1 00:00:00,080 --> 00:00:02,920 Speaker 1: Hi, This is due to the virus. I'm recording from home, 2 00:00:03,320 --> 00:00:09,680 Speaker 1: so you may notice a difference in audio quality. Well. 3 00:00:09,720 --> 00:00:12,920 Speaker 1: In this episode of news World, New York Governor Andrew 4 00:00:12,960 --> 00:00:16,680 Speaker 1: Cuomo completely mishandled the early days of the pandemic and 5 00:00:16,800 --> 00:00:20,960 Speaker 1: the virus entering our country. He made misguided policy decisions 6 00:00:21,000 --> 00:00:25,239 Speaker 1: that killed thousands, including many seniors. I've been talking about 7 00:00:25,239 --> 00:00:28,360 Speaker 1: how his actions have impacted thousands of New York citizens 8 00:00:28,600 --> 00:00:32,440 Speaker 1: for months. Just this week, the New York Times published quote, 9 00:00:32,880 --> 00:00:36,960 Speaker 1: nine top New York health officials have quit as Cuomo's 10 00:00:37,040 --> 00:00:40,839 Speaker 1: scorns expertise close for it. Governor Cuomos was handling the 11 00:00:40,840 --> 00:00:45,120 Speaker 1: pandemic has been further called into question after State Attorney 12 00:00:45,120 --> 00:00:49,880 Speaker 1: General Letitia James said his administration had undercounted the number 13 00:00:49,920 --> 00:00:52,879 Speaker 1: of COVID nineteen deaths of nursing home residents by not 14 00:00:53,080 --> 00:00:56,840 Speaker 1: publicly disclosing deaths of those residents that occurred in hospitals. 15 00:00:57,440 --> 00:01:00,520 Speaker 1: In fact, New York is one of the hardest states 16 00:01:00,520 --> 00:01:04,440 Speaker 1: in the nation, with over one point four two million cases. 17 00:01:04,800 --> 00:01:08,679 Speaker 1: It's a million, four hundred and twenty thousand cases and 18 00:01:08,880 --> 00:01:12,800 Speaker 1: forty three thousand, one hundred and seventy eight days. My 19 00:01:12,880 --> 00:01:17,520 Speaker 1: guest has a new book out about Cuomo and Mayor Deblasio. 20 00:01:18,160 --> 00:01:31,959 Speaker 1: Matt Palumbo. Matt Palumbo, thank you for joining me, interrupted 21 00:01:32,000 --> 00:01:34,280 Speaker 1: me on. It's the great pleasure. Now your new book. 22 00:01:34,440 --> 00:01:37,360 Speaker 1: I must say I like the title Dumb and Dumber. 23 00:01:37,920 --> 00:01:41,880 Speaker 1: How Cuomo and de Blasio ruined New York. You wrote quote, 24 00:01:41,959 --> 00:01:44,640 Speaker 1: if Young yorsh for its own country, it would have 25 00:01:44,720 --> 00:01:47,480 Speaker 1: more coronavirus desk per capita than any other in the 26 00:01:47,600 --> 00:01:51,840 Speaker 1: entire world. Why did this happen? It was really a 27 00:01:51,840 --> 00:01:54,000 Speaker 1: comedy of errors. From the start. There was just a 28 00:01:54,080 --> 00:01:56,800 Speaker 1: huge liberal narrative that Trump was downplaying the risks of 29 00:01:56,840 --> 00:01:59,360 Speaker 1: the virus, and it's certainly true that he wasn't publicly 30 00:01:59,400 --> 00:02:02,200 Speaker 1: alarmist it. But the only people down playing the pandemic 31 00:02:02,280 --> 00:02:05,080 Speaker 1: or future pandemic were people like the Blaiso and Cuomo. 32 00:02:05,280 --> 00:02:08,519 Speaker 1: Trump early on band travel from China, and that was 33 00:02:08,560 --> 00:02:11,640 Speaker 1: all happening as Democrats were fixated on impeachment. We're not 34 00:02:11,680 --> 00:02:14,320 Speaker 1: even paying attention to the virus early on, and people 35 00:02:14,320 --> 00:02:16,480 Speaker 1: like the Blasi and Quoma were really just denying that 36 00:02:16,520 --> 00:02:18,680 Speaker 1: he was going to return into something was telling people, 37 00:02:18,680 --> 00:02:20,840 Speaker 1: you know, keep going on with life as usual. And 38 00:02:20,960 --> 00:02:22,840 Speaker 1: it got to the point where the sort of inject 39 00:02:22,919 --> 00:02:25,840 Speaker 1: social justice into it, where health officials were saying, you know, 40 00:02:25,880 --> 00:02:27,919 Speaker 1: the virus could be bad, but it's not going to 41 00:02:28,000 --> 00:02:30,640 Speaker 1: be as bad as anti Asian racism might emerge, So 42 00:02:30,680 --> 00:02:32,960 Speaker 1: go to Chinatown and spend money the air and congregrate. 43 00:02:33,000 --> 00:02:34,840 Speaker 1: And they were just kind of encouraging all of these 44 00:02:34,840 --> 00:02:36,520 Speaker 1: things you would not want to do when a virus 45 00:02:36,600 --> 00:02:39,400 Speaker 1: is about to hit your city. And then in New 46 00:02:39,440 --> 00:02:41,480 Speaker 1: York as a whole, and this is really where things 47 00:02:41,480 --> 00:02:45,320 Speaker 1: went off the rails. Cuomo's nursing home scandal is primarily 48 00:02:45,360 --> 00:02:47,880 Speaker 1: responsible for why the state's death toll is what it 49 00:02:48,040 --> 00:02:50,960 Speaker 1: was now. There are all these concerns early on, based 50 00:02:50,960 --> 00:02:53,880 Speaker 1: on various models on what hospital utilization would be like, 51 00:02:54,240 --> 00:02:56,440 Speaker 1: and there's a lot of concerns that hospitals would become 52 00:02:56,440 --> 00:02:59,800 Speaker 1: overwhelmed from the virus. So in response to that, Cuomo 53 00:03:00,040 --> 00:03:02,480 Speaker 1: signed into order it's called the March twenty fifth of order, 54 00:03:02,680 --> 00:03:05,280 Speaker 1: and that sent people who had been previously tested positive 55 00:03:05,320 --> 00:03:07,400 Speaker 1: for coronavirus but were at least a few days into 56 00:03:07,400 --> 00:03:10,240 Speaker 1: their symptoms or the hospitalization, they would be sent to 57 00:03:10,320 --> 00:03:13,560 Speaker 1: nursing homes. Now and this is completely insane. New York 58 00:03:13,680 --> 00:03:16,000 Speaker 1: was the only state in the nation that prohibited testing 59 00:03:16,000 --> 00:03:18,080 Speaker 1: these people when they went to nursing homes, so we 60 00:03:18,160 --> 00:03:20,239 Speaker 1: had no way of knowing if they were so infectious. 61 00:03:20,280 --> 00:03:22,519 Speaker 1: And well we do know now that obviously they were. 62 00:03:22,880 --> 00:03:24,959 Speaker 1: Within just a few months, about two months, there would 63 00:03:25,000 --> 00:03:27,720 Speaker 1: be six thousand people in nursing homes were reported dead. 64 00:03:28,200 --> 00:03:30,400 Speaker 1: And that was just reported according to what they were 65 00:03:30,400 --> 00:03:32,359 Speaker 1: telling us. I argued in the book was close to 66 00:03:32,360 --> 00:03:35,600 Speaker 1: the twelve thousand. And the reason why is if you 67 00:03:35,800 --> 00:03:38,880 Speaker 1: contracted coronavirus in a nursing home and then were transported 68 00:03:38,920 --> 00:03:41,520 Speaker 1: back to a hospital as an elderly person, your death 69 00:03:41,560 --> 00:03:43,560 Speaker 1: was a hospital death, not a nursing home death. And 70 00:03:43,600 --> 00:03:46,280 Speaker 1: then now we have the new AG report basically confirming 71 00:03:46,320 --> 00:03:49,400 Speaker 1: that yes, they were understated to that exact extent, and 72 00:03:49,640 --> 00:03:52,360 Speaker 1: Cooma's defenses have just could have been laughable since then, 73 00:03:52,440 --> 00:03:55,000 Speaker 1: So he had the New York Health Department commissioned their 74 00:03:55,040 --> 00:03:57,480 Speaker 1: own study exonerating themselves, and they were trying to claim, 75 00:03:57,760 --> 00:03:59,680 Speaker 1: now it wasn't our policy, was they got it from 76 00:03:59,680 --> 00:04:02,080 Speaker 1: the nur So I started speaking to nurses who worked 77 00:04:02,080 --> 00:04:04,040 Speaker 1: in these nursing homes and they said, no, we were 78 00:04:04,160 --> 00:04:06,280 Speaker 1: tested going in so we couldn't have spread it. We 79 00:04:06,360 --> 00:04:09,200 Speaker 1: obviously got it from the coronavirus patients they were sending 80 00:04:09,240 --> 00:04:12,040 Speaker 1: us of them. It spread from there. Also interesting that 81 00:04:12,160 --> 00:04:16,000 Speaker 1: study was sponsored by mckinseley, which Cuomo himself relied on 82 00:04:16,080 --> 00:04:19,680 Speaker 1: for those extrapolations on how overwhelmed hospitals would get. So 83 00:04:19,839 --> 00:04:21,920 Speaker 1: there's sort of a conflict of interest within the conflict 84 00:04:21,960 --> 00:04:24,720 Speaker 1: of interest, and now quomos pivoted even from there and 85 00:04:24,800 --> 00:04:26,640 Speaker 1: to just kind of denying that there whatever was in 86 00:04:26,760 --> 00:04:29,160 Speaker 1: nursing home scandal and saying, you know, we didn't need 87 00:04:29,160 --> 00:04:31,880 Speaker 1: this space. We have the tent hospitals and the USNS 88 00:04:31,920 --> 00:04:34,000 Speaker 1: comfort that Trump sent, so why would we have even 89 00:04:34,040 --> 00:04:36,279 Speaker 1: needed that policy. So we've kind of gone through everything 90 00:04:36,360 --> 00:04:39,600 Speaker 1: from this disaster to Cuomo trying to get his own 91 00:04:39,640 --> 00:04:41,960 Speaker 1: department to cover for him, to just outright denying that 92 00:04:42,040 --> 00:04:44,159 Speaker 1: this happened, and then for the most part, the media 93 00:04:44,279 --> 00:04:45,800 Speaker 1: does seem to have let him get away from it, 94 00:04:45,880 --> 00:04:49,120 Speaker 1: though hopefully this AG report changes that. So I'm curious 95 00:04:49,440 --> 00:04:53,320 Speaker 1: what was the rationale for not testing? Well, that's the 96 00:04:53,360 --> 00:04:55,400 Speaker 1: thing I can't figure out. It makes no sense at all. 97 00:04:55,520 --> 00:04:57,960 Speaker 1: And you know, Cuomo himself tried to blame Trump for 98 00:04:58,040 --> 00:05:00,000 Speaker 1: the nursing home scandal and said, well, it was actually 99 00:05:00,040 --> 00:05:02,360 Speaker 1: CDC guidance that I got of our policy to free 100 00:05:02,400 --> 00:05:05,760 Speaker 1: up space, but the CDC explicitly said you'd have to 101 00:05:05,760 --> 00:05:08,000 Speaker 1: test these people. It's you know, one of those questions 102 00:05:08,040 --> 00:05:09,440 Speaker 1: I can't answer is I don't think there really is 103 00:05:09,440 --> 00:05:12,040 Speaker 1: a rational answer. It was just, you know, very sloppily 104 00:05:12,120 --> 00:05:15,960 Speaker 1: designed this plan. Well. I did a podcast a couple 105 00:05:16,000 --> 00:05:19,080 Speaker 1: of months ago with Betsy McCoy, the former Lieutenant governor 106 00:05:19,080 --> 00:05:22,000 Speaker 1: of New York. She thought all this was deeply involved 107 00:05:22,320 --> 00:05:26,240 Speaker 1: in Cuomo's relationship with the New York Hospital Association and 108 00:05:26,400 --> 00:05:30,240 Speaker 1: their top lobbyist, and that the hospitals really did not 109 00:05:30,320 --> 00:05:33,880 Speaker 1: want people with COVID in the hospitals and dramatically preferred 110 00:05:33,920 --> 00:05:36,039 Speaker 1: dumpy all on nurse holds. I don't know if that's 111 00:05:36,040 --> 00:05:39,760 Speaker 1: true enough, but mcquo deeply believed that this all went 112 00:05:39,800 --> 00:05:43,320 Speaker 1: back to sort of local politics. It's depressing, as we 113 00:05:43,400 --> 00:05:45,720 Speaker 1: know the people in charge of these sort of policies 114 00:05:45,800 --> 00:05:48,000 Speaker 1: knew what the result would be. Are new as an 115 00:05:48,000 --> 00:05:51,000 Speaker 1: Eggs secretary that Biden disappointed took her mother out of 116 00:05:51,040 --> 00:05:53,840 Speaker 1: an nursing home before putting this kind of policy into effect. 117 00:05:54,120 --> 00:05:56,120 Speaker 1: There was one county in New York and there's Rents 118 00:05:56,120 --> 00:05:59,400 Speaker 1: Salar County where you know Republican runs the county. He 119 00:05:59,520 --> 00:06:02,240 Speaker 1: said this nursing waters insane. He was the only person 120 00:06:02,320 --> 00:06:05,440 Speaker 1: that defined it. The only nursing home in his county 121 00:06:05,440 --> 00:06:08,040 Speaker 1: had no coronavirus deaths. So it's very clear that you 122 00:06:08,080 --> 00:06:26,800 Speaker 1: know this was what was responsible for it. I was 123 00:06:26,839 --> 00:06:30,760 Speaker 1: looking at something you highlight in your book on the 124 00:06:30,800 --> 00:06:33,600 Speaker 1: difference to New York City in San Francisco and that 125 00:06:33,920 --> 00:06:37,800 Speaker 1: they're sort of both very densely populated. But I then 126 00:06:37,800 --> 00:06:41,120 Speaker 1: went out and did my own research. New York City 127 00:06:41,160 --> 00:06:45,680 Speaker 1: has ten times the population of San Francisco, but San 128 00:06:45,720 --> 00:06:48,800 Speaker 1: Francisco had three hundred and twenty four deaths. New York 129 00:06:48,839 --> 00:06:53,920 Speaker 1: City had twenty seven thousand, one thirty eight. So if 130 00:06:54,400 --> 00:06:58,080 Speaker 1: they've been proportionate, New York should have had thirty two 131 00:06:58,160 --> 00:07:03,760 Speaker 1: hundred and forty. Yeah, they're extra twenty four thousand deaths 132 00:07:03,760 --> 00:07:07,120 Speaker 1: in New York City compared to San Francisco. How could 133 00:07:07,120 --> 00:07:10,520 Speaker 1: there be such a gigantic difference and COVID impact in 134 00:07:10,600 --> 00:07:13,119 Speaker 1: the two cities. Yeah, Well, they just took action first, 135 00:07:13,120 --> 00:07:14,960 Speaker 1: And you know, I'm not going to pretend that everything's AOK. 136 00:07:15,080 --> 00:07:16,880 Speaker 1: In San Francisco. I mean, a lot of their small 137 00:07:16,920 --> 00:07:19,200 Speaker 1: businesses are suffering just as much as in New York. 138 00:07:19,600 --> 00:07:21,280 Speaker 1: But you know, at least they don't have the COVID 139 00:07:21,320 --> 00:07:23,640 Speaker 1: death pull along with that. And it really just came 140 00:07:23,680 --> 00:07:26,560 Speaker 1: down to taking action early. They started doing mass testing 141 00:07:26,680 --> 00:07:29,560 Speaker 1: very early. They started banning very large gallerings, and like 142 00:07:29,560 --> 00:07:32,720 Speaker 1: you know, obviously I'm not pro very strict lockdown, but 143 00:07:32,920 --> 00:07:35,000 Speaker 1: you know, I don't think it's that unreasonable start of 144 00:07:35,000 --> 00:07:36,800 Speaker 1: banning mass gallerings. And they were way ahead of the 145 00:07:36,800 --> 00:07:39,240 Speaker 1: curve on that and just all these other just you know, 146 00:07:39,800 --> 00:07:42,320 Speaker 1: precautionary managers. They took ahead of time as opposed to 147 00:07:42,400 --> 00:07:45,400 Speaker 1: saying go out and congregate and you know, fight racism 148 00:07:45,440 --> 00:07:47,800 Speaker 1: by exposing yourself to a virus. But you know, it 149 00:07:47,840 --> 00:07:52,080 Speaker 1: shows up with the numbers when you compare Governor Cuomo 150 00:07:52,680 --> 00:07:57,040 Speaker 1: and Marrid Blasio, how would you compare their relative impact. 151 00:07:57,920 --> 00:08:00,160 Speaker 1: If you look at the deaths per capita, they are 152 00:08:00,240 --> 00:08:02,400 Speaker 1: much higher in the city than in the state. So 153 00:08:02,520 --> 00:08:04,640 Speaker 1: you know, naturally I would say de Vlasi did a 154 00:08:04,680 --> 00:08:07,480 Speaker 1: worse job. Obviously, the nurse at home contributed to the 155 00:08:07,520 --> 00:08:09,800 Speaker 1: Vlasi his death count as well, so it's hard to say. 156 00:08:10,040 --> 00:08:12,160 Speaker 1: I think the Blasi was probably worse. He was more 157 00:08:12,200 --> 00:08:15,360 Speaker 1: actively promoting things that were harmful. I would say he 158 00:08:15,440 --> 00:08:19,240 Speaker 1: was sort of rejecting the reality of the virus longer 159 00:08:19,280 --> 00:08:22,160 Speaker 1: than Cuomo did. Correct. Yeah, he got to the point 160 00:08:22,160 --> 00:08:23,920 Speaker 1: where so many in the advisors had to threaten to 161 00:08:23,960 --> 00:08:25,920 Speaker 1: resign to get him to take action on certain things. 162 00:08:26,360 --> 00:08:28,640 Speaker 1: And you know, he never really led by example either, 163 00:08:28,680 --> 00:08:30,720 Speaker 1: which I know we can't really expect for our politicians. 164 00:08:30,760 --> 00:08:33,040 Speaker 1: Like he banned going to the gym, and the last 165 00:08:33,080 --> 00:08:35,040 Speaker 1: thing he did on that day was good to the gym. 166 00:08:35,080 --> 00:08:37,439 Speaker 1: So he just didn't really send much of a message. 167 00:08:37,600 --> 00:08:39,959 Speaker 1: Nor did his health department even seem to really be 168 00:08:40,040 --> 00:08:42,720 Speaker 1: that focused on where you would want to fight the virus. So, 169 00:08:42,760 --> 00:08:45,400 Speaker 1: for instance, there were massive outbreaks with the New York 170 00:08:45,400 --> 00:08:47,960 Speaker 1: Police Department. The health official that encouraged people to like 171 00:08:48,000 --> 00:08:51,439 Speaker 1: Hungary in Chinatown refused to distribute MASS to the police 172 00:08:51,559 --> 00:08:54,200 Speaker 1: when they requested them and made some derography or comment 173 00:08:54,240 --> 00:08:56,920 Speaker 1: about police. Now, you know, regardless of your opinion on MASS, 174 00:08:57,240 --> 00:08:59,520 Speaker 1: she is someone who does believe they work and did 175 00:08:59,559 --> 00:09:02,400 Speaker 1: despite that explicitly refused to give them the cops, And 176 00:09:02,440 --> 00:09:04,480 Speaker 1: you know, I'm not saying that's correlated with why there's 177 00:09:04,520 --> 00:09:06,440 Speaker 1: explosion in cases, but it just shows that, you know, 178 00:09:06,480 --> 00:09:09,880 Speaker 1: the word neglecting key demographs of people for political purposes 179 00:09:10,080 --> 00:09:13,199 Speaker 1: that were disproportionately exposed to this virus. When you look 180 00:09:13,240 --> 00:09:16,360 Speaker 1: at that whole experience, it seemed to me that Cuomo 181 00:09:16,400 --> 00:09:20,360 Speaker 1: and particularly got amazingly positive coverage from the news media 182 00:09:20,880 --> 00:09:24,680 Speaker 1: despite reality. Well that's sort of what the motivation for 183 00:09:24,760 --> 00:09:26,720 Speaker 1: this book was. But at the beginning of the coronavirus 184 00:09:26,840 --> 00:09:28,400 Speaker 1: I was in the position of everyone of just kind 185 00:09:28,440 --> 00:09:30,680 Speaker 1: of accepting, well, I know nothing about this, but Cuomo 186 00:09:30,760 --> 00:09:32,280 Speaker 1: is the one getting all the praise. So I went, well, 187 00:09:32,360 --> 00:09:34,320 Speaker 1: let's see what this guy's doing if he's stigured it out. 188 00:09:34,520 --> 00:09:36,800 Speaker 1: And it turns out he's figured nothing out. As there 189 00:09:36,840 --> 00:09:39,480 Speaker 1: were praising Quomo, everyone was ragging on Sweden, which you 190 00:09:39,480 --> 00:09:42,480 Speaker 1: know very famously, you know, didn't have any official lockdown, 191 00:09:42,520 --> 00:09:44,400 Speaker 1: as the government give guidance some things to do, but 192 00:09:44,559 --> 00:09:46,880 Speaker 1: nothing was really strictly enforced. And you know, I don't 193 00:09:46,880 --> 00:09:49,040 Speaker 1: really defend their model, but I just noticed that, like 194 00:09:49,120 --> 00:09:51,520 Speaker 1: despite all the death rates Sweden war of going well, 195 00:09:51,559 --> 00:09:53,439 Speaker 1: at the same time, they're way higher in New York. 196 00:09:53,800 --> 00:09:56,280 Speaker 1: So how is it the media in the same publication 197 00:09:56,320 --> 00:09:59,000 Speaker 1: will attack Sweden but give Cuomo a pass when you 198 00:09:59,000 --> 00:10:01,240 Speaker 1: would have been saference even the whole time. And then 199 00:10:01,240 --> 00:10:03,240 Speaker 1: it was just kind of unraveling from there everything that 200 00:10:03,280 --> 00:10:05,360 Speaker 1: went wrong, you know, of which there was many. And 201 00:10:05,440 --> 00:10:08,679 Speaker 1: I think Cuomo's approval actually in the book I quoted, 202 00:10:08,720 --> 00:10:11,160 Speaker 1: it's about eighty four percent. So everyone is buying the 203 00:10:11,240 --> 00:10:14,560 Speaker 1: narrative and it's complete nonsense. No, it was amazing to 204 00:10:14,600 --> 00:10:16,880 Speaker 1: me that, you know, Cuomo could do things that we're 205 00:10:17,080 --> 00:10:21,000 Speaker 1: literally killing people, and somehow the New York media would 206 00:10:21,040 --> 00:10:23,680 Speaker 1: he praise on it. Now, it does seem to me 207 00:10:23,760 --> 00:10:27,079 Speaker 1: that as Trump sort of becomes less central to the 208 00:10:27,160 --> 00:10:31,600 Speaker 1: national dialogue, the media is suddenly much more aggressive about 209 00:10:31,640 --> 00:10:34,199 Speaker 1: going after Cuomo, and in that sense, he may be 210 00:10:34,280 --> 00:10:38,680 Speaker 1: at the beginning of a period of really serious investigative reporting. Yeah. 211 00:10:38,679 --> 00:10:40,880 Speaker 1: I mean, there's been a lot of coronavirus narrative shifts 212 00:10:40,920 --> 00:10:42,599 Speaker 1: since Trump left office. I mean, I think it was 213 00:10:42,679 --> 00:10:45,200 Speaker 1: just within like the week prior to Biden taking office 214 00:10:45,440 --> 00:10:47,800 Speaker 1: and the weeks I thought that every mayor just suddenly 215 00:10:47,840 --> 00:10:50,240 Speaker 1: went yeah, I guess bars and restaurant should be open, 216 00:10:50,240 --> 00:10:52,000 Speaker 1: and I guess school should be open after all, and 217 00:10:52,320 --> 00:10:54,360 Speaker 1: at the time, of course, is too obvious to be 218 00:10:54,400 --> 00:10:58,040 Speaker 1: a coincidence. I think how much damage did the Cuomo's 219 00:10:58,080 --> 00:11:01,640 Speaker 1: strategy due to small business in New York. I think 220 00:11:01,640 --> 00:11:03,960 Speaker 1: it's like close to at least thirty or forty percent 221 00:11:04,200 --> 00:11:07,320 Speaker 1: small businesses. Closures are probably permanent because at the time 222 00:11:07,360 --> 00:11:09,600 Speaker 1: of these lockdowns, most restaurants only had about a month 223 00:11:09,679 --> 00:11:12,760 Speaker 1: or two of cash to burn before running out. And 224 00:11:12,800 --> 00:11:15,320 Speaker 1: I've noticed in my own neighborhood there are some businesses 225 00:11:15,320 --> 00:11:17,920 Speaker 1: that are closing and then getting replaced by other businesses, 226 00:11:18,000 --> 00:11:20,440 Speaker 1: but it's not the same. It's a small business getting replaced, 227 00:11:20,480 --> 00:11:22,079 Speaker 1: but you know, a big business. I don't know. I 228 00:11:22,120 --> 00:11:24,200 Speaker 1: don't really think it's a trend we want to see, 229 00:11:24,280 --> 00:11:26,560 Speaker 1: but it's one we're seeing play out nicheanwide. We're seeing 230 00:11:26,559 --> 00:11:28,880 Speaker 1: the stock market stored a record high is in the 231 00:11:28,880 --> 00:11:30,560 Speaker 1: midst of this pandemic, and a large part of the 232 00:11:30,559 --> 00:11:33,319 Speaker 1: reason is that it's big businesses are composed I just 233 00:11:33,400 --> 00:11:35,800 Speaker 1: proportionate portion of these stock indexes, and they're the ones 234 00:11:35,840 --> 00:11:38,040 Speaker 1: getting pushed up at the expense of everyone else. I 235 00:11:38,080 --> 00:11:40,480 Speaker 1: think it's the saddest trend we've seen from this pandemic 236 00:11:40,480 --> 00:11:43,520 Speaker 1: obviously in addition to the depths. Now you focus in 237 00:11:43,559 --> 00:11:45,640 Speaker 1: your book on New York City and New York State. 238 00:11:46,120 --> 00:11:48,360 Speaker 1: Since you live in the Jersey, I have to ask you, 239 00:11:48,520 --> 00:11:52,720 Speaker 1: hasn't New Jersey had almost a parallel bad experience. Yeah, 240 00:11:52,720 --> 00:11:55,640 Speaker 1: it's worse. Actually, we have a very similar nursing on policy. 241 00:11:55,640 --> 00:11:57,600 Speaker 1: I mean, they at least tested people, but it had 242 00:11:57,600 --> 00:11:59,280 Speaker 1: its pretty much felt like that as well. And you know, 243 00:11:59,320 --> 00:12:02,439 Speaker 1: the proximity New York probably didn't help as well with it, 244 00:12:02,520 --> 00:12:05,160 Speaker 1: because the governor of New Jersey never gets the left 245 00:12:05,160 --> 00:12:07,920 Speaker 1: of publicity that the mayor and the governor of New 246 00:12:07,960 --> 00:12:11,080 Speaker 1: York to. Do you think that Cuomo will eventually take 247 00:12:11,120 --> 00:12:14,960 Speaker 1: responsibility for his actions or how does he ride this out? Well, 248 00:12:14,960 --> 00:12:16,640 Speaker 1: the thing is he doesn't really need to. I mean, 249 00:12:16,640 --> 00:12:18,240 Speaker 1: I don't need to tell you that the media works 250 00:12:18,240 --> 00:12:21,400 Speaker 1: the Democratic Party and that's what we're seeing. There is 251 00:12:21,440 --> 00:12:23,120 Speaker 1: one comment the other day he made that would have 252 00:12:23,160 --> 00:12:25,360 Speaker 1: sunk any other politician, And he was talking with an 253 00:12:25,400 --> 00:12:28,080 Speaker 1: ursing home scandal and tried to make the point that 254 00:12:28,120 --> 00:12:30,240 Speaker 1: if you die, it doesn't matter how you died. So 255 00:12:30,280 --> 00:12:32,520 Speaker 1: he said something like, yeah, people died in nursing homes 256 00:12:32,520 --> 00:12:36,079 Speaker 1: who care as people die? And I sort of understand 257 00:12:36,120 --> 00:12:38,400 Speaker 1: what he was attempting to say, but the phrasing was 258 00:12:38,440 --> 00:12:40,800 Speaker 1: just so terrible that if Trump made that comment, they 259 00:12:40,800 --> 00:12:43,360 Speaker 1: would stick to him for months, or any other politician really, 260 00:12:43,440 --> 00:12:45,920 Speaker 1: especially if the Republican I need he gets away with it. 261 00:12:46,120 --> 00:12:47,920 Speaker 1: And even with this nursing home scandal, I mean, we 262 00:12:47,920 --> 00:12:50,760 Speaker 1: haven't seen any consequences so far, and we really have 263 00:12:50,920 --> 00:12:53,280 Speaker 1: known the death toll is what that AG report said 264 00:12:53,360 --> 00:12:56,360 Speaker 1: since at least July or August, So I don't know. 265 00:12:56,400 --> 00:12:58,119 Speaker 1: It's just very heart too for me to be optimistic 266 00:12:58,120 --> 00:13:01,559 Speaker 1: to see consequences. I think it's a so bring part 267 00:13:01,600 --> 00:13:04,800 Speaker 1: of what's happening in the country that disasters can occurred 268 00:13:05,080 --> 00:13:08,920 Speaker 1: somehow nobody has ever held accountable, not unless maybe it's Trump, 269 00:13:09,320 --> 00:13:13,080 Speaker 1: but otherwise they somehow are vaccinated against any kind of 270 00:13:13,120 --> 00:13:16,520 Speaker 1: consequence for their behavior. And speaking of vaccines, you know, 271 00:13:16,640 --> 00:13:19,319 Speaker 1: he's also head in front with the rollout, and recently 272 00:13:19,320 --> 00:13:22,200 Speaker 1: his defense was, well, we're just not getting into vaccines 273 00:13:22,240 --> 00:13:24,760 Speaker 1: for the federal government to roll them out, But weeks 274 00:13:24,800 --> 00:13:27,679 Speaker 1: prior to that, he was complaining that they're not getting 275 00:13:27,679 --> 00:13:30,960 Speaker 1: it to enough people in general, so he actually expanded 276 00:13:31,000 --> 00:13:33,240 Speaker 1: their criteria for vaccinations, so you know, within just a 277 00:13:33,240 --> 00:13:36,120 Speaker 1: few weeks, contradicting himself on the reason why. And it 278 00:13:36,160 --> 00:13:38,160 Speaker 1: actually has to do with why all those people sort 279 00:13:38,200 --> 00:13:41,480 Speaker 1: of leaving in droves, those nine health officials. Was a 280 00:13:41,520 --> 00:13:43,880 Speaker 1: lot of counties have their own vaccine distribution plans, and 281 00:13:44,000 --> 00:13:46,000 Speaker 1: Quormwa decided, well, I'm going to kind of ignore the 282 00:13:46,080 --> 00:13:48,079 Speaker 1: experts and trying to come with my own. So we 283 00:13:48,200 --> 00:13:50,160 Speaker 1: hired the Lloyd to try to create a plan for him, 284 00:13:50,360 --> 00:13:53,160 Speaker 1: which is obviously very unpopular among those who are resigning. 285 00:14:10,000 --> 00:14:14,120 Speaker 1: There actually had been a pandemic plan which I think 286 00:14:14,240 --> 00:14:17,280 Speaker 1: was developed before Cuomo even became governor, but New York 287 00:14:17,320 --> 00:14:19,960 Speaker 1: didn't follow it. Yeah. I brought that up because there 288 00:14:20,000 --> 00:14:22,920 Speaker 1: was this whole narrative that Trump shredded Obama's pandemic plan 289 00:14:23,200 --> 00:14:25,320 Speaker 1: and they were kind of going blind with coronavirus. So 290 00:14:25,360 --> 00:14:27,320 Speaker 1: I was looking to that history, and well, they actually 291 00:14:27,320 --> 00:14:30,240 Speaker 1: replaced Obama's with one that was specific to an influenza 292 00:14:30,360 --> 00:14:32,960 Speaker 1: coming from China. So you know, obviously a coincidence of 293 00:14:33,040 --> 00:14:35,440 Speaker 1: the report was that specific to an influence that coming 294 00:14:35,480 --> 00:14:37,840 Speaker 1: from China, But they were way more prepared than Cloma was. 295 00:14:38,120 --> 00:14:40,360 Speaker 1: In fact, in a Quartoma book. Many people related to 296 00:14:40,400 --> 00:14:43,120 Speaker 1: culoma didn't even know this plan existed. So not only 297 00:14:43,240 --> 00:14:45,000 Speaker 1: was their plan that they didn't use it, many people 298 00:14:45,040 --> 00:14:47,600 Speaker 1: didn't even know it existed. I mean, we moved a 299 00:14:47,680 --> 00:14:52,880 Speaker 1: Navy hospital ship to New York, built out the Javits 300 00:14:52,920 --> 00:14:56,600 Speaker 1: Center to a thousand beds, and put in three Army 301 00:14:56,680 --> 00:15:00,320 Speaker 1: field hospitals. Now, I think the total use of the 302 00:15:00,000 --> 00:15:03,280 Speaker 1: any hospitals like ninety people or something. There was never 303 00:15:03,320 --> 00:15:06,680 Speaker 1: an actual shortage of hospital space in New York? Am 304 00:15:06,720 --> 00:15:09,680 Speaker 1: I wrong? You're right? And there's also regulations that made 305 00:15:09,680 --> 00:15:12,040 Speaker 1: it pretty much impossible to actually use the ship. The 306 00:15:12,120 --> 00:15:15,480 Speaker 1: regulations were they couldn't accept patients directly, they had to 307 00:15:15,520 --> 00:15:18,720 Speaker 1: be referred from a hospital. Ambulances couldn't bring anyone directly 308 00:15:18,760 --> 00:15:21,320 Speaker 1: to the ship, so you know, the two thirds of 309 00:15:21,320 --> 00:15:24,480 Speaker 1: the ways you'd get accepted there to be treated weren't possible. 310 00:15:24,760 --> 00:15:26,920 Speaker 1: But then there's also you know, a comedy of errors there. 311 00:15:26,920 --> 00:15:29,720 Speaker 1: Initially this ship was supposed to be exclusively for non 312 00:15:29,720 --> 00:15:33,200 Speaker 1: coronavirus patients. Turns out, with a few days of arriving, 313 00:15:33,200 --> 00:15:34,800 Speaker 1: one of the people who was on the ship when 314 00:15:34,800 --> 00:15:37,240 Speaker 1: it got they're caught coronavirus. So that was a disaster. 315 00:15:37,640 --> 00:15:40,000 Speaker 1: Then after a few days they changed it and repurposed 316 00:15:40,040 --> 00:15:43,480 Speaker 1: the ship specifically for coronavirus patients. So there's just no 317 00:15:43,560 --> 00:15:46,320 Speaker 1: plan and why those regulations were not just waived with 318 00:15:46,360 --> 00:15:49,440 Speaker 1: a strict dependence of mystery. Were they federal reg I 319 00:15:49,520 --> 00:15:51,400 Speaker 1: believe it was federal, But yeah, I don't know why 320 00:15:51,400 --> 00:15:53,320 Speaker 1: there was no planting there as well. Yeah, that's right. 321 00:15:53,720 --> 00:15:57,160 Speaker 1: There is a point where common sense should win. Kind 322 00:15:57,200 --> 00:15:59,400 Speaker 1: of amazing. Yeah, I don't know why he wouldn't have 323 00:15:59,440 --> 00:16:00,960 Speaker 1: just set this, you know, it's not like Trump is 324 00:16:01,000 --> 00:16:03,000 Speaker 1: aware of every federal orgulation in the books. I don't 325 00:16:03,000 --> 00:16:04,760 Speaker 1: know why he wouldn't have reached out and said, hey, 326 00:16:04,760 --> 00:16:06,680 Speaker 1: thanks to the free hospital, but we can't use it 327 00:16:06,720 --> 00:16:09,440 Speaker 1: for this reason. Please do X, Y and Z. So, 328 00:16:09,600 --> 00:16:12,640 Speaker 1: if you had to sum it up, what is it 329 00:16:12,800 --> 00:16:16,320 Speaker 1: you wish the average citizen of New York and New 330 00:16:16,400 --> 00:16:19,600 Speaker 1: York City would get from the way you've approached this 331 00:16:19,720 --> 00:16:23,960 Speaker 1: and from your better understanding of what actually happened. I 332 00:16:24,040 --> 00:16:25,680 Speaker 1: just wanted to be a kind of a wake up 333 00:16:25,720 --> 00:16:28,520 Speaker 1: to the media's narrative versus reality. I think the media 334 00:16:28,560 --> 00:16:30,840 Speaker 1: has the effective sort of putting horse blinders on us 335 00:16:30,840 --> 00:16:33,080 Speaker 1: and making us only see a narrative they want to see, 336 00:16:33,080 --> 00:16:35,200 Speaker 1: and it sort of seems to be their purpose. And 337 00:16:35,240 --> 00:16:37,040 Speaker 1: I just kind of want to wake more people up 338 00:16:37,040 --> 00:16:39,760 Speaker 1: and saying, you know, the fact that every single person 339 00:16:40,040 --> 00:16:42,520 Speaker 1: is seeing this guy's praises and giving him Emmy's doesn't 340 00:16:42,600 --> 00:16:45,360 Speaker 1: actually mean anything. It really just means he's a democrat 341 00:16:45,440 --> 00:16:48,560 Speaker 1: unfortunate enough to be one. In terms of the media bus, 342 00:16:48,600 --> 00:16:52,160 Speaker 1: one of the most amazing things was Cuomo getting an 343 00:16:52,200 --> 00:16:56,400 Speaker 1: International Emmy Founders Award and remember two thousand point quote 344 00:16:56,680 --> 00:17:00,360 Speaker 1: in recognition of his leadership during the COVID pandemic and 345 00:17:00,480 --> 00:17:04,200 Speaker 1: his masterful use of television to inform and calm people. 346 00:17:04,840 --> 00:17:07,840 Speaker 1: Why on earth would they have given him an Emmy 347 00:17:07,920 --> 00:17:11,879 Speaker 1: given the disaster that New York State was. I almost 348 00:17:11,920 --> 00:17:14,639 Speaker 1: think it's a provide cover. So if anyone criticizes us 349 00:17:14,680 --> 00:17:16,000 Speaker 1: and he can say, well, no, I got an Emmy 350 00:17:16,040 --> 00:17:19,199 Speaker 1: for it. If you were to plot coronavirus cases on 351 00:17:19,280 --> 00:17:22,600 Speaker 1: a chart in your the day he received the Emmy 352 00:17:22,800 --> 00:17:24,959 Speaker 1: is when it starts to really start taking off. So 353 00:17:25,000 --> 00:17:27,680 Speaker 1: the timing really couldn't have even worse on that, huh. 354 00:17:28,000 --> 00:17:31,639 Speaker 1: It just strikes me that the level of arrogance of 355 00:17:31,680 --> 00:17:35,800 Speaker 1: giving an Emmy to a guy who was a disaster it. 356 00:17:35,880 --> 00:17:39,920 Speaker 1: Then it tells you about the bias or the lack 357 00:17:39,960 --> 00:17:42,080 Speaker 1: of common sense of the news media. I'm not sure 358 00:17:42,119 --> 00:17:45,080 Speaker 1: which is more relevant. Yeah, I don't know. Like the 359 00:17:45,080 --> 00:17:47,160 Speaker 1: thing is, it's really not hard to check these facts. 360 00:17:47,160 --> 00:17:49,320 Speaker 1: I mean, it only takes a few Google searches to 361 00:17:49,400 --> 00:17:51,800 Speaker 1: just see what is the coronavirus death right, what's the 362 00:17:51,880 --> 00:17:54,359 Speaker 1: national average? And then we're from there. I have to 363 00:17:54,400 --> 00:17:57,159 Speaker 1: believe that they're knowingly doing it. You know, in your 364 00:17:57,160 --> 00:17:59,840 Speaker 1: book you go beyond just the health crisis and you 365 00:18:00,080 --> 00:18:03,160 Speaker 1: talk about how both do Blasio and Cuomo have really 366 00:18:03,200 --> 00:18:07,280 Speaker 1: crippled New York economically and in law and order. I mean, 367 00:18:07,280 --> 00:18:10,119 Speaker 1: what are the policies that have really begun purty New 368 00:18:10,200 --> 00:18:14,480 Speaker 1: York residents and frankly leading to a remarkable migration out 369 00:18:14,480 --> 00:18:17,320 Speaker 1: of New York to other states. And the thing about 370 00:18:17,359 --> 00:18:19,560 Speaker 1: this chapter is it really could be applied to California, 371 00:18:19,640 --> 00:18:22,119 Speaker 1: or New Jersey, Illinois, or other blue states as well. 372 00:18:22,400 --> 00:18:25,119 Speaker 1: It's not necessarily specific to them in particular. They've just 373 00:18:25,160 --> 00:18:26,719 Speaker 1: kind of jumped in front of the train and continued 374 00:18:26,800 --> 00:18:29,640 Speaker 1: all these liberal policies that have been inflating the cost 375 00:18:29,680 --> 00:18:34,399 Speaker 1: of living, racing property taxes, killing jobs, just general liberal policies. 376 00:18:34,760 --> 00:18:36,960 Speaker 1: The size of their government has gotten to the point 377 00:18:36,960 --> 00:18:39,439 Speaker 1: where it's about double the size of Florida's. And I 378 00:18:39,520 --> 00:18:41,760 Speaker 1: mentioned Florida because they're the number one state. People are 379 00:18:41,760 --> 00:18:44,320 Speaker 1: fleeing New York to leave too. So I do a 380 00:18:44,320 --> 00:18:46,800 Speaker 1: little comparison between New York and Florida, and I say, well, 381 00:18:46,800 --> 00:18:48,359 Speaker 1: you know, are they really getting a bank for their 382 00:18:48,359 --> 00:18:50,920 Speaker 1: book for paying for a government that's twice as large? 383 00:18:50,920 --> 00:18:52,240 Speaker 1: So I just go through, you know, what's the cost 384 00:18:52,320 --> 00:18:54,520 Speaker 1: of living, what's a poverty rate? After you just for 385 00:18:54,560 --> 00:18:56,919 Speaker 1: the cost of living, what are the school systems, like, 386 00:18:57,480 --> 00:18:59,679 Speaker 1: what's the average home size someone can afford to live in? 387 00:18:59,680 --> 00:19:01,840 Speaker 1: And just all these other variables in your quality of living. 388 00:19:01,880 --> 00:19:05,040 Speaker 1: And they're usually either better or close enough to New 389 00:19:05,080 --> 00:19:08,200 Speaker 1: York to be not that much distinguishable. So why pay 390 00:19:08,280 --> 00:19:11,040 Speaker 1: double when you could pay half as much basically the same? 391 00:19:11,320 --> 00:19:13,520 Speaker 1: And that's sort of the gist of that chapter. Do 392 00:19:13,560 --> 00:19:17,000 Speaker 1: you think this has been a permanent shift in the 393 00:19:17,040 --> 00:19:21,720 Speaker 1: balance of decisions towards leaving rather than state or is 394 00:19:21,720 --> 00:19:24,479 Speaker 1: it temporary? I remember I was reading something a Heritage 395 00:19:24,480 --> 00:19:26,640 Speaker 1: They were estimating that about a thousand people a day 396 00:19:27,040 --> 00:19:29,879 Speaker 1: leave from blue states to red seats, and that's unnet balanced, 397 00:19:29,880 --> 00:19:32,560 Speaker 1: so you know, accounting for migration from the opposite. I 398 00:19:32,600 --> 00:19:35,399 Speaker 1: don't know if it's accelerated since then what extent, but 399 00:19:35,480 --> 00:19:39,600 Speaker 1: a trent has continued every single year since then. You know. Ironically, though, 400 00:19:39,640 --> 00:19:42,080 Speaker 1: if these people do keep their politics, it does risk 401 00:19:42,160 --> 00:19:44,280 Speaker 1: turning many of these red states blue and then where 402 00:19:44,320 --> 00:19:46,040 Speaker 1: you go from there. That is sort of the only 403 00:19:46,040 --> 00:19:48,240 Speaker 1: concern I have about it. But it does weak in 404 00:19:48,320 --> 00:19:51,439 Speaker 1: the blue states when their tax based decays, and I 405 00:19:51,440 --> 00:19:53,400 Speaker 1: think it's going to cause a negative feedback loop where 406 00:19:53,440 --> 00:19:55,879 Speaker 1: they raise taxes further than more people leave, and you know, 407 00:19:55,880 --> 00:19:59,680 Speaker 1: so on and so forth. It's remarkable Clomos already said 408 00:19:59,680 --> 00:20:01,720 Speaker 1: he's going to run again for re election. Do you 409 00:20:01,760 --> 00:20:04,160 Speaker 1: think all of this affects him at all, or given 410 00:20:04,160 --> 00:20:08,000 Speaker 1: the nature of the New York machine, is he just invulnerable? Well, 411 00:20:08,040 --> 00:20:10,119 Speaker 1: with this approve already as it is now, it does 412 00:20:10,160 --> 00:20:12,399 Speaker 1: seem unlikely who would lose. But obviously we'd have to 413 00:20:12,440 --> 00:20:14,280 Speaker 1: be another Democrat to run against them to have a 414 00:20:14,359 --> 00:20:16,280 Speaker 1: chance kind of, you know, in New York's current climate, 415 00:20:16,760 --> 00:20:19,200 Speaker 1: which obviously is a tragedy of politics and the media 416 00:20:19,200 --> 00:20:21,679 Speaker 1: that this is even possible. Trump could do something that 417 00:20:21,760 --> 00:20:24,240 Speaker 1: was literally a situation of an Obama or a policy 418 00:20:24,280 --> 00:20:26,639 Speaker 1: and he would get portrayed as Hitler. Well, Cuomo can 419 00:20:26,640 --> 00:20:29,760 Speaker 1: send coronavirus patients and nursing homes, and it's for the 420 00:20:29,800 --> 00:20:32,919 Speaker 1: most part ignored the arsing attention now with the AG report, 421 00:20:33,000 --> 00:20:37,040 Speaker 1: But I wouldn't be surprised if it doesn't last that long. Yeah, 422 00:20:37,280 --> 00:20:39,520 Speaker 1: but obaterially because other than the New York Post, there's 423 00:20:39,560 --> 00:20:44,119 Speaker 1: no natural opponent to Cuomo in the media. Correct. Although 424 00:20:44,160 --> 00:20:47,040 Speaker 1: I was very surprised by how tough the New York 425 00:20:47,040 --> 00:20:51,440 Speaker 1: Times was on the resignation of these nine public health officials, 426 00:20:52,240 --> 00:20:54,480 Speaker 1: I did find coverage of that. Like in mainstream liberal 427 00:20:54,520 --> 00:20:58,199 Speaker 1: publications criticize them. It's just the ratio of positive to negative. 428 00:20:58,240 --> 00:21:01,040 Speaker 1: You know, there'd be ten positive for everyone can say 429 00:21:01,280 --> 00:21:03,720 Speaker 1: you are covering the negative. It's just the perception of 430 00:21:03,760 --> 00:21:05,960 Speaker 1: it is going to be way more positive for people. 431 00:21:06,440 --> 00:21:10,080 Speaker 1: That's remarkable. Well, I think you've made a significant contribution 432 00:21:10,240 --> 00:21:15,240 Speaker 1: to our understanding of what's happening in New York. I'm 433 00:21:15,280 --> 00:21:16,479 Speaker 1: like you, I think a lot of it. You can 434 00:21:16,480 --> 00:21:20,040 Speaker 1: then take that in different kinds of ways. It helps 435 00:21:20,080 --> 00:21:24,800 Speaker 1: explain Illinois and New Jersey and Connecticut and California where 436 00:21:24,800 --> 00:21:27,639 Speaker 1: we're fifteen the same way. But I really appreciate it, 437 00:21:27,680 --> 00:21:31,439 Speaker 1: and I think that your new book Dom and Dummer, 438 00:21:31,520 --> 00:21:34,760 Speaker 1: How Cuomo and Deblasio Ruined New York is really a 439 00:21:34,800 --> 00:21:38,080 Speaker 1: contribution to the national dialogue, and I commend you for 440 00:21:38,160 --> 00:21:41,400 Speaker 1: taking the time and focusing in getting that done. Thank 441 00:21:41,400 --> 00:21:42,920 Speaker 1: you very much. It was really an honor to be on. 442 00:21:42,960 --> 00:21:46,800 Speaker 1: Thank you so much for having me. Thank you to 443 00:21:46,840 --> 00:21:49,320 Speaker 1: my guest, Matt Palumbo. You can read a next sort 444 00:21:49,400 --> 00:21:52,280 Speaker 1: of his new book, Dumb and Dummer, How Cuomo and 445 00:21:52,359 --> 00:21:56,240 Speaker 1: Deblasio Ruined New York on our show page at newsworld 446 00:21:56,280 --> 00:22:00,760 Speaker 1: dot com. News World is produced by English Street sixty iHeartMedia. 447 00:22:01,160 --> 00:22:04,920 Speaker 1: Our executive producer is Debbie Meyers, our producer is guard 448 00:22:05,000 --> 00:22:09,199 Speaker 1: Zie Sloane, and our researcher is Rachel Peterson. The artwork 449 00:22:09,280 --> 00:22:13,160 Speaker 1: of the show was created by Steve ed Special thanks 450 00:22:13,160 --> 00:22:15,760 Speaker 1: to the team at Gingwich three sixty. 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