaker 1: And then the dog of a start and starts really growling. 596 00:34:44,160 --> 00:34:46,560 Speaker 1: I mean, like something is not good. It's broad daylight 597 00:34:46,560 --> 00:34:49,120 Speaker 1: and it's probably around lunch time, and out from a 598 00:34:49,120 --> 00:34:52,959 Speaker 1: little woodpile by the front door, this raccoon just comes 599 00:34:53,040 --> 00:34:54,920 Speaker 1: flying and I had never seen it, got up on 600 00:34:55,040 --> 00:34:57,279 Speaker 1: its back legs and had it was making a little 601 00:34:57,760 --> 00:35:00,400 Speaker 1: like a kind of like a crazy hits noise, and 602 00:35:00,440 --> 00:35:02,680 Speaker 1: it had its little paws and it was kind of 603 00:35:02,719 --> 00:35:05,920 Speaker 1: making scratching motions with the claws, and it's showing its 604 00:35:05,920 --> 00:35:08,359 Speaker 1: little teeth. It was the meanest little raccoon I've ever seen. 605 00:35:08,400 --> 00:35:11,520 Speaker 1: And Dom runs in, of course, by the front door. 606 00:35:11,520 --> 00:35:14,440 Speaker 1: He had a thirty eight right there. He grabs it. 607 00:35:14,640 --> 00:35:16,880 Speaker 1: He's like, get out of the way. Bam bam. He 608 00:35:17,000 --> 00:35:20,160 Speaker 1: lights up this raccoon right there because he was afraid 609 00:35:20,200 --> 00:35:21,320 Speaker 1: he was gonna get you know, I was gonna go 610 00:35:21,440 --> 00:35:23,160 Speaker 1: right at his dog and the raccoon. We're sort of 611 00:35:23,200 --> 00:35:25,280 Speaker 1: squaring off. Did you think it was a rabbit raccoon 612 00:35:25,360 --> 00:35:28,000 Speaker 1: or did you? Oh? Yeah, I mean it was daylight 613 00:35:28,360 --> 00:35:30,319 Speaker 1: and it was right next to the house, so I 614 00:35:30,320 --> 00:35:33,040 Speaker 1: we did think it was very possible. But then again 615 00:35:33,080 --> 00:35:35,319 Speaker 1: it might have just been disturbed in its uh, in 616 00:35:35,320 --> 00:35:37,279 Speaker 1: its little woodpile area, but it was right next to 617 00:35:37,280 --> 00:35:39,640 Speaker 1: the house. But man, raccoons, when they go bad, they 618 00:35:39,719 --> 00:35:42,680 Speaker 1: really mean. Yeah, we had I think I've told this story. 619 00:35:42,719 --> 00:35:46,080 Speaker 1: We had a Have you ever heard of tree rats? No, 620 00:35:47,239 --> 00:35:51,280 Speaker 1: so in uh and now I'm not talking about squirrels, 621 00:35:51,360 --> 00:35:54,040 Speaker 1: And we lived in the Caribbean, and so they have 622 00:35:54,480 --> 00:35:59,400 Speaker 1: uh tree rats like these are pretty decent sized rats 623 00:35:59,440 --> 00:36:02,560 Speaker 1: that live in the trees in the Caribbean and they 624 00:36:02,600 --> 00:36:06,839 Speaker 1: will gnaw through the like screen doors or whatever else 625 00:36:06,880 --> 00:36:11,440 Speaker 1: and come in. And this is these things are massive, right, 626 00:36:11,480 --> 00:36:13,680 Speaker 1: like some of these tree rats in the carib some 627 00:36:13,800 --> 00:36:17,799 Speaker 1: unusual size. Yes, like like even for a fat rat 628 00:36:17,840 --> 00:36:20,959 Speaker 1: in New York City, this would be like a massive rat. 629 00:36:21,400 --> 00:36:26,120 Speaker 1: And I think the most scared my wife has ever 630 00:36:26,200 --> 00:36:27,799 Speaker 1: been was when we came back and one of these 631 00:36:27,840 --> 00:36:31,680 Speaker 1: tree rats was just sitting and like immediately turned toward us, 632 00:36:31,680 --> 00:36:33,880 Speaker 1: like you know, in that way where it's like ready 633 00:36:33,920 --> 00:36:37,440 Speaker 1: to attack you. And she went sprinting into the bedroom, 634 00:36:37,480 --> 00:36:39,160 Speaker 1: shut the door and said, I had to get it out. 635 00:36:39,440 --> 00:36:41,279 Speaker 1: And I don't know that I've been more terrified than 636 00:36:41,320 --> 00:36:44,000 Speaker 1: trying to fight this tree rat inside of our Virgin 637 00:36:44,080 --> 00:36:47,120 Speaker 1: Islands place. I eventually managed to get it out, but 638 00:36:47,960 --> 00:36:48,840 Speaker 1: I think it was rabbing