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Speaker 1: Good evening. Everyone, Welcome to Stinchfield. So the government shutdown

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Speaker 1: continues today, and now it seems the Democrats are moving

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Speaker 1: from Obamacare to Snap Benefits, anything they can do to

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Speaker 1: raise the emotional toll of the government shutdown. But I'm

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Speaker 1: here to tell you Snap benefits, there's some real problems

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Speaker 1: with this SNAP program that needs to be figured out

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Speaker 1: first and foremost. Though, here's John Fetterman, the Senator from

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Speaker 1: Pennsylvania Democrat, with some common sense for his fellow Democrats.

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Speaker 2: I'm deeply, deeply distressing to know that forty two millions

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Speaker 2: Americans are going to lose their SNAP benefits. And now

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Speaker 2: that's one of the big reasons why I refuse to

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Speaker 2: shutting our government down. And again I feel like the

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Speaker 2: Democrats really need to own the shutdown.

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Speaker 1: I did a deep dive into the SNAP program and

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Speaker 1: what I'm finding, like every other government program, it is

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Speaker 1: ripe with fraud. Ripe with fraud from a retailer perspective,

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Speaker 1: meaning they're selling goods that aren't eligible for it. The

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Speaker 1: SNAP benefits, that's the Supplemental Nutrition Assistance program. It is

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Speaker 1: ripe for fraud from the consumer perspective. Many of these

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Speaker 1: people are selling their ebt cards. You know, they get

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Speaker 1: a little card like a debit card that is loaded

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Speaker 1: up with money. They sell those for twenty thirty forty

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Speaker 1: cents on the dollar. By one account, in twenty twenty four,

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Speaker 1: it looked like up to thirteen percent of all Snap

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Speaker 1: payments were somehow fraudulent, whether they were either misappropriation, retailer fraud,

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Speaker 1: or black market fraud. This is a gentleman in New

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Speaker 1: York spelling out just how prevalent the selling of these

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Speaker 1: cars really is.

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Speaker 3: In his neighborhood.

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Speaker 4: Foodstamps and they're selling it for cash. They'll get four

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Speaker 4: thousand dollars in food stamps and they'll just take like

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Speaker 4: one thousand dollars in cash, like bro Like that's happening

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Speaker 4: like everywhere.

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Speaker 3: That's why they're mad.

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Speaker 4: That is exactly why they're mad.

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Speaker 3: Right now.

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Speaker 4: You know the thing about it too, They will never

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Speaker 4: admit to selling their food stems.

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Speaker 3: What is happening?

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Speaker 1: Well, we know what's happening because you can go online.

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Speaker 1: You can see people talking about it all over the place. Now,

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Speaker 1: why haven't we gotten an Elon Musk style investigation into

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Speaker 1: the SNAP program to root out the waste, fraud and abuse.

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Speaker 3: Look folks.

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Speaker 1: We have known it has been going on for as

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Speaker 1: long as this program has been enacted. I went back

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Speaker 1: to the archives and found this report from twenty sixteen

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Speaker 1: from ABC.

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Speaker 3: Fraud and Poor Management.

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Speaker 5: Under my public support for this program, we identified thirty

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Speaker 5: six instances where dead.

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Speaker 6: People received benefits.

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Speaker 3: More than a year after their death.

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Speaker 1: If we are doing all this work on the retailer

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Speaker 1: side and we aren't taking care of the recipient side,

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Speaker 1: we are not going to stop the fraud in trafficking.

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Speaker 1: So again, retailer side, yes, recipient side, you better believe it. Now,

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Speaker 1: all this brings us to present day. You heard dimension

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Speaker 1: dead people. Yes, there are dead people receiving SNAP benefits.

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Speaker 1: How they're eating these little debies or whatever it else

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Speaker 1: they're buying with the SNAP benefits, I have no idea,

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Speaker 1: but it's bad news. Illegal aliens as well, by some accounts,

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Speaker 1: over a million illegal aliens on the SNAP program. That's illegal.

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Speaker 1: By the way, you cannot have illegal aliens on the

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Speaker 1: SNAP program. This is Brooke Rowlins, Secretary of Agriculture. That's

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Speaker 1: the agency that runs the SNAP program.

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Speaker 7: We found one guy in six different states getting a benefit.

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Speaker 7: We found about five thousand people that are dead who

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Speaker 7: are still getting benefits like it is time to drastically

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Speaker 7: reform this program so that we can make sure that

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Speaker 7: those who are truly needy, truly vulnerable, are getting what

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Speaker 7: they need and the rest of the corruption goes away

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Speaker 7: and we can serve the American taxpayer.

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Speaker 3: Again. This goes to the corruption at every level. I

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Speaker 3: want you to take a look at this.

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Speaker 1: This was on Amazon Food eligible for SNAP benefits. You

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Speaker 1: have white sturgeon at forty eight dollars an ounce, a

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Speaker 1: state white sturgeon at sixty nine dollars an ounce. You

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Speaker 1: got crab legs as you just saw twenty one dollars

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Speaker 1: an ounce, fifty four dollars an ounce. And let me

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Speaker 1: show you this caviare that's the sturgeon Amazon eligible Truffle oil.

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Speaker 1: If you look at this stuff, Trouble oil forty nine

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Speaker 1: dollars for seventeen ounce. Now why does someone on food

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Speaker 1: assistance need caviare and truffle oil and sturgeon lobster? I

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Speaker 1: saw one thing. I saw one pino noir. Now you're

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Speaker 1: not allowed to buy alcohol. They called this is thanks

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Speaker 1: to the Dallas Express. They call Amazon and Amazons. So

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Speaker 1: all that was a one off it was a mistake. Sorry,

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Speaker 1: Pino Noir. Come on, folks, now, when you think of

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Speaker 1: all of this, I want you to think of why

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Speaker 1: this is happening. And here's a statistic that should outrage

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Speaker 1: every single one of you. You know, the average weight

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Speaker 1: of a woman, yes weight in pounds of a woman

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Speaker 1: on Snap benefits in America is two one hundred and

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Speaker 1: eleven pounds for a five foot four woman on Snap benefits.

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Speaker 1: The average weight of a woman in America not on

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Speaker 1: Snap benefits is one hundred and forty pounds. Still too

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Speaker 1: heavy in my opinion. But do you understand what's happening here?

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Speaker 1: They're not buying the right foods on the Snap program.

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Speaker 1: All of this needs to be rained in. Thank god,

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Speaker 1: we do have some Snap recipients that have critical thinking skills,

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Speaker 1: like this young woman.

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Speaker 8: You know it's cheaper than a three dollars pack of

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Speaker 8: Little Debbie Snacks, a fifty cent can of green beans. Okay,

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Speaker 8: you know it's cheaper than three packs of soda, a

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Speaker 8: bunch of cans of fifty cent cans of vegetables. Okay,

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Speaker 8: you know what's cheaper than one hundred and fifty dollars

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Speaker 8: you spent on chips, sugar, soda, all of that buying

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Speaker 8: a bunch of meat because the amount of snacks that

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Speaker 8: you bought are enough to last you two weeks, and

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Speaker 8: the amount of meat that I bought is enough to

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Speaker 8: last me the entire month of November while I wait

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Speaker 8: for food benefits to fix themselves.

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Speaker 1: You know, I'm usually the first to judge people, the

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Speaker 1: red hair, the nos ring.

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Speaker 3: I think, oh boy, no, that's a critical thinker.

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Speaker 1: She's on SNAP. She shouldn't be. She's a bright young lady.

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Speaker 1: Somebody out there will go find her, hire her. Nobody

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Speaker 1: else thinks like that. Apparently, including in government. This program needs.

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Speaker 3: To be rained in. I want to bring in now

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Speaker 3: to discuss all of this.

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Speaker 1: Research Fellow on welfare and Family Policy at the Heritage Foundation,

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Speaker 1: Rachel Sheffield, is with us.

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Speaker 3: Rachel, welcome to the program for having me.

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Speaker 1: All right, Rachel, how long have you and others at

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Speaker 1: the Heritage Foundation known about fraud inside the SNAP program?

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Speaker 9: Well, I think fraud is something that's been going on

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Speaker 9: probably since the program, but yet I don't know that

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Speaker 9: for sure, but this is something that goes it is, Yes,

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Speaker 9: it is rampant in the program, and unfortunately it's something

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Speaker 9: that I don't even think we fully know the scope

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Speaker 9: of because I don't think it's measured broadly. And you know,

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Speaker 9: SNAP is just one of one part of a much

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Speaker 9: larger welfare system. We have ninety programs at a cost

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Speaker 9: of one point seven trillion a year. And you know,

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Speaker 9: for all the fraud that's going on, for fraud that's

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Speaker 9: going on in SNAP, you know, there's more, there's more

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Speaker 9: to go around.

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Speaker 1: Unfortunately, you know, I use it as an example because

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Speaker 1: clearly what Elon Musk did and the Doge Crew of

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Speaker 1: finding wayts run abuse and basically every level of government.

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Speaker 1: But this is just one example, and I use it

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Speaker 1: as an example because the Democrats are going crazy over SNAP.

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Speaker 1: I wish though, someplace along the way, somebody inside government

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Speaker 1: would go crazy over raining this stuff in.

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Speaker 3: It doesn't appear that there's been any real strong attempt

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Speaker 3: to do that.

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Speaker 9: Yeah, sadly this Yeah, as you mentioned earlier, we have

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Speaker 9: forty two million Americans on the SNAP program. The welfare

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Speaker 9: system had, you know, it began back in the nineteen

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Speaker 9: sixties with the you know, Lynda by Johnson's War on Poverty,

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Speaker 9: and you know, he said that he wanted to address

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Speaker 9: the causes, not just the symptoms of poverty. But unfortunately,

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Speaker 9: for sixty years plus now, we have been basically just

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Speaker 9: throwing money at the symptoms rather than trying to address

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Speaker 9: the causes, rather than trying to help people improve their lives,

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Speaker 9: get into work, have a better life for their families,

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Speaker 9: rather than to be dependent on government. And so, you know,

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Speaker 9: this is an issue that is actually, you know, a

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Speaker 9: lot of Americans, Democrats, Republicans agree that if you're going

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Speaker 9: to be receiving benefits and your able body, you should

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Speaker 9: work or prepare for work, or do something. But unfortunately,

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Speaker 9: unfortunately Congressional you know, Congress has done not very much

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Speaker 9: to address this very important issue. I don't think very

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Speaker 9: many Americans know that the welfare system is so large,

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Speaker 9: one point seven trillion. It's one of the largest functions

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Speaker 9: of you know, government spending, and yet it just kind of,

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Speaker 9: you know, it gets kind of talked about as if

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Speaker 9: it's one program here or there. But it's a huge

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Speaker 9: it's a huge it's a huge system. It needs reform.

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Speaker 9: And part of that is because we really want people

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Speaker 9: to have better lives. We don't want people to just

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Speaker 9: be dependent forever and ever on government. It's not good

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Speaker 9: for them. It's not a sustainable model.

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Speaker 3: Well it isn't at all.

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Speaker 1: I'm going to play a clip for you of a

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Speaker 1: woman on Snap. She's the complete opposite of the last

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Speaker 1: woman that I played for you. In fact, she's telling

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Speaker 1: anybody that were to stop looters when the Snap program

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Speaker 1: shut down, look out, because they may kill you for

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Speaker 1: looting this food.

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Speaker 3: Watch this, please mind job business.

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Speaker 10: Those people they trying to feed their keys, and they

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Speaker 10: trying to go home and just feed their keys.

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Speaker 3: And I would.

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Speaker 10: I would hate for you to not be able to

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Speaker 10: make it back to your family, and for you to

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Speaker 10: not be able to make it back home because you

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Speaker 10: trying to save these billionaire companies.

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Speaker 1: All right, she's laughing about it that if they loot

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Speaker 1: Walmart and they come out and kill you for trying

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Speaker 1: to stop them, that you'd hate not to go home.

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Speaker 1: But the reality is there's other options out there for people.

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Speaker 1: There are food banks all over the place. I don't

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Speaker 1: think they're widely utilized because people don't want to go

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Speaker 1: to a soup kitchen. They don't want to go to

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Speaker 1: a food kitchen. They'd rather go and I guess get

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Speaker 1: the little debbies. But in the end, are there other

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Speaker 1: options for these people in time of need? Would the

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Speaker 1: SNAP programs shut down? I mean, I want people that

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Speaker 1: need assistance to have some help. But there is other

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Speaker 1: options out there, isn't there?

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Speaker 9: Rachel Well, I think yeah, as you mentioned, I mean right,

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Speaker 9: there are food banks, there are other you know, SNAP

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Speaker 9: is just one. I've you know, ninety different welfare programs

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Speaker 9: and one of you know, there are other food assistance

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Speaker 9: programs out there, to school meal programs, school and school breakfast,

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Speaker 9: uh food programs for the elderly. I mean, unfortunately, SNAP

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Speaker 9: is you know, this, this this shutdown issue touches so

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Speaker 9: many people because again, as I mentioned, our welfare system

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Speaker 9: has just been designed to kind of feed on itself,

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Speaker 9: to continue to just grow and grow and bring more

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Speaker 9: people on who then become dependent rather than becoming you know,

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Speaker 9: self reliant, rather than working and gaining those skills that

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Speaker 9: will help them get off the program. So we have

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Speaker 9: that we've created this system where we're not actually helping people,

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Speaker 9: and they and they assume that the only way forward,

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Speaker 9: you know, the only path for them is to be

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Speaker 9: dependent on government, and that is not that is not

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Speaker 9: what we should be. You know, we need to report

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Speaker 9: this so that we can actually help people get out

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Speaker 9: of get you a better place.

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Speaker 3: I believe.

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Speaker 1: My belief, Rachel is this is exactly why Democrats created this.

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Speaker 1: So when they got to a position like this, they

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Speaker 1: could put the pressure on Republicans and say, look at

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Speaker 1: all these people. The people would rise up because they're

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Speaker 1: dependent on the SNAP program. This is exactly what the

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Speaker 1: Democrats designed. It's where they wanted these Rachel Sheffield, great

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Speaker 1: avenue on the program. Thank you, and a big thanks

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Speaker 1: to the Heritage Foundation as well.

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Speaker 11: Thanks for having me tonight.

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Speaker 3: Absolutely my pleasure. All right.

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Speaker 1: I want to turn now to another little devious and

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Speaker 1: deceitful crew. Besides the Democrats, it's the Democrats henchman, and

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Speaker 1: that is the mainstream media, specifically CBS News and even

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Speaker 1: more specifically than that.

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Speaker 3: Sixty minutes, sixteen.

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Speaker 1: Minutes came out hammering away at President Trump last night.

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Speaker 3: I was so angry at this interview.

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Speaker 1: Now, I don't get me wrong, President Trump has won

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Speaker 1: courage to go sit with CBS News in sixty minutes

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Speaker 1: when he knows they hate him with a vengeance.

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Speaker 3: But he killed it.

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Speaker 12: Man.

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Speaker 1: President Trump was gold in the face of a very

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Speaker 1: combative angry which with a b reporter named Nora O'Donnell.

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Speaker 1: I knew it was going to be trouble when the

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Speaker 1: peace started out like this.

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Speaker 13: It's been five years since President Trump appeared for an

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Speaker 13: interview on sixty Minutes, so we had a lot of questions.

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Speaker 12: What are you doing.

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Speaker 13: As president to end the shutdown tonight?

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Speaker 6: He answers them.

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Speaker 13: Americans have been watching videos of ice tackling a young mother,

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Speaker 13: tear gas being used in a Chicago residential neighborhood, and

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Speaker 13: the smashing of car windows. Have some of these raids

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Speaker 13: gone too far?

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Speaker 3: No, I think they haven't gone far enough, Thank you,

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Speaker 3: mister President. They haven't. Again, it's all filled with half truce.

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Speaker 1: They don't tell you what's really behind the woman being tackled.

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Speaker 1: Who's getting in the way of ice agents trying to

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Speaker 1: do their job, not obeying command. Same thing with the

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Speaker 1: people in the car. What are you doing to stop

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Speaker 1: the shut down? Mister President? For the drumb them have

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Speaker 1: to do anything. The Democrats just have to vote for

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Speaker 1: a continuing resolution. It was angry, it was got your

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Speaker 1: style reporting, and it was exactly what I expect from

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Speaker 1: sixty Minutes.

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Speaker 3: Here's an example.

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Speaker 5: You're okay with those tactics, Yeah, because you have to

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Speaker 5: get the people out, you know, you have to look

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Speaker 5: at the people.

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Speaker 3: Many of them are murderers.

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Speaker 14: Many of them are people that were thrown out of

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Speaker 14: their countries because they were, you know, criminals.

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Speaker 1: So the tactics what tackling an illegal alien who's getting

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Speaker 1: in the way of ICE agents doing their job, that's

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Speaker 1: literally putting agents in danger and the public around her.

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Speaker 1: Smashing the window of someone who's inside a car that

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Speaker 1: refuses to obey commands when they think there's felons inside

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Speaker 1: that car, dangerous individuals who could do serious harm in

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Speaker 1: the American people. Sixty minutes told none of that story.

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Speaker 1: And then I look at this, the victims. They got

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Speaker 1: to bring up the victims, James Comy and Letitia James,

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Speaker 1: darlings of the left. Oh, mister president, aren't you engaged

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Speaker 1: in political retribution?

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Speaker 13: James Comy, John Bolton, Letitia James were all recently indicted.

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Speaker 13: There's a pattern to these names. They're all public figures

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Speaker 13: who have publicly denounced you.

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Speaker 3: Is it political retribute?

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Speaker 12: What you know?

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Speaker 3: Who got indicted?

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Speaker 14: The man you're looking at, I got indicted and I

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Speaker 14: was innocent, And here I am because I was able

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Speaker 14: to beat all of the nonsense that was thrown at me.

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Speaker 3: She shouldn't bring that up.

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Speaker 1: He was indicted in Georgia, he was indicted federally, he

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Speaker 1: was indicted in New York City, he was indicted in

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Speaker 1: New York State. They came after him from every freaking

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Speaker 1: angle to stop him from being president. And you worried

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Speaker 1: about political retribution from a guy who literally was the

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Speaker 1: leader of an attempted coop of the United States of America.

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Speaker 1: Talking about James Tomy weaponizing the FBI to not just

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Speaker 1: go after President Trump, but everybody around him, literally weaponizing

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Speaker 1: the Department of Justice. You had federal judges who act

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Speaker 1: so deviously and continue to act so previously. And they're

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Speaker 1: worried about Letitia James. She lied by all accounts on

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Speaker 1: her mortgage. There's a real victim at play here, where

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Speaker 1: there were no victims with President Trump because he didn't

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Speaker 1: do anything. First off, I am so angry at this

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Speaker 1: sixty minutes piece that sometimes people tell me I get.

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Speaker 3: Too fired up. I can't help it.

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Speaker 1: I want to bring in now Reacher, research analyst at

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Speaker 1: the Media Research Center.

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Speaker 3: I know they get fired.

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Speaker 1: Up over stuff like this. Bill Dagostino is with us. Bill,

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Speaker 1: welcome to the program.

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Speaker 6: Great to see you, Graham.

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Speaker 3: Am I overreacting? Bill?

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Speaker 15: No, I don't think you are. But I think I

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Speaker 15: have something that's probably going to upset you more, which

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Speaker 15: is that, by all accounts, this was the most even

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Speaker 15: handed interview that CBS has managed to do with President

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Speaker 15: Trump probably ever. So parse that one out for a second.

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Speaker 15: This is this is them our absolute best.

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Speaker 1: So this is like telling me that you know, crime

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Speaker 1: is down in Chicago because they only have one hundred

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Speaker 1: and fifty murders, not two hundred murders.

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Speaker 3: But so this was even handed. Bill, to explain this

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Speaker 3: to me.

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Speaker 15: Oh no, it wasn't. It was not even handed. This

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Speaker 15: is this is the closest to even handed they've ever come.

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Speaker 15: And I think this might this might genuinely be Nora

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Speaker 15: O'Donnell doing her best. The reason I say that is

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Speaker 15: because we did not see the same kind of combative, interrupting,

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Speaker 15: fact checking, et cetera that you that you saw during

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Speaker 15: for example, jd Vance's at the time as a candidate,

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Speaker 15: his debate. Right when she was one of the moderators,

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Speaker 15: she and Margaret Brennan were constantly jumping in and interrupting,

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Speaker 15: and I think that she was instructed not to, and

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Speaker 15: so instead she just wove all of the obnoxious jabs,

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Speaker 15: gotchas and whatever else into her questions. But Trump was

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Speaker 15: able to be very effective because of that, because she

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Speaker 15: couldn't just constantly jump in and stop him every time

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Speaker 15: he started on a train of thought, every thirty seconds,

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Speaker 15: and so because of that, it ended up being one

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Speaker 15: of the least effective attempts at sinking this president that

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Speaker 15: I think the media have ever done, because she was

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Speaker 15: forced to actually play by the rules. She couldn't just argue.

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Speaker 15: For example, he called Zoron Mamdanni a communistice.

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Speaker 1: Let me just play a clip for you, because I

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Speaker 1: think this is the clip where I was getting very

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Speaker 1: angry with her for doing exactly what you're saying here,

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Speaker 1: and that's interrupting him. Roll that one, guys, we can

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Speaker 1: make it much less expensive for people and give them

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Speaker 1: much better healthcare.

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Speaker 3: Willing to work with the Democrats on it.

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Speaker 14: The problem is they want to give money to prisoners,

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Speaker 14: to drug dealers, to all these millions of people that

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Speaker 14: were allowed to come in with an open border from Biden,

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Speaker 14: and nobody can do that.

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Speaker 1: One Republican would ever do that, all right, So that

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Speaker 1: wasn't quite it. But you see, where's the plan. She's

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Speaker 1: wanting a plan from him.

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Speaker 15: I'll let you continue, Bill, right, because she will she

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Speaker 15: will always do that, right, I mean, this is this

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Speaker 15: is basically the best we can expect from them until

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Speaker 15: we get essentially a complete overhaul. This is this is

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Speaker 15: the best effect that you're going to see from Barry

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Speaker 15: Weiss taking control of CBS News until they actually start

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Speaker 15: cleaning out a lot of these people. This is the

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Speaker 15: best Nora O'Donnell can do because she's always going to

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Speaker 15: push the Democrat line because she got into media to

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Speaker 15: push the Democrat line.

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Speaker 12: Right.

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Speaker 15: If you remove that from her, she has no more

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Speaker 15: rays on debtro she has no more reason to be

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Speaker 15: in the position.

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Speaker 3: That she's in.

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Speaker 15: And so if you're not satisfying with what you're seeing here,

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Speaker 15: we need an overhaul, and I would I would argue

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Speaker 15: that that's pretty much the only way forward for any

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Speaker 15: of these news networks that continue to insist that they're

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Speaker 15: objective when this is this is what they do, right,

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Speaker 15: This is this is how they question a president of

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Speaker 15: the United States, Is they essentially read a slate of

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Speaker 15: DNC talking points to him.

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Speaker 1: Yeah, here's another clip cut twenty guys, this is her

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Speaker 1: just literally trying to blame everything on President Trump.

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Speaker 5: So then what happens in the case Asumer is a

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Speaker 5: basket case and he has nothing to lose, become I

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Speaker 5: just left Japan, He's become a come a Kazi pilot.

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Speaker 13: Sounds like it's not going to get solved, the shutdown.

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Speaker 3: It's going to get sofa. Oh, it's going to get

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Speaker 3: so how we'll.

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Speaker 14: Get it sub eventually they're going to have to vote bill.

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Speaker 15: Incredible, right, I mean, so this is this is the

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Speaker 15: premise that literally every Democrat or excuse me, liberal journalists

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Speaker 15: question about how do we solve this shutdown? Starts and

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Speaker 15: ends at for any Republican, any any member of the administration,

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Speaker 15: and certainly for Trump, is well, what are you going

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Speaker 15: to do about this?

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Speaker 3: Right?

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Speaker 15: There is There is never any question about how do

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Speaker 15: you get Democrats to cave on this? How do you

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Speaker 15: get Democrats to come to the table and accept what

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Speaker 15: you're offering them? It's always well, can't you cave? Right,

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Speaker 15: It's it's always you have to negotiate. It's always well,

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Speaker 15: Mike Johnson has to has to reopen the House right

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Speaker 15: or or whatever else. It's it's never about what the

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Speaker 15: Democrats are willing to accept. It's always about what Republicans

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Speaker 15: will do to bend the need to them. The ball

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Speaker 15: is basically always in Republicans court as far as these

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Speaker 15: news media are concerned, because they want Democrats to get

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Speaker 15: what they want at the end of the day. And

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Speaker 15: so that's the premise that every question that they ask

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Speaker 15: about the shutdown starts.

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Speaker 12: From welcome back everyone.

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Speaker 1: Apologies for the technical errors, but we are back up

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Speaker 1: in morning. All right, Tomorrow is election day in many

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Speaker 1: states across the country.

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Speaker 3: What is tops of the list?

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Speaker 1: We have Virginia governor's race, we have New Jersey governor's race.

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Speaker 1: We've got the mayor's race in New York. Will a

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Speaker 1: communist take over New York City? We also have the shutdown.

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Speaker 1: How big an effect does the shutdown have on these elections?

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Speaker 3: This is poster for Lunce on CNN.

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Speaker 16: I believe that the shutdown is politically motivated. I believe

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Speaker 16: that if they wanted to, they could find common grounds.

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Speaker 16: They choose not to, and that is hurt the Republican brand,

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Speaker 16: the Republican reputation, their numbers are down, is you point

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Speaker 16: out in your own calling at Donald Trump. But the

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Speaker 16: numbers that are falling the worst, to my surprise, are

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Speaker 16: the Democrats. Everyone is being hurt by this, everyone's credibility

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Speaker 16: and respect.

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Speaker 1: So look, isn't a surprise that Congress's numbers are folding

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Speaker 1: from both sides of the aisle. No, everyone's upset with Congress,

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Speaker 1: Republicans and Democrats. But you hear what he said there,

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Speaker 1: they're more upset with Democrats. Will this have an effect

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Speaker 1: on any of these races or will Democrats run the table?

442
00:23:48,600 --> 00:23:52,199
Speaker 3: Now? I want to remind you this, Mom Donnie, is

443
00:23:52,640 --> 00:23:53,359
Speaker 3: bad news.

444
00:23:53,920 --> 00:23:59,560
Speaker 1: Mom Donnie's information about his family continues to come out here.

445
00:24:00,280 --> 00:24:05,240
Speaker 3: This was a quote from his father, Okay, his father.

446
00:24:06,480 --> 00:24:10,120
Speaker 1: According to a study by the Global Anti Semitism Policy Institute,

447
00:24:10,119 --> 00:24:13,600
Speaker 1: Mam Donni's father's quoted is saying, quote, the long term

448
00:24:13,640 --> 00:24:18,560
Speaker 1: security of a Jewish homeland in historic Palestine requires the

449
00:24:18,640 --> 00:24:23,200
Speaker 1: dismantling of the Jewish state, confirming what many of us

450
00:24:23,240 --> 00:24:26,200
Speaker 1: believe was that Mam Donni is a total anti semit

451
00:24:26,880 --> 00:24:29,480
Speaker 1: But we have problems with our own Republican party with

452
00:24:29,520 --> 00:24:32,600
Speaker 1: anti Semites as well, So I don't know if this

453
00:24:32,720 --> 00:24:35,040
Speaker 1: plays a big role in New York. Certainly New York

454
00:24:35,119 --> 00:24:38,560
Speaker 1: is a Jewish town. You would think it would, but

455
00:24:38,600 --> 00:24:42,639
Speaker 1: they haven't shown me before that they will push against

456
00:24:42,640 --> 00:24:47,520
Speaker 1: people that hate Jews, Democrats being number one on that list. Now,

457
00:24:48,200 --> 00:24:52,119
Speaker 1: Trump called Mam Donni a communist. I believe he is.

458
00:24:52,600 --> 00:24:54,080
Speaker 1: I think he's worse than that. I think he's a

459
00:24:54,160 --> 00:24:56,440
Speaker 1: terrorist sympathizer as well. Trump says, you know what, we're

460
00:24:56,440 --> 00:24:58,200
Speaker 1: gonna hold up money to New York. You're gotta have

461
00:24:58,240 --> 00:25:02,040
Speaker 1: a terrorist sympathizer, communist send federal tax dollars to New

462
00:25:02,080 --> 00:25:04,840
Speaker 1: York City only to have it wasted on city run

463
00:25:04,920 --> 00:25:05,960
Speaker 1: grocery stores.

464
00:25:06,240 --> 00:25:07,760
Speaker 3: This was Mom Donnie's response.

465
00:25:08,600 --> 00:25:12,120
Speaker 17: Now, Donald Trump may speak as if it is his decision,

466
00:25:12,960 --> 00:25:16,000
Speaker 17: but this is money that this city is owned. This

467
00:25:16,080 --> 00:25:19,280
Speaker 17: is money that we will expect to collect. And I

468
00:25:19,359 --> 00:25:23,600
Speaker 17: will take every single day after this election to put

469
00:25:23,640 --> 00:25:27,600
Speaker 17: together my city government, my city hall, to ensure that

470
00:25:27,680 --> 00:25:30,320
Speaker 17: it is prepared not only for the threats from Donald Trump,

471
00:25:30,480 --> 00:25:33,040
Speaker 17: but also the threats from an affordability crisis.

472
00:25:34,800 --> 00:25:36,520
Speaker 3: So he's going to try to push back.

473
00:25:36,560 --> 00:25:38,760
Speaker 1: That plays well with his base, It doesn't play well

474
00:25:38,800 --> 00:25:39,639
Speaker 1: with the American people.

475
00:25:39,680 --> 00:25:42,520
Speaker 3: The only problem Is. He's in New York City. If

476
00:25:42,560 --> 00:25:45,160
Speaker 3: New York gets a Communist for a mayor, I hope

477
00:25:45,200 --> 00:25:47,720
Speaker 3: they suffer. I really do. That's my hometown, by the way,

478
00:25:48,160 --> 00:25:49,199
Speaker 3: and I'm sorry to say that.

479
00:25:49,280 --> 00:25:51,360
Speaker 1: I got a lot of New York friends there watching.

480
00:25:52,200 --> 00:25:55,000
Speaker 1: I know the guys out at the America Warehouse. I

481
00:25:55,000 --> 00:25:58,040
Speaker 1: don't want you to suffer. But quite frankly, New York

482
00:25:58,119 --> 00:25:59,720
Speaker 1: is going to get what it deserves. They elect this

483
00:25:59,800 --> 00:26:03,720
Speaker 1: guy in the office. My guy is Curtis Sliwa. Cuomo's

484
00:26:03,760 --> 00:26:04,960
Speaker 1: the one who should have stepped down.

485
00:26:05,040 --> 00:26:07,600
Speaker 3: Not Sliwa, here's Curtis.

486
00:26:08,160 --> 00:26:11,720
Speaker 1: They talked about favorability, which your panel was mentioning.

487
00:26:12,200 --> 00:26:14,080
Speaker 3: I and Barack Obama.

488
00:26:13,760 --> 00:26:16,280
Speaker 14: Rated out the best in New York City in terms

489
00:26:16,320 --> 00:26:19,960
Speaker 14: of national, local, and state figures fifty two percent.

490
00:26:20,240 --> 00:26:23,960
Speaker 3: The unfavorable ratings for Arewel Cuomo were miserable. You can't

491
00:26:23,960 --> 00:26:24,600
Speaker 3: overcome that.

492
00:26:24,840 --> 00:26:28,159
Speaker 1: Everybody loves Curtis, like to show everybody loves Raymond, and

493
00:26:28,200 --> 00:26:32,360
Speaker 1: now I have to translate it into boats tomorrow. Now,

494
00:26:32,359 --> 00:26:34,800
Speaker 1: I understand it's important to go on CNN, but I'm

495
00:26:34,800 --> 00:26:36,439
Speaker 1: going to tell you this about Curtis Sliwa.

496
00:26:37,480 --> 00:26:39,560
Speaker 3: I had sent text messages to his sister.

497
00:26:39,640 --> 00:26:43,000
Speaker 1: I sent emails to him, I talked to his friends

498
00:26:43,040 --> 00:26:44,560
Speaker 1: about getting him on the program.

499
00:26:44,560 --> 00:26:46,840
Speaker 3: You're going to have to rally strong concerns. There are

500
00:26:46,880 --> 00:26:47,880
Speaker 3: a lot in New York.

501
00:26:48,840 --> 00:26:52,000
Speaker 1: I got nothing back, not even a response back from

502
00:26:52,040 --> 00:26:55,919
Speaker 1: the Curtis Sliwa campaign. So again, you know, these guys

503
00:26:55,960 --> 00:27:00,000
Speaker 1: make their beds in many respects. I want to bring

504
00:27:00,200 --> 00:27:03,320
Speaker 1: in now though, director of Big Data poll and host

505
00:27:03,359 --> 00:27:05,959
Speaker 1: of Inside the Numbers, Rich Barris is back with us.

506
00:27:06,000 --> 00:27:07,119
Speaker 3: Rich. It's always good to see you.

507
00:27:07,800 --> 00:27:10,000
Speaker 6: It's always great to be here. Thanks for having me.

508
00:27:10,760 --> 00:27:14,240
Speaker 1: All right, Rich, Let's talk about maybe where we have

509
00:27:14,320 --> 00:27:16,880
Speaker 1: a better chance than New York. I have a feeling, mom,

510
00:27:16,920 --> 00:27:21,000
Speaker 1: Donnie's gonna win there. Let's talk about New Jersey. First,

511
00:27:21,440 --> 00:27:25,080
Speaker 1: Jack Chitarelli. That seems to be the closest to the bunch.

512
00:27:25,160 --> 00:27:26,440
Speaker 1: How are you seeing that race?

513
00:27:27,280 --> 00:27:28,320
Speaker 6: It is the closest.

514
00:27:28,480 --> 00:27:31,199
Speaker 18: Honestly, I think Republicans are most likely going to have

515
00:27:31,200 --> 00:27:34,879
Speaker 18: a bad night tomorrow and Jack Sidarelli is the best

516
00:27:35,000 --> 00:27:37,920
Speaker 18: chance they have for a win, which you know would

517
00:27:37,920 --> 00:27:41,159
Speaker 18: be viewed as an upset right now. But I would

518
00:27:41,400 --> 00:27:43,920
Speaker 18: just note that the polling has not been very good

519
00:27:44,040 --> 00:27:46,600
Speaker 18: in the state of New Jersey. And even some of

520
00:27:46,680 --> 00:27:49,840
Speaker 18: the polls that give Mikey Cheryl a bigger lead are

521
00:27:49,920 --> 00:27:53,000
Speaker 18: still close these this is a close race. So I

522
00:27:53,000 --> 00:27:56,200
Speaker 18: think the X factor here is that the polls, especially

523
00:27:56,240 --> 00:27:58,920
Speaker 18: the better ones, are showing that Cidarewi is winning a

524
00:27:58,960 --> 00:28:02,480
Speaker 18: lot of Democrats lot, so while Republicans did not post

525
00:28:02,560 --> 00:28:04,800
Speaker 18: the early vote numbers that I want to see, the

526
00:28:05,000 --> 00:28:09,679
Speaker 18: X factor is how many of these Democrats come out tomorrow,

527
00:28:10,000 --> 00:28:13,600
Speaker 18: because that will even be a higher crossover number for Jacksonarelli.

528
00:28:13,640 --> 00:28:15,439
Speaker 6: And he's proven he can do it. He did it

529
00:28:15,480 --> 00:28:16,080
Speaker 6: in twenty one.

530
00:28:16,359 --> 00:28:20,160
Speaker 18: It looks even bigger this year, and that can really

531
00:28:20,200 --> 00:28:24,200
Speaker 18: present a challenge for polling. It really can. So I think,

532
00:28:24,240 --> 00:28:27,320
Speaker 18: you know, that's the brighter spot for the night. And

533
00:28:27,359 --> 00:28:28,840
Speaker 18: by the way, I'm glad you said what you said

534
00:28:28,840 --> 00:28:31,600
Speaker 18: about New York. I'm a Five Boroughs guy myself. I

535
00:28:31,640 --> 00:28:34,520
Speaker 18: live in the South now, but my family was Staten Island,

536
00:28:34,520 --> 00:28:37,520
Speaker 18: Brooklyn and Queens long long tradition.

537
00:28:37,240 --> 00:28:39,520
Speaker 6: In the Five Boroughs. I don't want to see either.

538
00:28:39,800 --> 00:28:41,800
Speaker 18: But the fact of the matter is this has been

539
00:28:41,840 --> 00:28:43,720
Speaker 18: going on a while, and the government you elect is

540
00:28:43,720 --> 00:28:44,960
Speaker 18: the government you deserve.

541
00:28:46,200 --> 00:28:46,440
Speaker 3: You know.

542
00:28:46,960 --> 00:28:50,040
Speaker 1: I hope when it comes to New York if they

543
00:28:50,080 --> 00:28:52,720
Speaker 1: go down this route that it makes a difference.

544
00:28:52,760 --> 00:28:54,520
Speaker 3: Now, I do morning drive radio out.

545
00:28:54,400 --> 00:28:57,960
Speaker 1: In Los Angeles, Rich, Los Angeles got even worse than

546
00:28:58,000 --> 00:29:00,800
Speaker 1: New York. It doesn't seem to make a difference to

547
00:29:00,840 --> 00:29:03,080
Speaker 1: the people of LA. I mean, that place is a

548
00:29:03,120 --> 00:29:05,840
Speaker 1: hell hole now with crime and homelessness and everything, and

549
00:29:06,200 --> 00:29:08,560
Speaker 1: nobody seems to make a change when they vote Rich.

550
00:29:09,800 --> 00:29:12,080
Speaker 18: I got to tell you to the out migration, New

551
00:29:12,160 --> 00:29:17,040
Speaker 18: York's actual greatest export is human beings. People have been

552
00:29:17,080 --> 00:29:22,280
Speaker 18: fleeing that state, and they've been Republican voters, particularly ramping

553
00:29:22,360 --> 00:29:25,520
Speaker 18: up during COVID. Even my own uncle he would like,

554
00:29:25,680 --> 00:29:29,800
Speaker 18: never value, I'm never leaving Queens left, He's gone.

555
00:29:30,080 --> 00:29:32,200
Speaker 6: So you know, there's another I just saw.

556
00:29:32,800 --> 00:29:34,360
Speaker 18: I don't know if they're going to publish this or not,

557
00:29:34,440 --> 00:29:37,800
Speaker 18: but I just saw this study anticipating what happens if

558
00:29:37,840 --> 00:29:40,920
Speaker 18: mom Donnie gets elected, and it's upwards of ten percent

559
00:29:41,000 --> 00:29:44,440
Speaker 18: of the state of New York will leave if Mom

560
00:29:44,520 --> 00:29:45,480
Speaker 18: Donnie gets elected.

561
00:29:47,720 --> 00:29:49,480
Speaker 3: That's a ridiculous.

562
00:29:48,880 --> 00:29:49,640
Speaker 6: Amount of people.

563
00:29:49,880 --> 00:29:52,440
Speaker 18: And what happens when that Yeah, when that occurs, that

564
00:29:52,520 --> 00:29:56,240
Speaker 18: outward migration occurs. Same thing we saw in California until

565
00:29:56,240 --> 00:29:58,960
Speaker 18: the Hispanic vote started to shift a bit more dramatically.

566
00:29:59,400 --> 00:30:02,000
Speaker 18: These voters they go and they vote with their feet

567
00:30:02,080 --> 00:30:04,360
Speaker 18: and they go to North Carolina, they go to Florida,

568
00:30:04,400 --> 00:30:08,240
Speaker 18: they go to Georgia, and they vote Republican. So unfortunately,

569
00:30:08,640 --> 00:30:11,400
Speaker 18: you know, I would I would almost give this analogy

570
00:30:11,440 --> 00:30:13,320
Speaker 18: to like a short sail, you know, when a company

571
00:30:13,680 --> 00:30:16,200
Speaker 18: or or selling, when a company needs liquidity and they're

572
00:30:16,240 --> 00:30:18,040
Speaker 18: in they're in a selling crisis.

573
00:30:18,040 --> 00:30:20,040
Speaker 6: We were just talking about this on social media in

574
00:30:20,080 --> 00:30:20,480
Speaker 6: my group.

575
00:30:21,040 --> 00:30:23,480
Speaker 18: They keep selling to get more liquidity, which causes the

576
00:30:23,520 --> 00:30:25,640
Speaker 18: price to you know, the stock to just keep going

577
00:30:25,680 --> 00:30:27,520
Speaker 18: down and down, and that ends up in a crisis

578
00:30:27,520 --> 00:30:30,560
Speaker 18: and a tailspin and then there's no floor. And I mean,

579
00:30:30,720 --> 00:30:33,800
Speaker 18: of course I hope that doesn't happen, but unfortunately we

580
00:30:33,840 --> 00:30:35,120
Speaker 18: have seen this time and time again.

581
00:30:35,960 --> 00:30:39,640
Speaker 1: Yeah, I agree with you on that. Let's take a

582
00:30:39,640 --> 00:30:44,280
Speaker 1: look at Virginia. Now, Virginia, I love win some seers.

583
00:30:44,480 --> 00:30:46,440
Speaker 1: I think she's a great Canada. I think she'd make

584
00:30:46,480 --> 00:30:49,520
Speaker 1: a great governor. Why is she not getting the traction

585
00:30:49,680 --> 00:30:51,320
Speaker 1: that Glenn Youngkin got.

586
00:30:51,080 --> 00:30:51,800
Speaker 3: Four years ago.

587
00:30:52,640 --> 00:30:56,160
Speaker 18: I think Youngkin ran an almost flawless campaign. I mean,

588
00:30:56,200 --> 00:30:59,760
Speaker 18: there is also the States voting tradition which is the opposite.

589
00:30:59,840 --> 00:31:02,320
Speaker 18: We're against Democrats in New Jersey, but in here, in

590
00:31:02,360 --> 00:31:05,240
Speaker 18: the case of Virginia, they have a very long tradition

591
00:31:05,320 --> 00:31:08,560
Speaker 18: of electing the party for governor that is the opposite

592
00:31:08,600 --> 00:31:10,560
Speaker 18: party of the White House that just won in the

593
00:31:10,600 --> 00:31:12,480
Speaker 18: preceding election, the presidential election.

594
00:31:12,960 --> 00:31:15,280
Speaker 6: So this is an uphill battle for Sears.

595
00:31:15,360 --> 00:31:17,400
Speaker 18: But I do think there's something to be said for

596
00:31:17,440 --> 00:31:19,280
Speaker 18: a little bit of a lesson and know your audience.

597
00:31:19,960 --> 00:31:22,520
Speaker 18: We were actually analyzing this how much money went toward

598
00:31:22,560 --> 00:31:25,760
Speaker 18: different messaging and what you know, what what ads they

599
00:31:25,800 --> 00:31:28,360
Speaker 18: were running in the message they were presenting, and while

600
00:31:28,400 --> 00:31:30,920
Speaker 18: the polls and all the research was screaming that people

601
00:31:30,920 --> 00:31:33,960
Speaker 18: were saying, like everywhere else in the country, cost of living,

602
00:31:34,080 --> 00:31:37,400
Speaker 18: cost of living, cost of living, she was focused on

603
00:31:37,480 --> 00:31:39,560
Speaker 18: urch airy issues like the trans issue.

604
00:31:39,600 --> 00:31:42,320
Speaker 6: Glenn Youngkin, he walked into.

605
00:31:42,200 --> 00:31:46,200
Speaker 18: Bubblegum at the same time and he was this is

606
00:31:46,880 --> 00:31:49,959
Speaker 18: a special kind of campaign, you know, not that many

607
00:31:50,000 --> 00:31:53,720
Speaker 18: campaigns could be, you know, given the accolades that Glenn

608
00:31:53,720 --> 00:31:57,520
Speaker 18: Youngkin can. I mean, he made grocery store prices and

609
00:31:57,640 --> 00:32:00,719
Speaker 18: other prices and cost of living issues the number one

610
00:32:00,960 --> 00:32:03,640
Speaker 18: while never letting go of those other issues. And there

611
00:32:03,640 --> 00:32:06,880
Speaker 18: were specific events in loud And County that year dealing

612
00:32:06,920 --> 00:32:10,480
Speaker 18: with schools that amplified that message when he talked about

613
00:32:10,480 --> 00:32:11,280
Speaker 18: the trans issues.

614
00:32:11,360 --> 00:32:13,320
Speaker 6: So I think she just missed the mark.

615
00:32:13,360 --> 00:32:15,320
Speaker 18: I think it was, you know, a lesson of knowing

616
00:32:15,360 --> 00:32:18,719
Speaker 18: your audience, knowing it well well.

617
00:32:19,080 --> 00:32:23,920
Speaker 1: I placed a bet on Calshie that the Democrats would

618
00:32:24,000 --> 00:32:28,480
Speaker 1: not sweep Sweet and a twenty dollars bet on Calcy

619
00:32:28,520 --> 00:32:31,280
Speaker 1: that the Democrats would not sweep New York, New Jersey

620
00:32:31,960 --> 00:32:35,360
Speaker 1: or New York now pays one hundred dollars. So it's

621
00:32:35,400 --> 00:32:38,440
Speaker 1: looking like a twenty percent chance that they don't sweep

622
00:32:38,480 --> 00:32:41,640
Speaker 1: an eighty percent chance that they do. Yeah, I think

623
00:32:41,680 --> 00:32:44,440
Speaker 1: that you're legit real quick, probably right.

624
00:32:44,400 --> 00:32:46,360
Speaker 6: Rich, I think that's probably right.

625
00:32:46,560 --> 00:32:46,800
Speaker 11: I do.

626
00:32:47,680 --> 00:32:50,520
Speaker 6: I again, though I would not count Jack out. I

627
00:32:50,640 --> 00:32:51,240
Speaker 6: really wouldn't.

628
00:32:51,320 --> 00:32:55,440
Speaker 18: He's a great retail politician, and we already know he's overperformed.

629
00:32:55,720 --> 00:32:58,600
Speaker 6: I just didn't like the early vote numbers that I saw.

630
00:32:59,040 --> 00:33:03,120
Speaker 18: Not that Democrats doing gangbuster job either, It's just that

631
00:33:03,360 --> 00:33:06,760
Speaker 18: there was there's some very real Virginia too, some very

632
00:33:06,800 --> 00:33:09,280
Speaker 18: real issues with Republicans being able to get out these

633
00:33:09,360 --> 00:33:11,720
Speaker 18: Trump voters that are low prop voters and then to

634
00:33:11,760 --> 00:33:14,200
Speaker 18: my surprise in the last week, even some of the

635
00:33:14,240 --> 00:33:16,000
Speaker 18: three out of four US and four out of fours,

636
00:33:17,360 --> 00:33:20,200
Speaker 18: we're not showing up where I was really needing to

637
00:33:20,200 --> 00:33:21,000
Speaker 18: see them.

638
00:33:21,360 --> 00:33:23,480
Speaker 3: If you want to win, you gotta show up. We

639
00:33:23,640 --> 00:33:26,239
Speaker 3: gotta show up. Always. Always great to have you out

640
00:33:26,280 --> 00:33:26,760
Speaker 3: of program.

641
00:33:26,800 --> 00:33:29,240
Speaker 6: Thanks all the best.

642
00:33:29,760 --> 00:33:31,200
Speaker 3: Absolutely you two. All right.

643
00:33:31,240 --> 00:33:33,239
Speaker 1: Gold is up around forty percent this year, and if

644
00:33:33,240 --> 00:33:36,720
Speaker 1: your portion of your savings isn't diversified into gold, you're

645
00:33:36,760 --> 00:33:37,480
Speaker 1: missing the boat.

646
00:33:37,520 --> 00:33:38,200
Speaker 3: Here's the facts.

647
00:33:38,200 --> 00:33:41,560
Speaker 1: Inflation is still too high, the US dollars still too weak,

648
00:33:41,600 --> 00:33:44,880
Speaker 1: and the government debt is insurmountable. This is why central

649
00:33:44,920 --> 00:33:47,920
Speaker 1: banks are flocking to gold. They're the ones driving prices

650
00:33:48,000 --> 00:33:50,520
Speaker 1: up to record highs. But it's not too late to

651
00:33:50,520 --> 00:33:53,440
Speaker 1: buy gold from Birch Gold Group. They'll help you convert

652
00:33:53,480 --> 00:33:55,880
Speaker 1: an existing IRA or four to one k into attack

653
00:33:55,960 --> 00:33:57,360
Speaker 1: sheltered IRA and gold.

654
00:33:57,400 --> 00:33:58,080
Speaker 3: Get started.

655
00:33:58,160 --> 00:34:01,520
Speaker 1: Just text America to the number nine nine eight. Claim

656
00:34:01,520 --> 00:34:05,240
Speaker 1: you're free. infoKit. There's no obligation, just useful information. Text

657
00:34:05,240 --> 00:34:07,920
Speaker 1: America to the number nine eight.

658
00:34:08,440 --> 00:34:08,839
Speaker 3: All right.

659
00:34:09,680 --> 00:34:15,360
Speaker 1: Up next, a friend of ours confronts I'm not so

660
00:34:15,520 --> 00:34:18,680
Speaker 1: big friend of ours, not Maduro, somebody else.

661
00:34:18,719 --> 00:34:32,600
Speaker 19: We'll get to that next flok's next up on.

662
00:34:32,560 --> 00:34:35,120
Speaker 1: The who should be charged perad would certainly in my

663
00:34:35,200 --> 00:34:37,520
Speaker 1: mind be John Brennan, the former director of the CIA.

664
00:34:37,560 --> 00:34:41,520
Speaker 1: He was an integral part of the attempted coup of America. Well,

665
00:34:41,560 --> 00:34:44,760
Speaker 1: Congress has referred to the DOJ for lying to Congress.

666
00:34:45,160 --> 00:34:48,280
Speaker 1: But one of our regulars here, a long time career

667
00:34:48,360 --> 00:34:53,920
Speaker 1: intelligence guy, Tom Especiale, confronted Brennan, you gotta see this,

668
00:34:54,840 --> 00:34:55,480
Speaker 1: why think.

669
00:35:00,480 --> 00:35:01,560
Speaker 3: And you misrepresented that.

670
00:35:01,600 --> 00:35:03,160
Speaker 20: We never said it was the suspasion said it was

671
00:35:03,239 --> 00:35:05,359
Speaker 20: Russian influence operations, which is what they do.

672
00:35:05,640 --> 00:35:14,760
Speaker 3: The difference between no, you don't know that, you filing

673
00:35:15,760 --> 00:35:17,200
Speaker 3: all the cub.

674
00:35:19,719 --> 00:35:23,640
Speaker 1: Hell top smiling after it. Brennan looks like a child

675
00:35:23,760 --> 00:35:26,040
Speaker 1: on the playground. So as we said it was a

676
00:35:26,120 --> 00:35:29,640
Speaker 1: Russian influence operation, anybody who looked at that Hunter Biden

677
00:35:29,760 --> 00:35:31,760
Speaker 1: laptop knew that was not Russian influence.

678
00:35:31,880 --> 00:35:32,600
Speaker 12: It was legit.

679
00:35:33,160 --> 00:35:34,920
Speaker 1: I mean, you didn't have to even be an intel

680
00:35:34,960 --> 00:35:37,200
Speaker 1: guy to figure that out. I want to bring in

681
00:35:37,320 --> 00:35:39,960
Speaker 1: now the man you just saw, thirty year career Army

682
00:35:40,000 --> 00:35:44,480
Speaker 1: intelligence officer, senior US Intelligence professional and senior collection strategists

683
00:35:44,480 --> 00:35:48,839
Speaker 1: on domestic terrorism and ODN I from October twenty twenty

684
00:35:48,920 --> 00:35:51,880
Speaker 1: to January twenty at twenty twenty one. It's a long intro,

685
00:35:52,160 --> 00:35:55,719
Speaker 1: too long. Thomas Speciale is with us. Thomas, welcome to

686
00:35:55,760 --> 00:35:58,560
Speaker 1: the program. Hey, it's good to be here. Thanks for

687
00:35:58,640 --> 00:36:01,719
Speaker 1: having me. Well, I saw that and I said, oh

688
00:36:01,800 --> 00:36:05,439
Speaker 1: my gosh, I gotta get you one because you said,

689
00:36:05,520 --> 00:36:08,360
Speaker 1: why did you do that letter about the Hunter Biden laptop?

690
00:36:08,440 --> 00:36:09,880
Speaker 3: What did you make of his response?

691
00:36:12,080 --> 00:36:15,920
Speaker 21: I'm a career interrogator, I've been you know, I'm trained

692
00:36:15,960 --> 00:36:20,200
Speaker 21: to make provocative statements and see how people react and.

693
00:36:22,239 --> 00:36:23,680
Speaker 11: And what that wasn't planned.

694
00:36:24,000 --> 00:36:26,719
Speaker 21: That's just kind of what naturally came out is, you know,

695
00:36:27,000 --> 00:36:31,719
Speaker 21: why would you sign that memo with everybody knowing that

696
00:36:32,160 --> 00:36:36,080
Speaker 21: the Hunter Biden laptop was legitimate? Why would you do that?

697
00:36:36,320 --> 00:36:40,320
Speaker 21: And I believe the answer is very clear. You know,

698
00:36:40,440 --> 00:36:44,080
Speaker 21: the Morell email basically lays it all out. We want

699
00:36:44,160 --> 00:36:46,960
Speaker 21: to give Biden a talking point in the debate on

700
00:36:47,120 --> 00:36:50,600
Speaker 21: this Hunter Biden laptop, and we need your help. And

701
00:36:50,840 --> 00:36:54,800
Speaker 21: I think that they made a catastrophic error in doing so,

702
00:36:55,040 --> 00:36:58,520
Speaker 21: because what they did was is they, for all intents

703
00:36:58,560 --> 00:37:03,080
Speaker 21: and purposes, they Kentuck conducted offensive counterintelligence against the American people.

704
00:37:03,239 --> 00:37:07,719
Speaker 21: These guys are trained intelligence officers. They knew exactly what

705
00:37:07,920 --> 00:37:09,799
Speaker 21: to say and exactly how to.

706
00:37:09,800 --> 00:37:10,840
Speaker 11: Get it out into the media.

707
00:37:11,520 --> 00:37:15,160
Speaker 21: And then Biden was probably told exactly what to say

708
00:37:15,960 --> 00:37:19,040
Speaker 21: in response, and it was it was done, you know.

709
00:37:19,080 --> 00:37:22,400
Speaker 21: And I make very clear, folks, this is not about

710
00:37:23,160 --> 00:37:25,120
Speaker 21: This is not about what they did to Trump or

711
00:37:25,200 --> 00:37:27,239
Speaker 21: what they did to Carter Page, or even what they

712
00:37:27,280 --> 00:37:30,800
Speaker 21: did to Michael Flynn. They did all of these things

713
00:37:30,920 --> 00:37:37,759
Speaker 21: that they did to us. They did all these disinformation campaigns.

714
00:37:37,280 --> 00:37:38,240
Speaker 3: All these lies.

715
00:37:38,960 --> 00:37:42,880
Speaker 11: They did it to the electorate to steal the election,

716
00:37:43,800 --> 00:37:44,480
Speaker 11: to take the election.

717
00:37:45,880 --> 00:37:48,719
Speaker 1: It wasn't just that interaction. And I love that you

718
00:37:48,840 --> 00:37:51,040
Speaker 1: have a beer in your hand, by the way, that's

719
00:37:51,160 --> 00:37:53,640
Speaker 1: like the best part, because disarmy.

720
00:37:53,719 --> 00:37:55,560
Speaker 3: I mean, well, of course it is.

721
00:37:56,000 --> 00:37:58,839
Speaker 1: And I also think it's it's it's disarming.

722
00:37:58,960 --> 00:38:00,360
Speaker 3: I mean, I know you could use this weapon.

723
00:38:00,440 --> 00:38:02,879
Speaker 1: But more than that, I used to walk into confrontational

724
00:38:02,960 --> 00:38:05,000
Speaker 1: interviews with a cup of coffee in my hand, just

725
00:38:05,080 --> 00:38:07,320
Speaker 1: to show that I'm not all worried about the interview

726
00:38:07,920 --> 00:38:11,120
Speaker 1: as a way, and so I love that aspect of it.

727
00:38:11,200 --> 00:38:13,560
Speaker 1: But you also confronted him while he was on stage.

728
00:38:13,640 --> 00:38:15,640
Speaker 1: Let me play this clip for everybody.

729
00:38:16,040 --> 00:38:19,239
Speaker 20: I would like to hear what your justification was for

730
00:38:19,400 --> 00:38:23,800
Speaker 20: supporting the dossier that was known to be false being

731
00:38:24,080 --> 00:38:29,319
Speaker 20: used as source material in the second ica, I don't know.

732
00:38:29,320 --> 00:38:30,160
Speaker 3: Who put you up to this.

733
00:38:30,360 --> 00:38:31,200
Speaker 11: Nobody put me up to.

734
00:38:31,160 --> 00:38:33,040
Speaker 15: This or I'm here on what role you played or

735
00:38:33,080 --> 00:38:35,800
Speaker 15: who I Want's a bunch of that you just passed on.

736
00:38:36,560 --> 00:38:40,240
Speaker 11: Absolutely, the emails are clear. So the emails are clear.

737
00:38:40,920 --> 00:38:41,839
Speaker 11: The emails are clear.

738
00:38:42,640 --> 00:38:49,680
Speaker 1: The second question, you nailed them, and you could tell

739
00:38:49,760 --> 00:38:51,920
Speaker 1: from his body language he knows you nailed him.

740
00:38:51,960 --> 00:38:56,920
Speaker 11: Thomas, Yeah, yeah, the uh, this was totally not planned

741
00:38:56,920 --> 00:38:57,319
Speaker 11: on my part.

742
00:38:57,400 --> 00:39:00,440
Speaker 21: It was like by accident that I saw this event

743
00:39:00,760 --> 00:39:02,040
Speaker 21: a couple of days before it.

744
00:39:02,239 --> 00:39:03,040
Speaker 11: I registered.

745
00:39:04,600 --> 00:39:06,759
Speaker 21: I was hoping to get maybe a side you know,

746
00:39:06,920 --> 00:39:10,239
Speaker 21: sidebar conversation and ask it privately, but then they opened

747
00:39:10,280 --> 00:39:12,640
Speaker 21: the floor to questions and I wasn't sure.

748
00:39:12,719 --> 00:39:15,280
Speaker 11: You know, a lot of these really high profile guests don't.

749
00:39:15,120 --> 00:39:18,359
Speaker 21: Stick around for the reception afterwards, so I just took

750
00:39:18,400 --> 00:39:21,360
Speaker 21: the opportunity to ask it publicly. It wasn't my intent

751
00:39:21,600 --> 00:39:26,480
Speaker 21: to create this big kerfuffle on the internet, but you know,

752
00:39:27,280 --> 00:39:29,440
Speaker 21: and that's why I kind of laugh about it, because

753
00:39:30,719 --> 00:39:32,640
Speaker 21: you know, all I was trying to find out was

754
00:39:32,880 --> 00:39:37,000
Speaker 21: is the the that Tulsi Gabbert has released these emails?

755
00:39:37,560 --> 00:39:43,560
Speaker 21: Are you know, Admiral Rogers telling the Toomy and Clapper

756
00:39:43,880 --> 00:39:47,440
Speaker 21: and Brennan. I'm not comfortable with signing off on this

757
00:39:48,040 --> 00:39:51,320
Speaker 21: ICA because there's nothing in the reporting that supports some

758
00:39:51,400 --> 00:39:53,719
Speaker 21: of the things you guys are saying. And he says,

759
00:39:53,920 --> 00:39:55,799
Speaker 21: I'm not going to sign it, my people aren't going

760
00:39:55,840 --> 00:40:00,759
Speaker 21: to sign it, and you know, and and so it's

761
00:40:00,960 --> 00:40:05,400
Speaker 21: very telling that he did not immediately say, you know,

762
00:40:05,640 --> 00:40:06,080
Speaker 21: you don't know what.

763
00:40:06,120 --> 00:40:08,520
Speaker 11: You're talking about. He just basically went after why I

764
00:40:08,600 --> 00:40:08,879
Speaker 11: was there?

765
00:40:10,200 --> 00:40:10,680
Speaker 3: Real quick?

766
00:40:10,719 --> 00:40:12,400
Speaker 1: If you can the ICA for when home is the

767
00:40:12,440 --> 00:40:15,680
Speaker 1: Intelligence Community assessment which was used at Barack Obama said

768
00:40:15,719 --> 00:40:19,239
Speaker 1: go back and change it, which is just literally ridiculous,

769
00:40:20,200 --> 00:40:23,920
Speaker 1: real quick? Should he be charged with one line to Congress?

770
00:40:24,000 --> 00:40:25,880
Speaker 1: Is there anything else he can be charged with? Can

771
00:40:25,920 --> 00:40:27,400
Speaker 1: you do that in thirty seconds? For me?

772
00:40:27,920 --> 00:40:30,040
Speaker 11: I don't know what you can charge him with.

773
00:40:30,280 --> 00:40:32,000
Speaker 21: I don't think you can charge him with treason because

774
00:40:32,040 --> 00:40:33,840
Speaker 21: it has to be on behalf of another government or

775
00:40:33,880 --> 00:40:36,520
Speaker 21: to the benefit of another government. I think that they

776
00:40:36,640 --> 00:40:43,040
Speaker 21: may pursue seditious conspiracy charges because clearly there was an

777
00:40:43,040 --> 00:40:47,800
Speaker 21: atmosphere of sedition against Trump. And you know, I'm not

778
00:40:48,080 --> 00:40:52,040
Speaker 21: convinced that Obama said go back and change the ICA.

779
00:40:52,640 --> 00:40:56,960
Speaker 21: The first ICA was a cyber ica only about Russian

780
00:40:57,040 --> 00:40:59,759
Speaker 21: hacking the election, and the second ICA was more of

781
00:40:59,800 --> 00:41:03,200
Speaker 21: a wholesome intelligence community assessment of and I think that

782
00:41:03,320 --> 00:41:07,600
Speaker 21: that was really at the request of Brennan and Komi

783
00:41:08,239 --> 00:41:10,719
Speaker 21: because they wanted to lay the record down that the

784
00:41:10,800 --> 00:41:12,080
Speaker 21: Russians had influenced the election.

785
00:41:13,120 --> 00:41:16,920
Speaker 1: Well, it's fascinating stuff. I'm grateful to you for you

786
00:41:17,120 --> 00:41:19,320
Speaker 1: going and confront of me. I'd say having the kahonas

787
00:41:19,360 --> 00:41:20,880
Speaker 1: to do it. I know you have the kahona you

788
00:41:21,080 --> 00:41:22,319
Speaker 1: did a longtime Army guy.

789
00:41:22,640 --> 00:41:23,480
Speaker 3: I'll give you this tip.

790
00:41:23,520 --> 00:41:26,560
Speaker 1: You're gonna have to watch Friday Night, Thomas, because I've

791
00:41:26,600 --> 00:41:29,600
Speaker 1: got my other longtime Army guy who was an intelligence

792
00:41:29,640 --> 00:41:32,520
Speaker 1: operative specialized in interrogation as well, and he's a body

793
00:41:32,600 --> 00:41:33,320
Speaker 1: language expert.

794
00:41:33,560 --> 00:41:35,080
Speaker 3: We do body language every day.

795
00:41:35,320 --> 00:41:37,960
Speaker 1: We're gonna do the body language of Brennan both squirming

796
00:41:38,040 --> 00:41:40,920
Speaker 1: in the chair and pointing his finger at you. So

797
00:41:41,040 --> 00:41:43,719
Speaker 1: that should be fun. We'll do that Friday night, Thomas, specially.

798
00:41:43,800 --> 00:41:45,880
Speaker 1: As always, thank you, my friend.

799
00:41:46,480 --> 00:41:48,440
Speaker 11: No, thank you ether, thank you, sir, all right, I

800
00:41:48,480 --> 00:41:48,960
Speaker 11: have a good night.

801
00:41:49,000 --> 00:41:52,600
Speaker 3: Absolutely you two. All right, folks, we'll keep an eye

802
00:41:52,640 --> 00:41:52,840
Speaker 3: on that.

803
00:41:52,960 --> 00:41:55,160
Speaker 1: Of all the cell phone providers out there, only one

804
00:41:55,239 --> 00:41:57,680
Speaker 1: stands for freedom, and that, of course, is Patriot Mobile.

805
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Speaker 1: Over twelve years, Patriot Mobile has fought for our rights

806
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Speaker 1: while offering exceptional nationwide service across all three major networks.

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Speaker 1: Join hundreds of thousands of Americans supporting causes they believe in.

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810
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811
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Speaker 1: to seven to two Patriot or visit Patriotmobile dot com,

812
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Speaker 1: forward slash rav use the promo code RAV for a

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Speaker 1: free months of service. Again nine to seven to two Patriot.

814
00:42:27,160 --> 00:42:28,680
Speaker 1: Tell them Grant Stinchfield sent you.

815
00:42:29,560 --> 00:42:33,279
Speaker 3: All right. Do you feel pain all over? There is

816
00:42:33,320 --> 00:42:44,280
Speaker 3: a solution next, flks.

817
00:42:44,280 --> 00:42:46,799
Speaker 1: There's nothing worse than having pain all over, like even

818
00:42:46,880 --> 00:42:47,879
Speaker 1: run over by a truck.

819
00:42:48,000 --> 00:42:48,320
Speaker 3: Watch this.

820
00:42:49,640 --> 00:42:54,880
Speaker 22: I have Ellers danloads, which is a rare connective tissue disorder.

821
00:42:55,160 --> 00:42:59,879
Speaker 22: I remember waking up in the morning and everything hurt.

822
00:43:00,480 --> 00:43:02,320
Speaker 22: There wasn't a part of me that didn't hurt, and

823
00:43:03,040 --> 00:43:05,320
Speaker 22: I cried out to God and I said.

824
00:43:05,840 --> 00:43:07,880
Speaker 12: Lord, is this going to be the rest of my life?

825
00:43:08,400 --> 00:43:12,240
Speaker 22: I was watching Wayne Allen and he talked about energized Health,

826
00:43:12,440 --> 00:43:15,319
Speaker 22: and I thought, where do I have to this. I've

827
00:43:15,400 --> 00:43:19,839
Speaker 22: gone from taking three narcotic pain medications in the last

828
00:43:19,880 --> 00:43:23,560
Speaker 22: three weeks, I've taken zero. Thank you, John and Chelsea.

829
00:43:23,960 --> 00:43:27,080
Speaker 22: This program is absolutely changing my life.

830
00:43:29,200 --> 00:43:32,240
Speaker 1: Well, she's talking about John and Chelsea Jubilee, the founders

831
00:43:32,280 --> 00:43:35,560
Speaker 1: of Energized Health, which is literally changing people's lives, including

832
00:43:35,600 --> 00:43:37,600
Speaker 1: my own. I keep telling you I lost fifteen pounds

833
00:43:37,640 --> 00:43:40,160
Speaker 1: in two weeks on the Energized Health Protocol and have

834
00:43:40,280 --> 00:43:40,919
Speaker 1: kept it off.

835
00:43:41,440 --> 00:43:46,040
Speaker 3: John Jubilee, welcome back to the show. Be here.

836
00:43:46,320 --> 00:43:48,719
Speaker 23: Wow, come on, that's an awesome testimony.

837
00:43:48,920 --> 00:43:49,000
Speaker 17: Right.

838
00:43:49,080 --> 00:43:54,400
Speaker 23: Can you imagine Grant being on three narcotic prescription narcotic

839
00:43:54,480 --> 00:43:57,600
Speaker 23: how much pain you have to be in and go

840
00:43:57,760 --> 00:44:00,920
Speaker 23: from all that pain to being pain free with nomads?

841
00:44:01,760 --> 00:44:02,120
Speaker 3: All right?

842
00:44:02,239 --> 00:44:05,920
Speaker 1: And so her story is not totally unique, John, You've

843
00:44:06,000 --> 00:44:08,240
Speaker 1: got a lot of stories like this as a result

844
00:44:08,520 --> 00:44:10,080
Speaker 1: of the Energized Health Protocol.

845
00:44:11,000 --> 00:44:11,440
Speaker 3: Oh, it is.

846
00:44:11,520 --> 00:44:13,959
Speaker 23: And you know, and I want people to think about

847
00:44:14,000 --> 00:44:15,839
Speaker 23: this for a moment now. Most people have probably never

848
00:44:16,000 --> 00:44:20,000
Speaker 23: heard of that disorder. It's very rare, but it's on

849
00:44:20,120 --> 00:44:23,880
Speaker 23: the autoimmune list. And you may have heard of rheumatoried

850
00:44:23,960 --> 00:44:29,080
Speaker 23: arthritis that's an autoimmune disorder, or hashimotos But anything in

851
00:44:29,200 --> 00:44:34,480
Speaker 23: the autoimmune we reverse it. And Grant ninety nine percent

852
00:44:34,520 --> 00:44:38,200
Speaker 23: of people their doctor has told them you cannot reverse

853
00:44:38,320 --> 00:44:41,200
Speaker 23: an autoimmune disorder. You can just deal with the pain,

854
00:44:41,840 --> 00:44:45,320
Speaker 23: deal with the symptoms, but you're never going to reverse it.

855
00:44:45,960 --> 00:44:48,600
Speaker 23: But I want to say something on behalf of doctors though.

856
00:44:48,680 --> 00:44:51,920
Speaker 23: We have hundreds of doctors who have become our client Grant,

857
00:44:52,640 --> 00:44:56,160
Speaker 23: and those doctors over all the years, many of them

858
00:44:56,200 --> 00:44:59,800
Speaker 23: have become my friend, and they say to me, John,

859
00:45:00,239 --> 00:45:03,160
Speaker 23: this is what we should have learned in medical school.

860
00:45:03,760 --> 00:45:06,440
Speaker 23: They should be teaching going to the root cause, like

861
00:45:06,560 --> 00:45:10,719
Speaker 23: you do, pushing out inflammation, pushing out toxins. You're going

862
00:45:10,800 --> 00:45:13,719
Speaker 23: to the root cause. I wish I would have learned

863
00:45:13,760 --> 00:45:14,880
Speaker 23: this in medical school.

864
00:45:15,680 --> 00:45:16,480
Speaker 3: You know, it's amazing.

865
00:45:16,560 --> 00:45:19,680
Speaker 1: So you're not just talking about losing body fat, right,

866
00:45:20,440 --> 00:45:24,040
Speaker 1: you talk about losing pain in your joints, which is amazing.

867
00:45:24,080 --> 00:45:28,560
Speaker 1: You talk about is autoimmune disorders. You mentioned arthritis. I

868
00:45:28,680 --> 00:45:31,520
Speaker 1: imagine this helps with people suffering from that too, John.

869
00:45:32,160 --> 00:45:36,960
Speaker 23: Well, anyone that has arthritis, if you have joint pain, Grant,

870
00:45:37,239 --> 00:45:39,200
Speaker 23: I'm going to raise my hand here for people to

871
00:45:39,320 --> 00:45:42,440
Speaker 23: let them know that when I did this twenty eight

872
00:45:42,600 --> 00:45:46,240
Speaker 23: years ago, Grant, I didn't care one bit about losing

873
00:45:46,840 --> 00:45:49,919
Speaker 23: any fat. Now I had fact to lose, by the way,

874
00:45:50,239 --> 00:45:52,920
Speaker 23: and I did lose about forty pounds of fat. So

875
00:45:53,040 --> 00:45:56,560
Speaker 23: I did lose fat, but I was not goal set

876
00:45:56,760 --> 00:45:59,480
Speaker 23: on losing the fat. All I cared about, Grant, is

877
00:45:59,520 --> 00:46:03,040
Speaker 23: I wanted to feel better. I was in pain. Every

878
00:46:03,160 --> 00:46:05,400
Speaker 23: step of my life was a step of pain. I

879
00:46:05,560 --> 00:46:08,160
Speaker 23: was bone on bone of both of my knees. I

880
00:46:08,280 --> 00:46:10,719
Speaker 23: have high blood pressure, I had hypertension, and that just

881
00:46:10,880 --> 00:46:13,520
Speaker 23: sucks the energy out of a man or a woman.

882
00:46:14,160 --> 00:46:16,359
Speaker 23: All I cared about, Grant was could I feel better?

883
00:46:16,760 --> 00:46:17,800
Speaker 3: And it just so happened.

884
00:46:17,840 --> 00:46:20,319
Speaker 23: Not only did I feel better, but I did lose

885
00:46:20,360 --> 00:46:22,239
Speaker 23: ten inches in my waist, I gained a lot of

886
00:46:22,280 --> 00:46:25,120
Speaker 23: muscle and hydration, and I did change my appearance.

887
00:46:26,280 --> 00:46:29,640
Speaker 1: You got a ninety nine percent plus success rate a

888
00:46:29,719 --> 00:46:32,239
Speaker 1: money back guarantee, John, I'm gonna tell people how they

889
00:46:32,280 --> 00:46:33,120
Speaker 1: can get in touch.

890
00:46:32,960 --> 00:46:36,040
Speaker 3: With you and your team over at Energized Health.

891
00:46:36,080 --> 00:46:39,000
Speaker 1: So folks, if you've been stuck in the cycle of dieting,

892
00:46:39,600 --> 00:46:42,719
Speaker 1: gaining and feeling frustrated, it is time for a new path.

893
00:46:42,840 --> 00:46:43,520
Speaker 3: Do what I did.

894
00:46:43,920 --> 00:46:47,799
Speaker 1: Go to energizedhealth dot com. Watch the free masterclass there.

895
00:46:48,239 --> 00:46:52,360
Speaker 1: Learn how cellular hydration can help you lose fat, tighten

896
00:46:52,440 --> 00:46:56,399
Speaker 1: your skin, reset your metabolism for good, and of course

897
00:46:56,520 --> 00:47:02,799
Speaker 1: all that pain goes away Energized Health. That's energizedhealth dot com.

898
00:47:03,600 --> 00:47:13,040
Speaker 1: All right, we're back with a few final thoughts, folks.

899
00:47:13,080 --> 00:47:16,880
Speaker 1: With every success that President Trump has, every failure in California,

900
00:47:16,920 --> 00:47:19,759
Speaker 1: Gavenussom is getting desperate and then he comes up with

901
00:47:19,920 --> 00:47:20,719
Speaker 1: doozies like this.

902
00:47:21,800 --> 00:47:26,920
Speaker 3: Nothing I dislike more than the politician that sits there

903
00:47:27,080 --> 00:47:28,879
Speaker 3: and lies to you and we all just sit there,

904
00:47:28,960 --> 00:47:30,680
Speaker 3: roll in our eyes. Go and give me a break,

905
00:47:33,360 --> 00:47:37,320
Speaker 3: Give me a break like that Gavin Newsome, He just

906
00:47:37,440 --> 00:47:37,880
Speaker 3: lied to you.

907
00:47:38,320 --> 00:47:41,040
Speaker 1: All he does is lie. Remember covid'll kill you. Don't

908
00:47:41,080 --> 00:47:42,759
Speaker 1: go out in public. Oh, let's go to the French

909
00:47:42,840 --> 00:47:45,520
Speaker 1: laundry and have a wild party. That guy's a piece

910
00:47:45,560 --> 00:47:48,960
Speaker 1: of work man, he really is. Stinchfield's army rolls. We

911
00:47:49,000 --> 00:47:51,640
Speaker 1: will see you back here tomorrow night. Actually, special election

912
00:47:51,760 --> 00:47:54,040
Speaker 1: night coverage with Steve Bannon, it'll be