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<v Speaker 1>It's Nightside with Dan Ray. I'm Deli Fleas Boston Video.

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<v Speaker 2>Welcome back everyone as we head into our ten o'clock

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<v Speaker 2>hour here on Tuesday night, the twenty ninth of October.

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<v Speaker 3>My name is Dan Ray. As we move our way towards.

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<v Speaker 2>Midnight, I'm delighted to welcome back a very important figure

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<v Speaker 2>at this time of the year every quadrennial, but he's

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<v Speaker 2>an important figure throughout all the time as far as

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<v Speaker 2>I'm concerned, Suffolk University poster Spencer Kimball, who's developed really

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<v Speaker 2>quite a reputation.

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<v Speaker 3>For Suffolk University with the polls that he does for

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<v Speaker 3>so many clients. Spencer Kimball, welcome back to Nightside, Dan.

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<v Speaker 4>And thanks again for having me as always absolutely so.

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<v Speaker 2>Tell us how many different You don't have to give

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<v Speaker 2>me the names of all the clients, but Suffolk you

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<v Speaker 2>do a lot of polling, not only for Suffolk but

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<v Speaker 2>also for other institutions and corporations.

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<v Speaker 4>Correct, well, Dan, you got me backwards. Remember I went

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<v Speaker 4>to Suffolk, studied with Dave and now I'm over at Emerson.

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<v Speaker 5>But we run.

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<v Speaker 3>Yeah, you know, I apologie.

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<v Speaker 2>First of all, I totally apologize. I totally apologize. I

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<v Speaker 2>was doing a couple of things. It's Emerson College. My mistake,

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<v Speaker 2>that is, that's a mortal sin here to mix you up.

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<v Speaker 4>Now there on the other side of a common we're friends.

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<v Speaker 2>No, no, no, no, no, I totally get so tell

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<v Speaker 2>us about Emerson, because what I meant is that that

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<v Speaker 2>I see all the national polls, and there's a couple

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<v Speaker 2>of other universities around the country. But both Dave Pale

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<v Speaker 2>Loogus at Suffolk and you at Emerson, and thank you

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<v Speaker 2>for being a very gentle correction. You should have yelled

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<v Speaker 2>at me because I totally blanked out, and I apologize

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<v Speaker 2>for that. I'm there trying to do three or four

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<v Speaker 2>things simultaneously here and I sometimes have a tough time

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<v Speaker 2>doing one one thing, well, signed one thing.

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<v Speaker 3>Well, so who else? I mean? Why?

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<v Speaker 2>How has Suffolk gotten How has Emerson gotten such a

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<v Speaker 2>really great reputation amongst the polling community.

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<v Speaker 4>Well, first, you know, it's great to hear that reputation

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<v Speaker 4>exists within your space, and that's what we try to

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<v Speaker 4>work to achieve. What essentially helped us create the space

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<v Speaker 4>is innovation in data collection. And it's not the most

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<v Speaker 4>exciting thing to talk about. But if we just think

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<v Speaker 4>about the ways we communicate today the way we communicated

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<v Speaker 4>forty years ago. It's really leaps and bounds in lifestyle

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<v Speaker 4>differences and in communication. So what we've done at Emerson

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<v Speaker 4>is we study communication and we look at, well, what's

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<v Speaker 4>the way people are communicating. In about ten twelve years ago,

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<v Speaker 4>we kind of restarted the survey and polling program and

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<v Speaker 4>used new ways of data collection to kind of test

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<v Speaker 4>it out in the academic world. So it's happening in industry,

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<v Speaker 4>but in the universities and colleges, we were generally collecting

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<v Speaker 4>data using live operators and we'd call people up and

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<v Speaker 4>ask them their questions. But as technology has evolved, what

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<v Speaker 4>we're doing today is text messaging people. We're sending out emails.

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<v Speaker 4>We use automated phone calls where people don't have to

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<v Speaker 4>they can use their keypads to answer surveys, and they

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<v Speaker 4>can even enter into panels. And these innovations is kind

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<v Speaker 4>of leading the forefront of the survey industry, and that's

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<v Speaker 4>what gives us these opportunities. And the pre election polling

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<v Speaker 4>for us is the canary and the coal mine. We

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<v Speaker 4>get to test out these different methodologies. You know, is

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<v Speaker 4>there a difference between a text message poll and an

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<v Speaker 4>online poll, or what about a survey that has people

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<v Speaker 4>opt in to participate in it. You know, anybody can

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<v Speaker 4>come take this survey at some of these groups, how

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<v Speaker 4>do those work? And the elections give us a chance

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<v Speaker 4>to kind of test out what methods are better, and

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<v Speaker 4>then we use that information to do other survey work,

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<v Speaker 4>which is a much larger industry. And I think that's

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<v Speaker 4>what you're alluding to with some of those other clients,

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<v Speaker 4>and that can range from the San Francisco Police Department,

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<v Speaker 4>who we currently are just finishing a study for, to

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<v Speaker 4>Common Good Index, to different associations. We do a holiday

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<v Speaker 4>study on footwear. We do a lot of health communication

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<v Speaker 4>on vaccines and bird flu and other areas that traditionally

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<v Speaker 4>may have been very expensive to conduct this type of research.

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<v Speaker 4>But because technology has evolved and we don't have to

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<v Speaker 4>pay operators to call people, we are able to bring

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<v Speaker 4>down the cost of some of the data collection, which

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<v Speaker 4>gives us really valuable information. And in some areas, obviously,

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<v Speaker 4>election polls have value, but some of the areas in

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<v Speaker 4>health communication and other market research also has value as well.

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<v Speaker 2>So let me ask you this question, Okay, In the

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<v Speaker 2>old days you would rely upon and maybe these were

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<v Speaker 2>days even before when you were involved. In the old days,

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<v Speaker 2>posters rely upon the white pages in the phone book

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<v Speaker 2>and they would they would, that's how they would find

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<v Speaker 2>people's numbers. Now, how do you find people's cell phone numbers?

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<v Speaker 2>There's no I'm sure there's somewhere that my cell phone

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<v Speaker 2>number is listed, but it's not available to you as

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<v Speaker 2>a polster, or maybe it is.

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<v Speaker 4>Well, Dan, that too has evolved over so telephones become

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<v Speaker 4>the major mode of data collection starting in the nineteen seventies.

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<v Speaker 4>And you know at and t let your fingers do

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<v Speaker 4>the you know talking, well anyways, the walking, let your

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<v Speaker 4>fingers do the walking, and so, uh, you can see,

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<v Speaker 4>telephones are there, and polsters were using something called random

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<v Speaker 4>digit dialing where they would create root numbers based on

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<v Speaker 4>area codes and then you'd have roots and then a

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<v Speaker 4>random number. And what happens in random digit dialing is

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<v Speaker 4>everybody could be included. So if you're a doctor and

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<v Speaker 4>you had an unlisted number, well, random digit dialing would.

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<v Speaker 3>Find that number.

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<v Speaker 4>Now, in the era of landlines, and now you got

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<v Speaker 4>to remember, you also were calling libraries and hospitals and

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<v Speaker 4>other random numbers that you have to be very careful about,

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<v Speaker 4>you know, calling and soliciting that process became expensive, so

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<v Speaker 4>they moved to using registered voter lists or registered based

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<v Speaker 4>sampling back in like the nineteen nineties and into the

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<v Speaker 4>the beginning of this of this century, where I know

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<v Speaker 4>you think that like you know, you register to vote

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<v Speaker 4>and there's your name and your address, but there's a

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<v Speaker 4>lot of companies out there that append the data back

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<v Speaker 4>to you. So we do have a database of you know,

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<v Speaker 4>I think it's well over two hundred and seventy million

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<v Speaker 4>points of contact with I think about one hundred and

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<v Speaker 4>forty million cell phones, one hundred and thirty million cell phones.

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<v Speaker 4>So we've got a large database to pull from. And

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<v Speaker 4>that's where so.

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<v Speaker 2>I'm not doing when you're going for cell phone because

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<v Speaker 2>more people, more and more people every year have got

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<v Speaker 2>rid of the landline and now we're cell phone dependent.

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<v Speaker 2>And you're saying that when you want to call someone

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<v Speaker 2>that fits my profile, you you you're not random dialing

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<v Speaker 2>and saying to the person, well, how old are you,

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<v Speaker 2>what's your ethnicity? Are you a Democrat, Republican, unenrolled, et cetera.

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<v Speaker 2>You have an idea when you when that number dials, Uh,

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<v Speaker 2>who that person is?

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<v Speaker 3>Who's going to pick up that phone?

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<v Speaker 5>Yeah.

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<v Speaker 4>In fact, when you get these texts, when you get

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<v Speaker 4>the text message, it's going to say, hi Dan, will

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<v Speaker 4>you take the survey? It's personalized and that's how that's

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<v Speaker 4>how much we know who's taking it now. To me,

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<v Speaker 4>there's an issue with personalizing it too much because there's

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<v Speaker 4>you want to be anonymous and confidential. There's the reason

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<v Speaker 4>why we have a secret ballot in this country. And

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<v Speaker 4>you know, the survey is intended to be anonymous, and

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<v Speaker 4>so we sometimes yeah, and to help keep people honest,

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<v Speaker 4>and you know, we think about are you comfortable if

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<v Speaker 4>somebody calls you up and says, you know, hi Dan?

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<v Speaker 4>You know the suspense and you're like, who's Spence? And

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<v Speaker 4>how do you know my name? So as to if

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<v Speaker 4>you get a text message from Emerson College that says, hey,

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<v Speaker 4>you want to take an Emerson College poll. As you mentioned,

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<v Speaker 4>a lot of people have heard of the Emerson College

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<v Speaker 4>poll and they might be willing to participate and share

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<v Speaker 4>their opinions with us for us to be able to

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<v Speaker 4>represent public opinion.

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<v Speaker 3>My guest is Spencer Kimball.

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<v Speaker 2>He is the polling guru if you will, for Emerson

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<v Speaker 2>College has done a great job this. I've never really

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<v Speaker 2>had a chance to drill down and understand this, so

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<v Speaker 2>I'm learning something. I hope some of you are as well.

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<v Speaker 2>When I get back, I'm going to tell you an

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<v Speaker 2>anonymous text that I got tonight. I don't think it

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<v Speaker 2>was directed at me, but you're going to break it

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<v Speaker 2>down for me when I explain to see I think

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<v Speaker 2>you'll get a kick out of it, and then we

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<v Speaker 2>will talk, assuming that you're willing to talk about what

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<v Speaker 2>you're seeing in the polls, in your polls and other polls.

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<v Speaker 2>As we are now really less than a week away

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<v Speaker 2>from November fifth, something that many of us have had

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<v Speaker 2>marked on our calendar for years, and now it is.

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<v Speaker 2>It's almost here. So I'm excited about it. I want

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<v Speaker 2>to talk with Spencer about it, and I hope some

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<v Speaker 2>of you might want to call and ask Spencer a

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<v Speaker 2>question if you'd like.

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<v Speaker 3>Feel free.

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<v Speaker 2>The number that we give out it's not my cell

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<v Speaker 2>phone number, it's the WBC call line six one seven,

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<v Speaker 2>two five four ten thirty six one seven nine three

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<v Speaker 2>one ten thirty Spencer. I could talk with you about

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<v Speaker 2>this stuff all night. I don't want to have used

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<v Speaker 2>your time. Just tell my producer what your time living is.

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<v Speaker 2>If if I if we're done at ten thirty and

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<v Speaker 2>you've got something you got to do in the.

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<v Speaker 3>Morning, please I'll uh if you can.

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<v Speaker 2>Stay a little later. I'd love to have you stay

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<v Speaker 2>a little later. But that's your call, and just talk

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<v Speaker 2>to my producer. The other Dan on the board tonight,

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<v Speaker 2>Rob is off, So Dan is our other producer tonight,

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<v Speaker 2>be back with your phone calls along with Spencer Kimball,

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<v Speaker 2>Emerson University pollster based here in Boston, Massachusetts, but with

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<v Speaker 2>a very long reach around the country. Back on Nightside

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<v Speaker 2>after this.

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<v Speaker 1>Now back to Dan Ray live from the Window World

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<v Speaker 1>night Side Studios on WBZ News Radio.

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<v Speaker 3>I'm talking with my friend Spencer Kimball. He is a pollster.

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<v Speaker 2>He and Dave Paleo Logus and John Zogby, I think

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<v Speaker 2>are the three best posters in the country.

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<v Speaker 3>We'll have Dave with us tomorrow night. We had Spencer

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<v Speaker 3>with us a week ago. Dave was with us as well.

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<v Speaker 2>Spencer's I get this text tonight, okay, and I want

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<v Speaker 2>you to interpret.

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<v Speaker 3>I think you're gonna get get it. Get a kick

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<v Speaker 3>out of this here ready.

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<v Speaker 2>No, No one should know my cell phone number except

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<v Speaker 2>people like you, friends of mine, or family members, et cetera.

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<v Speaker 3>Okay, so I get a text earlier this evening.

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<v Speaker 2>Hi Stephen. My name is not Stephen. Okay, my middle

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<v Speaker 2>name is not Stephen. Hi Stephen. I'm Matt, a volunteer

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<v Speaker 2>with Swing Left. Our call oween phone Bank to call

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<v Speaker 2>voters in Wisconsin with special guests including Katherine Hahn, Natasha Rothwell,

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<v Speaker 2>Busy Phillips, and Moore will be on Wednesday, October thirtieth

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<v Speaker 2>at seven pm Eastern time. We'd love to see you there.

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<v Speaker 2>Will you join us?

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<v Speaker 3>Now?

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<v Speaker 2>You're you're more hip than I am, Spencer, but I

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<v Speaker 2>have no idea. Who's Katherine Hahn? Do you have an idea?

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<v Speaker 4>No? Unless they're running for office? Not my department. I

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<v Speaker 4>have people I work with.

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<v Speaker 3>An actress, Dan telling me?

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<v Speaker 4>Is it?

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<v Speaker 3>Dan's telling me an actress? Okay? Dan? What about Natasha Rothwell?

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<v Speaker 3>That one? He doesn't know? What about Busy Phillips? Okay?

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<v Speaker 2>So we got Dan the producers one out of three?

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<v Speaker 2>So will you join us at rapid recruit dot Org.

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<v Speaker 2>I have no idea what that is, but I assume

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<v Speaker 2>since it's entitled Swing Left. It's probably not my cup

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<v Speaker 2>of tea politically, but here's how I answered this. Okay,

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<v Speaker 2>I hope I haven't broken any federal law here, but

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<v Speaker 2>your confession is good for the soul. I responded, I'll

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<v Speaker 2>go to Wisconsin to help. I have lots of cash

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<v Speaker 2>to bring with me.

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<v Speaker 4>Out to the Badger State.

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<v Speaker 3>I hope they.

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<v Speaker 2>Don't get too excited or something that Steven is going

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<v Speaker 2>to actually go there. But I thought to myself, I'm

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<v Speaker 2>receiving this is from area Coach six 't eighty one,

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<v Speaker 2>which I checked out, which is actually West Virginia. So

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<v Speaker 2>there's a phone bank in West Virginia that's called Swing

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<v Speaker 2>Left that's going to be calling people in Wisconsin. It's

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<v Speaker 2>just the way we communicate these days is fascinating.

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<v Speaker 3>So the question, then, and the reason I told you

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<v Speaker 3>this story, is if this had been.

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<v Speaker 2>As survey, it said, Hi, Steven, you know, somehow, some

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<v Speaker 2>way this my number is associated with with someone named

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<v Speaker 2>Stephen I have known, and by the way, I've had

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<v Speaker 2>this phone for a long time. So if this was

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<v Speaker 2>a poll, I could answer anything. I could tell them

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<v Speaker 2>that I wanted, you know, Trotsky or Lemon or Lenin

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<v Speaker 2>to be president, it wouldn't matter. But how tough is

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<v Speaker 2>it as a polster whose reputation depends on the accuracy

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<v Speaker 2>of the polls you conduct to make sure you know

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<v Speaker 2>who you're talking to and that you have some idea

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<v Speaker 2>about what their background is.

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<v Speaker 4>Well, you know, that's the challenge and why some folks

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<v Speaker 4>question not using live operators, because with a live operator,

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<v Speaker 4>you know that you're talking to somebody. You know it's

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<v Speaker 4>not a child. You know, you could ask them their

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<v Speaker 4>name to verify it, and some posters do that in

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<v Speaker 4>these news systems. And where the future is going to

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<v Speaker 4>go is within these panels where people have opted in

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<v Speaker 4>and they're getting rewarded to take the surveys. We're already

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<v Speaker 4>seeing it to some degree today, but in you know

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<v Speaker 4>the next three to five years, it'll be even bigger

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<v Speaker 4>business in these panels. And in those cases, those folks

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<v Speaker 4>you'll already have that demographic data on them. Obviously, they

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<v Speaker 4>can still not tell you the truth about their opinions,

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<v Speaker 4>or their opinions can also change. You know, you can

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<v Speaker 4>wake up happy and you know how things going great,

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<v Speaker 4>and by four o'clock you're like, was the tough day?

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<v Speaker 4>The opinions change and but with that, we do have

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<v Speaker 4>a few ways of testing within the survey of if

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<v Speaker 4>somebody is just like flicking through it and not pressing

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<v Speaker 4>or randomly you know, answering questions or UH has to make.

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<v Speaker 3>Sure, okay, speczer.

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<v Speaker 2>Do you over sample so that if you're looking to

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<v Speaker 2>get a poll, let's say a national poll of one

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<v Speaker 2>thousand legitimate voters, which are a portion between fifty states

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<v Speaker 2>and balance between men and women, Republicans, Democrats, independence and

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<v Speaker 2>all of that, do you over sample so you'll have

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<v Speaker 2>fifteen hundred or you'll have five thousand, and you can

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<v Speaker 2>you can sort of prone out the ones that you

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<v Speaker 2>think are responsive and.

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<v Speaker 3>Legitimate or or can you not do that at this point?

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<v Speaker 4>No, you certainly, you certainly go through that process. You know,

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<v Speaker 4>for example, you can see how long it took the

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<v Speaker 4>person to take the survey, somebody who took it within

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<v Speaker 4>thirty seconds. It raises an eyebrow. Those there's some mechanics

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<v Speaker 4>that we can see, you know, behind the curtain that

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<v Speaker 4>allows us to know where they are are and other

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<v Speaker 4>bits of information there. So there are things. But yes,

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<v Speaker 4>because of the way we collect the data, the cost

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<v Speaker 4>per collection is fairly low compared to live operator data collection.

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<v Speaker 4>So for live operators, hard to throw away data that's

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<v Speaker 4>costing maybe thirty five to forty dollars a complete. In

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<v Speaker 4>my world that's costing maybe fixed to eight dollars a complete.

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<v Speaker 4>So you know, still it hard to throw that away.

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<v Speaker 4>But we have a little bit more room. And so

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<v Speaker 4>to your point, we do scrub out. Not everybody who

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<v Speaker 4>takes the survey has the best of intentions, and we

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<v Speaker 4>have those those catches throughout the honey pots throughout the

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<v Speaker 4>survey to try to catch those folks.

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<v Speaker 3>Do you think that polls today are more accurate, less accurate,

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<v Speaker 3>or similar in terms of their accuracy to prior elections? Obviously,

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<v Speaker 3>as the technology changes, you'd like to think that the

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<v Speaker 3>technology creates more accurate polls. I mean, that's what the

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<v Speaker 3>goal is. Obviously.

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<v Speaker 2>Do you feel better as these newer, you know, procedures

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<v Speaker 2>are now being implemented, adopted and become really you know

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<v Speaker 2>part of the equation?

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<v Speaker 4>Oh, yes, right, The bottom line is yes, polling is

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<v Speaker 4>getting better. You've got to remember that a survey is

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<v Speaker 4>a range of scores. It's not an exact score, and

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<v Speaker 4>so the key is using a large enough sample, like

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<v Speaker 4>a sample of a thousand people that has a margin

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<v Speaker 4>enviuyer of three, which is like a six point spread. Now, historically, yeah,

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<v Speaker 4>either you know, three points on either side tow it's

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<v Speaker 4>a six point so but historically, like if you go

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<v Speaker 4>back to the famous nineteen thirty six George Gallup poll

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<v Speaker 4>and literary digest having alf land In beating FDR and

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<v Speaker 4>this emerged George Gallup, who had FDR winning that poll

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<v Speaker 4>actually falls outside their margin of error. They had the winner,

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<v Speaker 4>but they didn't have FDR winning by enough. And nineteen

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<v Speaker 4>forty Gallup gets the poll wrong. They actually have Wilkie

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<v Speaker 4>I think winning that election. So the polls aren't you

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<v Speaker 4>know historically nineteen forty eight. You know, they talk about

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<v Speaker 4>the twenty sixteen election and those were some bad polls

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<v Speaker 4>they but in forty eight, we're talking about being off

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<v Speaker 4>by like seventeen points in some states thirty points. Like

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<v Speaker 4>the polling disasters of forty eight were are truly let

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<v Speaker 4>all over. Like just imagine that being off across many

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<v Speaker 4>many states because there was only two or three polsters

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<v Speaker 4>at the time, four polsters. Now there's literally over four

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<v Speaker 4>hundred polsters and it's hard to and to make sense

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<v Speaker 4>of all of that. But the technology improves and the industry.

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<v Speaker 4>Remember we're we're market you know, survey research, market research.

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<v Speaker 4>We do polling as uh, you know, kind of an

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<v Speaker 4>offshoot to the bigger part of the discipline. So and

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<v Speaker 4>it also informs us, as I mentioned earlier, about what

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<v Speaker 4>methods and you know work best in the survey field.

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<v Speaker 4>By having an election, well.

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<v Speaker 2>It's great because you you can look back on, hopefully,

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<v Speaker 2>if not November fifth, November sixth, or November seventh, maybe

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<v Speaker 2>over the latest and say, okay, here's what we projected,

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<v Speaker 2>here's what it worked out to be. And so look

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<v Speaker 2>what I want to do. We've talked theory a lot.

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<v Speaker 2>I want to get to the to the big races

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<v Speaker 2>at hand.

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<v Speaker 5>Uh and right.

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<v Speaker 4>Time, Dann, we're gonna put our audience to sleep talking theory.

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<v Speaker 4>They're gonna be not at all.

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<v Speaker 2>No, I gotta tell you something. I'm fascinated by it.

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<v Speaker 2>And I get people who call all the time.

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<v Speaker 3>I've never been called by a pollster.

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<v Speaker 2>I don't to mean this is fascinating, Okay, yeah, because

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<v Speaker 2>it's great. Well, I really mean that seriously, It's something

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<v Speaker 2>that I read the polls, uh, And I'm always trying

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<v Speaker 2>to see what can I see? What? What little thing

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<v Speaker 2>can I see? I call it a vector? You know what?

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<v Speaker 2>What what way is the wind blowing that I can

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<v Speaker 2>see ahead of time? Uh? And and that's I'm I'm

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<v Speaker 2>sure you know what I'm what I'm referring to when

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<v Speaker 2>I when I speak like that. So, uh, if if

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<v Speaker 2>folks want to call and ask a question about polling

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<v Speaker 2>generally or about the race at hand, uh, they got

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<v Speaker 2>to light it up. Six one, seven, two, five, four,

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<v Speaker 2>ten thirty six one seven, nine three one ten thirty,

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<v Speaker 2>triple eight nine two nine, ten thirty. This again is

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<v Speaker 2>your opportunity to talk to a real, live, legitimate pollster.

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<v Speaker 2>These poles, by the way, folks, have tremendous impact within

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<v Speaker 2>campaigns and within the media at large, because when Emerson

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<v Speaker 2>College puts out a poll, it's red. Believe me, it's red.

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<v Speaker 2>And when Suffolk puts out a poll, it's red. And

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<v Speaker 2>believe me it's red, and it's carried. And there are

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<v Speaker 2>a couple of others around the country that are that

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<v Speaker 2>are that are important as well. But uh, five point

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<v Speaker 2>thirty eight is one that has been very interesting as well.

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<v Speaker 2>Uh I I well, we have much to discuss to discuss.

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<v Speaker 2>We'll be right back on Nightside with Spencer Kimball. If

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<v Speaker 2>you've never been polled, this is your opportunity to actually,

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<v Speaker 2>if not Pole, you can even troll a pollster here. Okay,

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<v Speaker 2>Spencer Kimball of Emerson, I don't want you to do that.

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<v Speaker 2>Back on Nightside right after these few messages and the

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<v Speaker 2>news at the bottom of the hour.

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<v Speaker 1>Night Side with Dan Ray, I'MBZ Boston's News Radio.

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<v Speaker 2>My guest is Spencer Kimball, Emerson college pollster who has

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<v Speaker 2>a national reach. At this point, Emerson is recognized, along

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<v Speaker 2>with Dave Paleo Logus's group at Suffolk, as a significant,

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<v Speaker 2>significant poster on presidential elections and on Senate races. So again, Spencer,

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<v Speaker 2>no one's expecting you to call the election. But what

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<v Speaker 2>are you seeing in the last few weeks? Do you

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<v Speaker 2>think that this election is going to be as close

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<v Speaker 2>as everyone would seem to suggest it is. Do you

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<v Speaker 2>see any movement to.

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<v Speaker 3>Speak of either the vice president or former President Trump?

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<v Speaker 4>Well, yes, that's the exciting week. Next week, this time

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<v Speaker 4>we'll be looking at returns and we will have a

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<v Speaker 4>much better sense obviously what's going on. But when we

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<v Speaker 4>look at you know around the country if we want

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<v Speaker 4>to kind of talk around the horn, if we go

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<v Speaker 4>out west, we see Arizona leaning more Republican. We'll just

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<v Speaker 4>talk presidential politics, but happy to jump into any Senate

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<v Speaker 4>But in the presidential level, Arizona there are eleven electoral votes.

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<v Speaker 4>There's a state that Biden stood to me. What you're

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<v Speaker 4>looking at is like you got to flip a state.

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<v Speaker 4>It's like in basketball, you got to win on the

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<v Speaker 4>other team's home court before the play. You know, it

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<v Speaker 4>becomes a series. So here, Arizona would be a state

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<v Speaker 4>where it looks to be a state Trump's can be

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<v Speaker 4>able to bring back that was part of his coalition

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<v Speaker 4>of twenty sixteen, lost it in twenty twenty by less

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<v Speaker 4>than about three tenths of a point. And out there

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<v Speaker 4>their major issue is immigration. It's like thirty percent. They're

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<v Speaker 4>the only state, really Texas a little high with immigration.

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<v Speaker 4>But yeah, so there's a state there that for Trump.

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<v Speaker 4>Georgia would be another one for Trump that Biden was

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<v Speaker 4>able to take back in twenty twenty by again about

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<v Speaker 4>two to three tenths of a point. We'll see if

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<v Speaker 4>by if Trump is able to hold that one. He

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<v Speaker 4>seems to be getting along well with Governor Kemp, and

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<v Speaker 4>we'll see what the ground game looks like in Georgia.

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<v Speaker 4>And then North Carolina would be a state for Harris

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<v Speaker 4>to take and that would open up a potential Southern

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<v Speaker 4>strategy if the Midwest Wall was to collapse and you know,

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<v Speaker 4>or if a state or two was to drop, particularly

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<v Speaker 4>if you go out to like Wisconsin. The polling is

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<v Speaker 4>generally trending towards Trump out there. Harris had a three

421
00:25:35.640 --> 00:25:39.519
<v Speaker 4>to four point lead. Historically, Wisconsin's been the toughest state

422
00:25:39.559 --> 00:25:42.359
<v Speaker 4>out of the seven for the Polsters. We were off

423
00:25:42.440 --> 00:25:46.079
<v Speaker 4>the most in Wisconsin over the last two cycles and

424
00:25:47.240 --> 00:25:50.119
<v Speaker 4>not really great at improvement. I wish we have done better.

425
00:25:50.359 --> 00:25:54.400
<v Speaker 4>Hopefully this cycle we do and right now we have

426
00:25:54.440 --> 00:25:57.960
<v Speaker 4>it tied leaning towards Trump, so that would be a

427
00:25:58.000 --> 00:26:02.559
<v Speaker 4>pickup state as well. And then you got your Pennsylvania

428
00:26:03.119 --> 00:26:12.039
<v Speaker 4>and Michigan vote looking close. But the general takeaway is

429
00:26:12.799 --> 00:26:18.440
<v Speaker 4>Trump is doing better with men in Harris is generally

430
00:26:18.480 --> 00:26:22.079
<v Speaker 4>doing about the same with women as Biden did with women,

431
00:26:22.640 --> 00:26:26.160
<v Speaker 4>and that kind of will cut across race and ethnicity,

432
00:26:26.759 --> 00:26:31.680
<v Speaker 4>and she does do better than Biden with younger voters,

433
00:26:32.160 --> 00:26:35.119
<v Speaker 4>but we have not seen those folks come to the polls.

434
00:26:35.519 --> 00:26:39.079
<v Speaker 4>So in this early voting, you'll notice that some of

435
00:26:39.119 --> 00:26:42.960
<v Speaker 4>the sites that monitor it, most of the early vote

436
00:26:43.039 --> 00:26:48.279
<v Speaker 4>is older vote. It's very disproportionate towards those over fifty.

437
00:26:48.839 --> 00:26:52.319
<v Speaker 4>And so we'll see if the Democrat young vote comes

438
00:26:52.319 --> 00:26:54.880
<v Speaker 4>out on election day and is able to put her

439
00:26:54.960 --> 00:26:59.160
<v Speaker 4>over the top in some of these key swing states.

440
00:26:58.759 --> 00:27:02.680
<v Speaker 4>But to remember some of these points that I'm talking about,

441
00:27:03.559 --> 00:27:06.319
<v Speaker 4>you know, it's like one eighty thousand votes in Pennsylvania

442
00:27:06.359 --> 00:27:07.960
<v Speaker 4>as a point, so you got to you got to

443
00:27:08.000 --> 00:27:12.000
<v Speaker 4>convince eighty thousand people to shift over if you're up

444
00:27:12.039 --> 00:27:16.319
<v Speaker 4>a point there. So those are you know, points aren't

445
00:27:16.359 --> 00:27:20.640
<v Speaker 4>always the same based on the population of each state.

446
00:27:21.680 --> 00:27:28.160
<v Speaker 2>So this is not twenty twenty, but it is. Trump

447
00:27:28.200 --> 00:27:33.480
<v Speaker 2>has to Trump won those three states the Blue Wall Wisconsin, Michigan,

448
00:27:33.519 --> 00:27:37.240
<v Speaker 2>and Pennsylvania. That's what elected him in twenty sixteen. So

449
00:27:37.319 --> 00:27:42.000
<v Speaker 2>he has to really accomplish, if not all of those states,

450
00:27:42.400 --> 00:27:45.920
<v Speaker 2>at least one of them at a minimum, and maybe

451
00:27:45.920 --> 00:27:51.799
<v Speaker 2>a couple. Because it's every every year is a little different.

452
00:27:51.839 --> 00:27:54.079
<v Speaker 2>I mean, people understand the middle of the country's red,

453
00:27:54.119 --> 00:27:57.519
<v Speaker 2>the coast tend to be blue. We get that, but

454
00:27:57.640 --> 00:28:01.079
<v Speaker 2>This is truly still close a call. Either one of

455
00:28:01.119 --> 00:28:05.480
<v Speaker 2>these candidates could win, okay, by a narrow margin. Does

456
00:28:05.599 --> 00:28:08.960
<v Speaker 2>either have the potential of winning by a decisive margin.

457
00:28:11.039 --> 00:28:15.559
<v Speaker 4>Well, first year earlier point, Trump could lose that blue

458
00:28:15.559 --> 00:28:20.920
<v Speaker 4>wall of Wisconsin, Michigan, Pennsylvania, take back Georgia, Arizona, and

459
00:28:21.000 --> 00:28:26.160
<v Speaker 4>then flip Nevada in New Hampshire and he wins the presidency.

460
00:28:26.440 --> 00:28:29.359
<v Speaker 4>So there's different pathways with polls that are within the

461
00:28:29.359 --> 00:28:34.720
<v Speaker 4>poll's margin of error. Now it looked like there's a

462
00:28:34.720 --> 00:28:37.880
<v Speaker 4>better chance for Trump to have a blowout than for

463
00:28:38.000 --> 00:28:40.880
<v Speaker 4>Harris to have a blowout. And I say that based

464
00:28:40.920 --> 00:28:47.279
<v Speaker 4>on the popular vote. Generally, the conventional wisdom is if

465
00:28:47.319 --> 00:28:51.279
<v Speaker 4>the Republicans, if you know, the Republicans win the popular

466
00:28:51.400 --> 00:28:53.799
<v Speaker 4>vote like bushed it in two thousand and four, the

467
00:28:53.880 --> 00:28:57.039
<v Speaker 4>last Republican to do that. Since I think eighty eight,

468
00:28:58.680 --> 00:29:02.039
<v Speaker 4>the Republicans will win. And it looks on the popular

469
00:29:02.119 --> 00:29:05.759
<v Speaker 4>vote that it could go in either direction. But this

470
00:29:05.880 --> 00:29:08.680
<v Speaker 4>selection is a little bit different in that Harris hasn't

471
00:29:08.720 --> 00:29:12.640
<v Speaker 4>had a full year year and a half campaigning. It's

472
00:29:12.680 --> 00:29:16.359
<v Speaker 4>really only been a couple of months, and so she's

473
00:29:16.920 --> 00:29:21.400
<v Speaker 4>kind of doing okay. Like in our Massachusetts fault. She's

474
00:29:21.680 --> 00:29:24.759
<v Speaker 4>up by twenty three points, which is a solid lead,

475
00:29:25.279 --> 00:29:28.319
<v Speaker 4>but Biden won the state by about thirty three thirty

476
00:29:28.400 --> 00:29:33.319
<v Speaker 4>four points, so there is some melt that we're seeing

477
00:29:33.359 --> 00:29:36.960
<v Speaker 4>same thing in New York. And then we see a

478
00:29:36.960 --> 00:29:39.839
<v Speaker 4>little bit of a gains for Trump in Florida and Texas.

479
00:29:40.359 --> 00:29:43.920
<v Speaker 4>So we're seeing this rising tide, you know, in some

480
00:29:44.039 --> 00:29:46.640
<v Speaker 4>places for Trump and he's a little dropping, but in

481
00:29:46.680 --> 00:29:49.720
<v Speaker 4>the swing states, those are holding more steady because that's

482
00:29:49.720 --> 00:29:53.480
<v Speaker 4>where the money's being spent and the campaigns are being organized.

483
00:29:54.200 --> 00:29:58.880
<v Speaker 6>Yeah, ironically, Harris has much more money available right now.

484
00:29:59.000 --> 00:30:02.079
<v Speaker 6>I mean, she's she's swimming in the money. Trump is

485
00:30:02.119 --> 00:30:05.319
<v Speaker 6>not swimming in the money, at least in the political money.

486
00:30:05.400 --> 00:30:08.559
<v Speaker 6>What about Minnesota. I know that there's been some slippage

487
00:30:08.559 --> 00:30:10.960
<v Speaker 6>in Minnesota for the Democrats, even though Waltz is in

488
00:30:11.039 --> 00:30:11.480
<v Speaker 6>the ballot.

489
00:30:12.720 --> 00:30:16.680
<v Speaker 4>Yeah, to me, that would be hard to imagine Minnesota

490
00:30:16.920 --> 00:30:19.200
<v Speaker 4>being in play with Walls on the ballot. It was

491
00:30:19.279 --> 00:30:22.160
<v Speaker 4>kind of like Tim Kane being in Virginia, and you

492
00:30:22.200 --> 00:30:25.079
<v Speaker 4>know that state got more competitive in twenty sixteen.

493
00:30:25.960 --> 00:30:27.680
<v Speaker 5>We'll see if.

494
00:30:27.759 --> 00:30:30.680
<v Speaker 4>To me, Walls needs to give you Wisconsin if you're

495
00:30:30.680 --> 00:30:33.720
<v Speaker 4>the Democrat because that's your neighboring state. He's the governor

496
00:30:33.759 --> 00:30:35.880
<v Speaker 4>of Minnesota. He should be able to give you Wisconsin.

497
00:30:36.319 --> 00:30:40.119
<v Speaker 4>So Wisconsin's really a toss up, probably leaning towards Trump.

498
00:30:40.960 --> 00:30:45.119
<v Speaker 4>But Minnesota, if that's even in play now, the Democrats

499
00:30:45.119 --> 00:30:49.000
<v Speaker 4>have a real problem because those should in Minnesota, Virginia,

500
00:30:49.119 --> 00:30:55.160
<v Speaker 4>New Hampshire. Some folks think New Mexico those should not be.

501
00:30:55.279 --> 00:30:57.960
<v Speaker 4>But New Mexico I don't think is really swinging at all.

502
00:30:59.000 --> 00:31:01.640
<v Speaker 7>But the other I thought, I thought, I thought I

503
00:31:01.640 --> 00:31:05.079
<v Speaker 7>said some pole that said that Minnesota, uh, at some

504
00:31:05.240 --> 00:31:08.559
<v Speaker 7>point recently was a lot tighter than anyone would have expected,

505
00:31:08.599 --> 00:31:09.799
<v Speaker 7>which caused me.

506
00:31:09.759 --> 00:31:13.880
<v Speaker 4>To say whether yesterday three points.

507
00:31:13.160 --> 00:31:18.519
<v Speaker 2>Yeah, and and whether or not that is evidence that

508
00:31:18.519 --> 00:31:20.839
<v Speaker 2>that maybe Harris made a mistake in not picking the

509
00:31:20.839 --> 00:31:22.599
<v Speaker 2>government of Pennsylvania.

510
00:31:23.640 --> 00:31:26.880
<v Speaker 4>Well right before we get, you know, too far ahead

511
00:31:26.880 --> 00:31:28.480
<v Speaker 4>of the obituary.

512
00:31:29.359 --> 00:31:31.039
<v Speaker 3>No, no, I'm not, I'm not trying to get to

513
00:31:31.119 --> 00:31:35.079
<v Speaker 3>the obituary. I'm just saying, yeah.

514
00:31:34.599 --> 00:31:39.359
<v Speaker 4>Go ahead, she's uh, you know, Walls, you know, we'll

515
00:31:39.359 --> 00:31:42.599
<v Speaker 4>see how it plays out. But Walls did provide some

516
00:31:42.720 --> 00:31:46.720
<v Speaker 4>impact at the at the start of the race. I

517
00:31:46.759 --> 00:31:49.200
<v Speaker 4>would say, I think the biggest criticism of him has

518
00:31:49.240 --> 00:31:54.559
<v Speaker 4>been his debate performance, for better or worse, because it

519
00:31:54.680 --> 00:31:59.119
<v Speaker 4>wasn't able to keep the Republicans on defense from where

520
00:31:59.160 --> 00:32:01.960
<v Speaker 4>Trump was even know, if you look at the polling

521
00:32:02.759 --> 00:32:08.359
<v Speaker 4>between what September the first debate September tenth, and then

522
00:32:08.920 --> 00:32:11.799
<v Speaker 4>prior to that October.

523
00:32:11.640 --> 00:32:14.799
<v Speaker 3>October VP, Yeah, it was October first.

524
00:32:14.559 --> 00:32:17.119
<v Speaker 4>Percent said that Harris won the debate. But as you

525
00:32:17.119 --> 00:32:19.519
<v Speaker 4>look at the ballot test question over those three and

526
00:32:19.519 --> 00:32:23.640
<v Speaker 4>a half weeks, three weeks, Trump actually gained ground. So

527
00:32:23.720 --> 00:32:29.240
<v Speaker 4>it was a very strange ish, you know, situation where

528
00:32:31.480 --> 00:32:33.839
<v Speaker 4>was turning it. Yes, all right, I got it.

529
00:32:33.960 --> 00:32:35.119
<v Speaker 3>I gotta grab a commercial.

530
00:32:35.160 --> 00:32:36.680
<v Speaker 2>I got a couple of calls you want to get to,

531
00:32:38.000 --> 00:32:42.400
<v Speaker 2>and I think you've given me a sense of where

532
00:32:42.400 --> 00:32:44.359
<v Speaker 2>we are a week out. That doesn't mean that's where

533
00:32:44.400 --> 00:32:48.839
<v Speaker 2>we will be a week from now. But I'm looking

534
00:32:49.079 --> 00:32:52.240
<v Speaker 2>at a lot of polls and I'm seeing some of

535
00:32:52.279 --> 00:32:55.279
<v Speaker 2>the same trends that that you're seeing, which in the

536
00:32:55.400 --> 00:32:57.759
<v Speaker 2>end might not make a huge difference, or in the

537
00:32:57.880 --> 00:33:01.119
<v Speaker 2>end they might be the proverbial care canaries in the

538
00:33:01.160 --> 00:33:04.200
<v Speaker 2>coal mine. We'll be back on Night Side with Spencer Kimball.

539
00:33:04.440 --> 00:33:08.720
<v Speaker 2>Emerson College. Emerson College poster coming right back on Nightside.

540
00:33:09.599 --> 00:33:12.559
<v Speaker 1>Now back to Dan Way live from the Window World

541
00:33:12.720 --> 00:33:16.079
<v Speaker 1>Nice Side Studios on WBZ News Radio.

542
00:33:17.119 --> 00:33:20.079
<v Speaker 2>With me Is Emerson, Poster, Spencer, Kimball, Spencer, let's get

543
00:33:20.079 --> 00:33:22.039
<v Speaker 2>a couple of callers in here. We'll talk to the

544
00:33:22.119 --> 00:33:25.359
<v Speaker 2>real people. Let me go to Glenn in Brighton. Glenn,

545
00:33:25.400 --> 00:33:27.720
<v Speaker 2>you were next on Nice Side with Spencer. Kimball had

546
00:33:27.759 --> 00:33:29.240
<v Speaker 2>a question or comment for Spencer.

547
00:33:29.279 --> 00:33:32.960
<v Speaker 5>Glenn, Well, kind of both. I told you to producer

548
00:33:33.079 --> 00:33:35.559
<v Speaker 5>that I'd be a nice person because this sticks in

549
00:33:35.640 --> 00:33:40.279
<v Speaker 5>my c I wish that they neither band postering or

550
00:33:40.319 --> 00:33:43.880
<v Speaker 5>at least have what do not posted me with because

551
00:33:44.119 --> 00:33:45.799
<v Speaker 5>at the end of the day, I don't think it's

552
00:33:45.839 --> 00:33:49.279
<v Speaker 5>anybody's business or I vote for unless you, my friend,

553
00:33:49.680 --> 00:33:50.119
<v Speaker 5>you have.

554
00:33:50.039 --> 00:33:52.599
<v Speaker 3>To answer the polls. Glenn. You know you don't have

555
00:33:52.640 --> 00:33:53.359
<v Speaker 3>to answer me.

556
00:33:53.480 --> 00:33:55.160
<v Speaker 5>I know, and when I do, I lie.

557
00:33:56.599 --> 00:33:59.559
<v Speaker 3>Okay, Well, fine, say how to Glenn, Spencer.

558
00:34:01.279 --> 00:34:01.839
<v Speaker 5>I'm Glenn.

559
00:34:02.039 --> 00:34:06.039
<v Speaker 4>We did we appreciate you know, I mean, you're sharing

560
00:34:06.119 --> 00:34:10.719
<v Speaker 4>whatever opinions, but you know we're not looking to to

561
00:34:10.840 --> 00:34:14.480
<v Speaker 4>influence elections. You know, we're not looking to influence. We're

562
00:34:14.480 --> 00:34:17.920
<v Speaker 4>looking just to represent and be able to share with

563
00:34:18.000 --> 00:34:20.880
<v Speaker 4>public opinion. Not just on elections, but on the issues

564
00:34:20.920 --> 00:34:23.800
<v Speaker 4>of the day, in some of the policies that people

565
00:34:23.840 --> 00:34:27.400
<v Speaker 4>are talking about. So it's important that you know, you

566
00:34:27.480 --> 00:34:29.719
<v Speaker 4>take if you have the opportunity to participate in a

567
00:34:29.800 --> 00:34:33.280
<v Speaker 4>legitimate poll or survey, that you do share your opinion

568
00:34:33.599 --> 00:34:36.559
<v Speaker 4>if you want that opinion to be represented in in

569
00:34:36.639 --> 00:34:39.360
<v Speaker 4>these surveys, because they do have an impact on policy,

570
00:34:39.639 --> 00:34:43.400
<v Speaker 4>they have an impact on to work on, and that's

571
00:34:43.480 --> 00:34:47.039
<v Speaker 4>where you know, it's affording to participate.

572
00:34:47.880 --> 00:34:52.760
<v Speaker 5>That way. Oh, I'm sorry. I don't want to be

573
00:34:52.760 --> 00:34:54.679
<v Speaker 5>influenced by the Boss to go over the Boss and

574
00:34:54.719 --> 00:34:58.000
<v Speaker 5>the Herald or how we would or Taylor Swift or

575
00:34:58.039 --> 00:34:58.480
<v Speaker 5>any of them.

576
00:34:58.480 --> 00:35:01.400
<v Speaker 3>You know what I mean, Glenn, You don't have.

577
00:35:01.280 --> 00:35:04.039
<v Speaker 5>To be I think for myself. That's just me.

578
00:35:04.960 --> 00:35:06.400
<v Speaker 3>That's that you do that, Glenn.

579
00:35:06.440 --> 00:35:10.280
<v Speaker 4>So congratulations, you know, I mean one Glenn, I asked

580
00:35:10.400 --> 00:35:13.440
<v Speaker 4>you what's your most important issue? And I get that

581
00:35:13.559 --> 00:35:16.519
<v Speaker 4>opinion from a thousand people. It lets us know, like

582
00:35:16.639 --> 00:35:19.639
<v Speaker 4>housing affordability is a really important issue for voters.

583
00:35:20.000 --> 00:35:20.320
<v Speaker 5>Mooted.

584
00:35:20.440 --> 00:35:24.880
<v Speaker 4>We know that, but you know that's for you know,

585
00:35:25.360 --> 00:35:27.119
<v Speaker 4>that's what that's what we try to learn and then

586
00:35:27.159 --> 00:35:29.480
<v Speaker 4>hopefully resolve, you know, solve some of the problems that

587
00:35:29.519 --> 00:35:30.559
<v Speaker 4>we have in mind.

588
00:35:31.400 --> 00:35:32.719
<v Speaker 5>Mine's who week immigration.

589
00:35:33.559 --> 00:35:35.639
<v Speaker 2>All right, great, Glenn, I'm gonna let you go because

590
00:35:35.679 --> 00:35:38.400
<v Speaker 2>I think that probably we've that never the Twains, you'll

591
00:35:38.440 --> 00:35:38.719
<v Speaker 2>meet here.

592
00:35:38.800 --> 00:35:39.760
<v Speaker 3>Thanks Glenn.

593
00:35:39.840 --> 00:35:43.119
<v Speaker 5>I just wanted to say some click go ahead, be quick.

594
00:35:43.599 --> 00:35:45.800
<v Speaker 5>All right? Yeah, No, I did get a woman post

595
00:35:45.840 --> 00:35:48.719
<v Speaker 5>her and I could tell that she was actually her

596
00:35:48.760 --> 00:35:52.159
<v Speaker 5>boss called me the next day and apologized. She said,

597
00:35:52.239 --> 00:35:54.360
<v Speaker 5>you know, she started out, are you white? I should

598
00:35:54.400 --> 00:35:56.880
<v Speaker 5>get are you other? Are you? And I said, all right,

599
00:35:56.920 --> 00:35:58.960
<v Speaker 5>I'll tell you the truth. I'm a white, angle sex

600
00:35:59.000 --> 00:36:02.679
<v Speaker 5>and Protestant male. I'm a Trump supporter, and you know

601
00:36:02.880 --> 00:36:05.440
<v Speaker 5>I don't a poet. I want I want my country back.

602
00:36:05.480 --> 00:36:07.280
<v Speaker 5>And she goes, that's on you, and I said, well,

603
00:36:07.320 --> 00:36:09.000
<v Speaker 5>this is on you, and I hung up on her.

604
00:36:09.559 --> 00:36:12.280
<v Speaker 3>Okay, yeah, Solen, appreciate the experience.

605
00:36:12.639 --> 00:36:18.159
<v Speaker 2>I can understand. Uh, I know you pretty well. And again,

606
00:36:18.360 --> 00:36:20.679
<v Speaker 2>you don't have to participate with these folks. It's as

607
00:36:20.679 --> 00:36:23.119
<v Speaker 2>simple as that. As I told you tonight, I sent

608
00:36:23.199 --> 00:36:25.519
<v Speaker 2>the text back to someone said I'll see in Wisconsin.

609
00:36:25.559 --> 00:36:26.599
<v Speaker 3>I'll bring the cash.

610
00:36:27.199 --> 00:36:27.360
<v Speaker 5>You know.

611
00:36:27.920 --> 00:36:31.079
<v Speaker 2>I was having fun, all right, Thanks, Thanks Glenn. Jack

612
00:36:31.119 --> 00:36:33.119
<v Speaker 2>down to the Kpayjack. Next to a nice eye was

613
00:36:33.159 --> 00:36:35.679
<v Speaker 2>Spencer Kimball of Emerson University.

614
00:36:35.679 --> 00:36:41.000
<v Speaker 8>Go ahead, Jack, Thanks guys. I called a couple of

615
00:36:41.039 --> 00:36:43.920
<v Speaker 8>weeks ago and I said that the politics of today

616
00:36:44.039 --> 00:36:48.679
<v Speaker 8>is the ultimate high tech Brendon circus. Who you know

617
00:36:48.800 --> 00:36:55.320
<v Speaker 8>these candidates, this is Bretton's circus. On's who's really running

618
00:36:55.320 --> 00:36:59.920
<v Speaker 8>the show is deep under the deep state. They're underground anyway.

619
00:37:00.159 --> 00:37:09.440
<v Speaker 8>But I want to talk about polling. You know, it

620
00:37:09.519 --> 00:37:14.079
<v Speaker 8>seems to me, you know, you're pulling a person, an event,

621
00:37:14.440 --> 00:37:19.920
<v Speaker 8>a person. What about the depth of the poll. In

622
00:37:19.960 --> 00:37:23.239
<v Speaker 8>other words, you present a pole, but the depth of

623
00:37:23.320 --> 00:37:27.280
<v Speaker 8>the pole, it's really are It's actually a three dimensional

624
00:37:27.639 --> 00:37:34.119
<v Speaker 8>matrix of age and this is what you look at age, sex, location,

625
00:37:34.519 --> 00:37:39.199
<v Speaker 8>all all the dynamic data that goes into into what

626
00:37:39.400 --> 00:37:43.440
<v Speaker 8>with a pole? And uh, how do we how can

627
00:37:43.480 --> 00:37:49.960
<v Speaker 8>we more present the dimensional aspects of a poll rather

628
00:37:50.039 --> 00:37:51.519
<v Speaker 8>than just coming out with the statement.

629
00:37:53.159 --> 00:37:55.639
<v Speaker 3>Spencer's going to answer your question right now? Go ahead, Spencer.

630
00:37:56.840 --> 00:37:59.159
<v Speaker 4>Well, yeah, so the horse phrase is where it gets.

631
00:37:59.159 --> 00:38:02.000
<v Speaker 4>Everybody's a tent and they want the ballot test question

632
00:38:03.360 --> 00:38:07.400
<v Speaker 4>and that's what drives the media. But it's that underlying

633
00:38:07.519 --> 00:38:10.719
<v Speaker 4>data and when we look at this race for examples,

634
00:38:10.920 --> 00:38:12.159
<v Speaker 4>what it's.

635
00:38:12.079 --> 00:38:14.079
<v Speaker 3>Called the cross tabs, correct Spencer.

636
00:38:13.920 --> 00:38:17.360
<v Speaker 4>Yes, the cross tabs, the cross tabs, and so what.

637
00:38:17.320 --> 00:38:20.039
<v Speaker 3>You explained to Jack what you mean by that? Please?

638
00:38:20.960 --> 00:38:24.280
<v Speaker 4>And yeah, so Jack, it's a great question. I know

639
00:38:24.360 --> 00:38:27.000
<v Speaker 4>you're familiar, but for the rest of the audience out

640
00:38:27.000 --> 00:38:31.280
<v Speaker 4>there who might not be as familiar, we have different

641
00:38:31.360 --> 00:38:36.119
<v Speaker 4>variables like gender, or age, or education, and we want

642
00:38:36.159 --> 00:38:41.440
<v Speaker 4>to know how some of those different variables demographics impact

643
00:38:41.480 --> 00:38:43.920
<v Speaker 4>who they're going to vote for or what issues are

644
00:38:44.000 --> 00:38:48.239
<v Speaker 4>most important to them. And what we do is we

645
00:38:48.320 --> 00:38:52.880
<v Speaker 4>can take a look by comparing instead of the whole

646
00:38:52.960 --> 00:38:56.760
<v Speaker 4>sample of a thousand people, we're looking at a subset

647
00:38:56.800 --> 00:38:59.800
<v Speaker 4>of let's say five hundred men or five hundred women,

648
00:39:00.360 --> 00:39:05.239
<v Speaker 4>and from that we can learn, for example, that Donald

649
00:39:05.280 --> 00:39:08.840
<v Speaker 4>Trump is doing better with men this cycle than he

650
00:39:08.880 --> 00:39:14.280
<v Speaker 4>did in twenty twenty, and women are about the same

651
00:39:14.360 --> 00:39:18.760
<v Speaker 4>with Harris than they were with Biden. And that difference

652
00:39:18.960 --> 00:39:22.800
<v Speaker 4>is what's driving the polls and why you're seeing a

653
00:39:22.880 --> 00:39:25.559
<v Speaker 4>three to four point tightening from what we saw in

654
00:39:25.639 --> 00:39:28.960
<v Speaker 4>twenty twenty. And that's all because we have the cross

655
00:39:29.000 --> 00:39:32.599
<v Speaker 4>stabs to look at that data and better understand what's

656
00:39:32.800 --> 00:39:38.639
<v Speaker 4>driving these changes in attitude and what groups are driving it.

657
00:39:39.760 --> 00:39:42.559
<v Speaker 4>And now we like to kind of pull back curtain,

658
00:39:42.679 --> 00:39:46.039
<v Speaker 4>be open from what normal people don't see because we

659
00:39:46.119 --> 00:39:49.599
<v Speaker 4>use this in market research to help sell candy bars

660
00:39:49.599 --> 00:39:53.679
<v Speaker 4>and cars and other products and services by better understanding

661
00:39:53.719 --> 00:39:57.559
<v Speaker 4>our audience ahead of time and then using that information

662
00:39:57.800 --> 00:40:03.000
<v Speaker 4>for persuasion. But here we're just trying to gauge public

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00:40:03.039 --> 00:40:07.000
<v Speaker 4>opinion on those issues of policy or candidates.

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00:40:07.440 --> 00:40:10.039
<v Speaker 2>Gentlemen, I gotta jump in, Jack. We're flat out a

665
00:40:10.079 --> 00:40:11.760
<v Speaker 2>time boy. I wish you called early. It was a

666
00:40:11.760 --> 00:40:14.599
<v Speaker 2>great question, and Spencer, that's a great thanks Jack, Spencer,

667
00:40:14.639 --> 00:40:17.719
<v Speaker 2>that's a great answer. Spencer, Thanks so much for your time.

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00:40:17.760 --> 00:40:19.480
<v Speaker 2>I know it's the busy season. I can't tell you

669
00:40:19.480 --> 00:40:21.840
<v Speaker 2>how much I value your friendship and your work. And

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00:40:21.880 --> 00:40:25.360
<v Speaker 2>we will be watching very closely between now and Tuesday,

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00:40:25.960 --> 00:40:28.559
<v Speaker 2>and if you see anything that's interesting that you want

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00:40:28.559 --> 00:40:33.079
<v Speaker 2>to share with us any night, you got the private numbers, Okay.

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00:40:33.880 --> 00:40:37.440
<v Speaker 4>We'll send out a text. Thanks Dan, Thanks.

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00:40:37.239 --> 00:40:40.400
<v Speaker 2>So much, Thanks so much, Spencer, Kimball. Let's continue to

675
00:40:40.440 --> 00:40:44.559
<v Speaker 2>talk about polls. We may agree or disagree on this,

676
00:40:44.679 --> 00:40:47.679
<v Speaker 2>but i'd like to know your thoughts on polls. I

677
00:40:47.760 --> 00:40:50.280
<v Speaker 2>think they're invaluable. And I tell you why I think

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00:40:50.280 --> 00:40:53.360
<v Speaker 2>they're going to be invaluable this time. Back on Night's side,

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00:40:53.639 --> 00:40:55.159
<v Speaker 2>right after the eleven o'clock news
