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Speaker 1: Hey, y'all, we are finally back. Oh my goodness, it's

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Speaker 1: been too long, man. So much life has happened, So

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Speaker 1: much has happened, so much science has happened. Yes, so

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Speaker 1: much nonscience has happened on somebody. And that's why we

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Speaker 1: had to come back. I felt like when the world

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Speaker 1: needed us the most, we disappeared like the avatar aang.

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Speaker 1: It just was not right. Well, we are finally here

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Speaker 1: to make it right. I'm TT and I'm Zakiah and

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Speaker 1: from Spotify, this is Dope Labs. Welcome back to semester

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Speaker 1: four of Dope Labs. We have missed you so much,

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Speaker 1: but let's just jump into it. For the uninitiated, Dope

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Speaker 1: Labs is a weekly podcast that mixes hardcore science, pop culture,

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Speaker 1: and a healthy dose of friendship. This week, we're talking

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Speaker 1: all about something that's been heavy on our minds and

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Speaker 1: hearts for the last few months, science denial. But before

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Speaker 1: we get into that, we have some exciting news that

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Speaker 1: we want to tell y'all about. You thought you couldn't

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Speaker 1: get enough before, Well, we're gonna find out more more, more,

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Speaker 1: more Dumblamore, More Dope Lab, More Dope Lab. Moore, Hey,

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Speaker 1: y'all ask for it. No more of the bi weekly stuff.

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Speaker 1: We're gonna be in your ears every single week. And

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Speaker 1: that's not the only big change that's happening. Semester four

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Speaker 1: is coming exclusively to Spotify for free starting December sixteenth.

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Speaker 1: So if you already listened to us on Spotify, keep

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Speaker 1: doing what you're doing, and don't forget to follow Dope

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Speaker 1: Labs and tap that little bell icon so you never

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Speaker 1: missed when a new episode drops. Now after December sixteenth

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Speaker 1: be able to hear new episodes of Dope Labs anywhere else.

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Speaker 1: So if you don't listen to us on Spotify yet,

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Speaker 1: be sure that you go ahead and make that change.

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Speaker 1: Spotify is where you can listen to Dope Labs plus

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Speaker 1: all your other favorite shows for free. All right, ze,

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Speaker 1: I hope you're ready. Let's start the show. We're starting

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Speaker 1: off this new semester with a real banger. This week,

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Speaker 1: we're talking all about science denial. This has been a

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Speaker 1: huge topic, especially when it comes to the pandemic, but

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Speaker 1: we've also seen a lot of science denial reports in

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Speaker 1: recent years with other issues too. Tit you like climate change, absolutely,

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Speaker 1: we're really passionate about scientific information and combating science denial

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Speaker 1: in general. I mean, it's why we started the podcast. Yes, yes,

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Speaker 1: we want science to be accessible for everybody, and part

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Speaker 1: of that means having good information and the right tools

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Speaker 1: to make decisions, especially when it comes to your health.

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Speaker 1: So we really wanted to understand science denial, its history,

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Speaker 1: and the motivations behind it. And trust us when we

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Speaker 1: say this issue is not as simple as it might seem.

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Speaker 1: So let's get into the rest of tap.

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Speaker 2: But it's a sham Sam Sam Sam, shams Sam, But

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Speaker 2: it's a sham sham.

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Speaker 1: If you're new to Dope Labs. We typically structure our

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Speaker 1: episodes into three main parts, the recitation, the dissection, and

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Speaker 1: the conclusion. The recitations at the beginning of the lab

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Speaker 1: where we get everybody on the same page and define

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Speaker 1: what we know already and what we want to know

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Speaker 1: by the end of the episode, right, And that's followed

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Speaker 1: up by the dissection where we answer those questions in

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Speaker 1: the recitation, where we talk to our guest expert and

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Speaker 1: learn all the information we do our deep dive during

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Speaker 1: this part of the episode, and then we get to

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Speaker 1: the conclusion where we put a nice bow on everything.

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Speaker 1: We kind of round up everything that we have learned

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Speaker 1: throughout the rest of the lab and talk about any

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Speaker 1: conclusions that we can make. All right, So for this

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Speaker 1: episode about science denial, what do we know? Why are

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Speaker 1: we talking about this? Well? I feel like science denials

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Speaker 1: on the tip of everybody sung right now because of

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Speaker 1: the virus spreading that shall not be named. No, we're

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Speaker 1: in the middle of a pandemic. So this is a

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Speaker 1: new experience, a new shared experience for all of us.

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Speaker 1: And so there's a lot of people who are very confused,

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Speaker 1: who are trying to get up to speed with the

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Speaker 1: science around viruses, virus transmission, vaccines and everything like that.

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Speaker 1: And there's a lot of fear, absolutely, I think in

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Speaker 1: addition to all those things you just said and fear,

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Speaker 1: there's a lot of information of varying quality and truth

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Speaker 1: being spread. If you're trying to make some decisions, it's

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Speaker 1: hard to know who or what to believe, and you're

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Speaker 1: just constantly bombarded with information. Yeah, and then we also

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Speaker 1: know that science denial is affecting very specific communities more

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Speaker 1: than others. The other thing I want to know is

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Speaker 1: where do we draw the line from skepticism to denial,

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Speaker 1: Because I feel like a healthy dose of skepticism is good, right.

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Speaker 1: I think that helps you have like really great conversations. Right,

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Speaker 1: But there's like this really thin line where things start

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Speaker 1: to go left. Another question that I have is what

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Speaker 1: can we do to check in on ourselves. I'm not

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Speaker 1: coming from a place where I'm on a high horist.

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Speaker 1: How do I check in with myself? How do I

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Speaker 1: check myself if I'm falling victim to that? I think

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Speaker 1: all of those are really good questions. Let's jump into

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Speaker 1: the dissection. Our guests for today are doctor Gail Sinatra

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Speaker 1: and doctor Barbara Hoefer.

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Speaker 2: My name is Gale Sinatra, and I'm a professor at

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Speaker 2: USC University of Southern California in the Rossier School of Education.

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Speaker 3: And I am Barbara Hoefer. I'm recently retired from Middlebury College,

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Speaker 3: so professor Amrita and that's in Vermont.

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Speaker 1: Doctors Hofer and Sinatra published a book earlier this summer

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Speaker 1: called Science Denial, Why It Happens and What to Do

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Speaker 1: about It. Their book explores the psychological issues that keep

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Speaker 1: folks from having a broad understanding of science. It also

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Speaker 1: offers solutions for those wondering what they can do to

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Speaker 1: help curb the spread of misinformation. And when we say

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Speaker 1: we want to know about science denial, what we mean

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Speaker 1: is we want to know why people may flat out deny,

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Speaker 1: or maybe just a little bit doubt or resist scientific

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Speaker 1: fact or general scientific conclusions. What's keeping them from accepting

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Speaker 1: what's already been proven. It can feel really easy to say,

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Speaker 1: not me, I'm not a victim of science denial. But

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Speaker 1: it's not just accepting big issues like climate change or

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Speaker 1: understanding that vaccine's work. It could also be how you

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Speaker 1: decide to take risks, or if you choose to buckle

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Speaker 1: up in your seat belt even though you know it

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Speaker 1: can protect you in a crash. I think it's also

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Speaker 1: these smaller nuanced things in our day to day lives

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Speaker 1: as well. And everyone is susceptible, all of us, even

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Speaker 1: the people that you know have been highly trained in

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Speaker 1: the science field. We can all be a part of

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Speaker 1: that group. And I think that is something that folks

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Speaker 1: have to understand. What I still want to know a

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Speaker 1: little bit more about is that difference between skepticism and

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Speaker 1: stepping all the way over to science deny.

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Speaker 3: We want people to be skeptical if you see one

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Speaker 3: study with a small sample and there's some clickbait headline,

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Speaker 3: be suspicious, be skeptical. That's the time to question it

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Speaker 3: if it has not been substantiated, corroborated, supported with additional studies.

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Speaker 1: TTU posted something the other day and I was like,

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Speaker 1: spot on, Oh no, what did I say. I've seen

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Speaker 1: a lot of crazy stuff on Twitter. You said it's

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Speaker 1: been a year and a half or a year and

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Speaker 1: nine months. If you're still doing their research, what kind

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Speaker 1: of research is it? Yeah? I just feel like people

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Speaker 1: are still saying I'm doing my research on coronavirus. I'm like, hello, yeah,

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Speaker 1: you doing research. You're kind of just not doing anything

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Speaker 1: and being stuck in your thought process, which I understand.

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Speaker 1: This is a big topic to turn and swallow. Yes,

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Speaker 1: especially if you have to get all the background skills,

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Speaker 1: if you need to understand virology, immunology, molecular biology, vaccine design, sociology,

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Speaker 1: human behavior, risk management, that's a big mountain to climb. Yes.

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Speaker 1: And you know, we've talked about skepticism. We mentioned it

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Speaker 1: a little bit earlier, but I think there's a difference

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Speaker 1: between skepticism of information that you know, you don't know

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Speaker 1: where the source is, it's just tumbling down your feed

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Speaker 1: versus the Johns Hopkins University Bloomberg School of Public Health

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Speaker 1: telling you that the cases are rising in your area,

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Speaker 1: and you're like, h, I don't believe what they're saying.

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Speaker 1: That's not just skepticism right there. So how do we

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Speaker 1: identify science denial?

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Speaker 2: Then you don't see people who are very doubting and

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Speaker 2: resisting science, hesitating to use an iPhone or get on

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Speaker 2: a plane. They're not denying physics, they're not denying the

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Speaker 2: technology that goes into Wi Fi. So it is this

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Speaker 2: phenomena of selective denial, which really is driven by your motivations,

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Speaker 2: your emotions. So you're picking and choosing what you like

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Speaker 2: about science and what you don't like, and science doesn't

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Speaker 2: work that way.

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Speaker 1: That's such a good point. You know, science does not

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Speaker 1: care about your feelings. It's not about our opinions or

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Speaker 1: what we want to be true.

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Speaker 2: It's about what the evidence suggests is our best understanding

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Speaker 2: of the science at the time.

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Speaker 1: Yes, it's so important to remember that science is backed

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Speaker 1: up by research and evidence. For example, with masking and vaccine,

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Speaker 1: scientists are doing studies to see how effective those measures

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Speaker 1: are and then creating guidelines accordingly. And yes, these guidelines

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Speaker 1: can change as the evidence changes as we learn more.

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Speaker 1: But we'll talk a little bit more about that later.

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Speaker 1: But I think we should start with the history of

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Speaker 1: science denial. Tt let's rewind a little bit. Have we

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Speaker 1: seen science denial before in different forms? And how did

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Speaker 1: we get here?

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Speaker 2: The history of science probably starts with science denial, doubt

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Speaker 2: and resistance.

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Speaker 3: We try to trace it back to Galileo and you

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Speaker 3: think about how he was under house arrests for the

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Speaker 3: beliefs that he had, how long it took for people

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Speaker 3: to accept his theories. Think about Darwin, It took more

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Speaker 3: than a n undred years for scientists to accept fully

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Speaker 3: what he was proposing in the way of evolution.

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Speaker 1: So, for real, it feels like science denial has been

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Speaker 1: going on since the beginning of science itself, and in

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Speaker 1: the last fifty years it's become more pervasive as there's

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Speaker 1: been some outside meddling, so corporations realizing that fostering some

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Speaker 1: science denial could help their bottom line. It all goes

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Speaker 1: back to the money.

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Speaker 3: Beginning with the tobacco industry, for example, were interested in

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Speaker 3: trying to deflect the idea that somehow it was cancer causing,

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Speaker 3: and they hired pr firms to so doubt, and the

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Speaker 3: same companies are being used by Exxon and other corporations

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Speaker 3: to make it look as though climate change isn't a

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Speaker 3: certain fact.

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Speaker 1: In fact, even as recently as twenty ten, Philip Morris

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Speaker 1: has routinely argued that Marlboro gold cigarettes actually decrease the

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Speaker 1: risk of cancer. That's wild, but that brings us to today.

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Speaker 1: With a global pandemic and a steadily warming planet. It

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Speaker 1: feels like people are holding their noses up at scientific

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Speaker 1: evidence left and right. So this has made me ask

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Speaker 1: is there an increase science of denial?

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Speaker 2: I think the difference that we see is the amplification

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Speaker 2: of misinformation through social media, and that's coupled with us

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Speaker 2: living in our information bubbles where we get the same

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Speaker 2: information and if it's misinformation, that's same misinformation reinforced over

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Speaker 2: and over again and it becomes more credible. There's the

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Speaker 2: joke that misinformation travels around the world before the truth

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Speaker 2: gets up and puts its pants on. Misinformation is really compelling.

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Speaker 2: It's sometimes interesting or intriguing or even funny to some people,

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Speaker 2: and that gets the clicks. And as we know the

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Speaker 2: way the algorithms are shaped, that more clicks gets more attention.

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Speaker 1: We've talked about algorithms on social media before. What goes

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Speaker 1: viral isn't always true. It really helps us understand why

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Speaker 1: it's so important to talk about science denial right now.

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Speaker 1: So when you think about that amplification and what we

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Speaker 1: know about the brain, and the more you see something,

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Speaker 1: the more is reinforced and you begin to believe it.

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Speaker 1: I think all that makes sense in the current context.

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Speaker 1: Sometimes people who are science deniers go overboard and say

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Speaker 1: I'm just waiting for the science. Well, part of the

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Speaker 1: science is assessing risk. Early on and even later in

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Speaker 1: the pandemic, was people outright saying no to mass like,

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Speaker 1: it's not gonna keep you one hundred percent safe. Well, ma'am,

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Speaker 1: if it's going to keep you ninety percent safe, I'm

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Speaker 1: gonna say, that's still useful, right, And I think that's

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Speaker 1: the part that we start to see this kind of

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Speaker 1: doubling down on. I'm so scientific. I know ninety is

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Speaker 1: less than one hundred, but I think you also know

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Speaker 1: ninety is higher than zero. You know, It's like if

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Speaker 1: you look at the forecast and it says there's a

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Speaker 1: seventy percent chance of rain, you see that and then

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Speaker 1: you're like, Okay, let me take my umbrella just in case. Right,

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Speaker 1: this is the same thing. You don't say, I'm not

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Speaker 1: gonna take my umbrella because it's not one hundred percent

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Speaker 1: chance of rain exactly. So why don't you apply that

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Speaker 1: same logic to mass. Now that we have an understanding

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Speaker 1: of what science denial is, we want to understand what

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Speaker 1: is causing people to flock to science denial. Let's get

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Speaker 1: into the reasons. Doctor Sinatra and doctor Hoefer outline five

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Speaker 1: explanations for science denial, doubt, and resistance. The first is

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Speaker 1: mental shortcuts and cognitive biases, second is understanding beliefs on

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Speaker 1: how and what you know. The third is motivated reasoning,

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Speaker 1: fourth is social identity, and the fifth is emotions and

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Speaker 1: attitudes and not attitude like the keys attitude, different attitude.

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Speaker 1: The first explanation is mental shortcuts and cognitive biases. Right.

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Speaker 1: Cognitive biases are kind of these mental gymnastics that we

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Speaker 1: do so we don't have to run through all the

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Speaker 1: processing every time. Yeah, so our brain is learning along

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Speaker 1: the way. You know, A equals Z, and you don't

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Speaker 1: have to do ABCDEFG all the way through. But sometimes

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Speaker 1: these brains can trick us, and they learn something early

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Speaker 1: on and they reinforce it over and over again. We're

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Speaker 1: going to talk about that in a later episode Mind

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Speaker 1: Over Matter. But you know, one type of cognitive bias

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Speaker 1: is known as confirmation bias.

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Speaker 3: Confirmation bias is this implicit tendency to seek, recall, affirm

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Speaker 3: things that already fit with your existing beliefs. So everybody

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Speaker 3: who's listening can probably think of a time when you

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Speaker 3: googled something to find an answer. You already thought you

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Speaker 3: knew what the answer was, and you're quick googling. As

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Speaker 3: soon as you find it, right, you think, okay, that

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Speaker 3: supports it, but you don't search laterally across to see

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Speaker 3: if it's confirmed or if there's anything that contradicts it.

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Speaker 3: That's confirmation bias.

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Speaker 1: I think we all can remember stuff that we saw

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Speaker 1: on the early Internet or like heard through the grape

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Speaker 1: vine at school. Do you remember me sharing with you

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Speaker 1: on Twitter where this guy said that he found shrimp

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Speaker 1: tails and his Sentimento's christ And I was like, h

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Speaker 1: I don't doubt it, because you know, a long time

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Speaker 1: ago I saw this thing that said that like up

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Speaker 1: to ten percent or something like that of cerial product

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Speaker 1: could be unknown material. And as soon as I said

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Speaker 1: it to you, I was like, hmm, let me check that,

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Speaker 1: because I was like, I have never heard this. I

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Speaker 1: don't believe that. And also, my today many years old

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Speaker 1: brain knows that ten percent is a lot. I've eaten

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Speaker 1: a lot of cereal in my day. I've never seen

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Speaker 1: anything strange that confirmation biased, you know. I think we've

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Speaker 1: been trained to always look for a countering point, make

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Speaker 1: a liar out of me, make me wrong. That's how

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Speaker 1: my Google searches look. I think. The other piece of

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Speaker 1: this right, So, if we think of these mental shortcuts,

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Speaker 1: the second arm of this is just how we think

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Speaker 1: about knowing and learning in the first place.

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Speaker 3: Another chapter that we have is on what psychologists call

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Speaker 3: epistemic cognition, So it's what people believe about knowledge, how

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Speaker 3: they think they know. And one of the issues is

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Speaker 3: epistemic trust. Who do we trust as a source of knowledge.

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Speaker 3: One of the things we talk about in the book

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Speaker 3: are reasons why some people might not trust the medical community.

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Speaker 1: This feels so relevant TT, especially in the face of

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Speaker 1: people deciding whether they trust or don't trust the government

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Speaker 1: and regulating organizations like the FDA, and even when we

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Speaker 1: see these organizations overstepping each other, just like we see

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Speaker 1: the CDC overruling the FDA, who is our regulatory agency,

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Speaker 1: and the CDC is saying, yes, everybody should have a

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Speaker 1: booster shot, right. I mean, when you see stuff like that,

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Speaker 1: how do you know who to trust? Because they both

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Speaker 1: are organizations that we look to for the facts, and

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Speaker 1: especially after seeing such political influence within those organizations, it's

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Speaker 1: hard to know. Hey, if it was susceptible, then is

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Speaker 1: it susceptible now? Is it still unbiased? You know, it

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Speaker 1: makes it really hard. We see the same thing with

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Speaker 1: people being skeptical of mainstream media or which news stations

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Speaker 1: they go to for their information, and it's concerning because

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Speaker 1: the information is not the same. And we talked about

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Speaker 1: this in an article that we wrote for Scientific American.

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Speaker 1: You know, the roots of folks distrust of the scientific community,

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Speaker 1: the medical community to be real, from force sterilization to

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Speaker 1: the latest evaluations of disparities and health. Yeah, I mean, historically,

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Speaker 1: bad things have happened to minoritized folks and to poor folks,

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Speaker 1: and now that leads to poor outcomes for those people.

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Speaker 1: It's embedded in the system, and it feels like a

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Speaker 1: snowbal effect because it's self perpetuating. So you have folks

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Speaker 1: who are going to receive medical treatment and receiving sub

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Speaker 1: par care. That sub par care translates to terrible outcomes.

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Speaker 1: And when they see that terrible care and terrible outcomes,

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Speaker 1: the other people that are on the periphery, you know,

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Speaker 1: family members, children, parents, they then say, I will not

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Speaker 1: trust the medical system, and so they don't go get

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Speaker 1: any type of preventative care, or maybe they don't have

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Speaker 1: access to preventative care, and so then they continue to

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Speaker 1: present with medical issues that are at much later stages

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Speaker 1: and then they get poor care then, or even if

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Speaker 1: they get good care, then they still have poor outcomes. Right, Yeah,

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Speaker 1: it's a vicious cycle of things. We even see things

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Speaker 1: like that present day because I know that there are

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Speaker 1: probably some people who think that's old school medicine, no sir,

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Speaker 1: But when you think about the care that Serena Williams

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Speaker 1: had when she was giving birth to her child, she

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Speaker 1: almost died, right. She kept communicating that she was in

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Speaker 1: a lot of pain, but she wasn't being believed. And

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Speaker 1: that is something that studies have come out that have

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Speaker 1: said there are a large group of doctors who believe

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Speaker 1: that black people have a higher pain tolerance, and so

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Speaker 1: they're treated differently, exactly, treated differently from top to bottom.

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Speaker 1: So that means that black people are less likely to

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Speaker 1: get pain medication. It's not even that you can earn

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Speaker 1: enough money to move you into a different economic class

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Speaker 1: and that protects you. It's about being black, even if

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Speaker 1: I go to the best hospital. Look at Serena Williams,

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Speaker 1: a world class athlete, the Serena Williams, so many grand slams,

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Speaker 1: all of that, and she's still a victim of this.

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Speaker 1: And so when you consider this right, it makes sense

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Speaker 1: that people would have this mistrust or this hesitancy or

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Speaker 1: resistance to information from the medical community, or the scientific community,

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Speaker 1: or even the government.

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Speaker 2: We also hear people say ask your doctor, as if

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Speaker 2: everyone has a doctor they can just get on the phone.

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Speaker 2: Do you have access, do you have a relationship with

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Speaker 2: the doctor, do you know who you can go ask?

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Speaker 2: Not everyone has that kind of access. Some people have

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Speaker 2: hypothesized that Great Britain has had a larger percentage of

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Speaker 2: people vaccinated because they have a universal health care system

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Speaker 2: and everyone knows who their doctor is, and everyone knows

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Speaker 2: where they can go and here, people don't necessarily know

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Speaker 2: where to go, and they don't necessarily have good.

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Speaker 1: Access, preach doctor Sinatra, and that makes all the sense right.

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Speaker 1: Along with this historic and current difference in treatment for

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Speaker 1: different groups, there's also the matter of access that you overlay.

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Speaker 1: And we've heard a lot of things around vaccines where

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Speaker 1: people are saying, oh, wow, well, people just get vaccinated.

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Speaker 1: I'm like, hey, it's a little deeper than wrap. You know,

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Speaker 1: it's not just am I going to go do this thing.

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Speaker 1: I think that that's something that scientists, scientific communicators, and

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Speaker 1: folks in the medical community need to take into account

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Speaker 1: when we are communicating with folks who are skeptical or deniers,

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Speaker 1: is that it's not coming from a place of misinformation.

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Speaker 1: It's coming from real, lived experience, a real place, and

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Speaker 1: it should be respected as such. And TT you hit

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Speaker 1: the nail on the head saying that science, communicators and

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Speaker 1: organizations need to consider who folks trust right and what

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Speaker 1: their lived experiences may be.

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Speaker 2: It's also about trust, So you trust people you identify with,

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Speaker 2: and then you have mistrust for people you don't identify with.

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Speaker 2: So while it's hard for us to understand why somebody

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Speaker 2: would take a livestock dewormer rather than a vaccine.

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Speaker 1: That's right. Folks have been taking ivermectin and that's a

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Speaker 1: drug that's typically used as a parasitic de wormer for

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Speaker 1: a livestock.

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Speaker 2: It's about where they're finding that information. They don't trust

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Speaker 2: the voices that talk about the safety and efficacy of

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Speaker 2: the vaccine, but they are trusting people that there's alternative

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Speaker 2: mechanisms medications to treat COVID, which has no basis. But

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Speaker 2: they're hearing this information from people they identify with and

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Speaker 2: that is who they trust.

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Speaker 1: So someone in your community who you trust says something

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Speaker 1: but there's no supporting scientific evidence, that can still sway

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Speaker 1: people to action or inaction. We saw that with Nicki Minaj.

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Speaker 1: What people grabbed onto and ran with is Nikki didn't

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Speaker 1: take the vaccine and didn't go to the met gala

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Speaker 1: because of it, and then she starts talking about some

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Speaker 1: cousin's friend who has swollen testicles. And that kind of

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Speaker 1: misinformation is so dangerous because people won't do their due diligence.

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Speaker 1: They're going to say, I love Nikki, okay, I love Roman,

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Speaker 1: and they will run with that information and they'll say

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Speaker 1: that's all I need to know.

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Speaker 3: We have realized that nobody trusts just one person. We

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Speaker 3: all have multiple people in our worlds that we trust,

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Speaker 3: and doctors and pastors, for example, can be very influential

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Speaker 3: in terms of the vaccine.

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Speaker 1: And this brings us right back to that algorithm problem though, right,

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Speaker 1: because if the multiple people you trust are all in

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Speaker 1: your bubble, they're all seeing the same shared misinformation, then

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Speaker 1: it feels like everybody you trust is saying don't get vaccinated.

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Speaker 1: The problem then is when people like I know somebody

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Speaker 1: who didn't get vaccinated. They got COVID and they were

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Speaker 1: really sick and they were in and out of the hospital,

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Speaker 1: but then they wrote this really like cryptic post about

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Speaker 1: maybe you should get vaccine. I'm going to tell you

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Speaker 1: who to believe this and that, but I had this

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Speaker 1: terrible experience. You think they got shared like all of

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Speaker 1: their other misinformation? Do you think they came with that

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Speaker 1: same hot fire? No? No, And part of that may

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Speaker 1: be that it wasn't shared because other people have their

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Speaker 1: own what we call motivated reasoning behind what they will

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Speaker 1: and won't share or what they will and won't believe.

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Speaker 1: And doctors Sinatra and Hoefer told us that motivated reasoning

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Speaker 1: is another explanation for science denial.

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Speaker 2: Motivated reasoning is that you can either reason towards what

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Speaker 2: we call an accuracy goal, like in other words, you

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Speaker 2: want to find out the accurate information, or you can

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Speaker 2: often subconsciously reason towards a desired conclusion. So that comes

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Speaker 2: into play when you are weighing information that you've read online.

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Speaker 1: Doctor Sinatra gave us an example of motivated reasoning around

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Speaker 1: stem cell therapyes potential to help with Parkinson's disease.

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Speaker 2: So perhaps you have a friend who has Parkinson's, and

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Speaker 2: so you read articles about whether stem cell therapy can

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Speaker 2: help with Parkinson's. You may be overly enthusiastic about the

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Speaker 2: potential for this therapy and you may reason that it's

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Speaker 2: great when it may be only okay or even not great. Conversely,

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Speaker 2: if you have concerns about the use of stem cells

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Speaker 2: and you question where they come from and you're wondering

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Speaker 2: if they've been used ethically, and then you look at

432
00:23:47,400 --> 00:23:50,400
Speaker 2: a stem cell therapy online, you may reason that, oh,

433
00:23:50,440 --> 00:23:53,080
Speaker 2: this stem cell therapy isn't any good, it doesn't work

434
00:23:53,080 --> 00:23:57,240
Speaker 2: at all. So that's a motivated reasoner. Whether you're reasoning

435
00:23:57,400 --> 00:24:00,679
Speaker 2: too positively or too negatively, based on and wanting the

436
00:24:00,720 --> 00:24:04,160
Speaker 2: outcome to go towards what you're already believing.

437
00:24:04,359 --> 00:24:06,320
Speaker 1: That's a really good point. It almost feels like how

438
00:24:06,320 --> 00:24:09,600
Speaker 1: you do those Googles, you know, if you're already deciding something.

439
00:24:09,720 --> 00:24:12,200
Speaker 1: Is one way we start typing into Google. Google starts

440
00:24:12,200 --> 00:24:14,320
Speaker 1: to guess what you want to type. And if Google,

441
00:24:14,720 --> 00:24:18,560
Speaker 1: which it does, knows like your search history, it's collecting

442
00:24:18,600 --> 00:24:21,560
Speaker 1: all this data from your emails and all these things

443
00:24:21,600 --> 00:24:25,080
Speaker 1: like that, it'll probably lead you to the exact place

444
00:24:25,119 --> 00:24:28,800
Speaker 1: you're looking for, the exact answer that you want answered

445
00:24:28,800 --> 00:24:30,919
Speaker 1: in the exact way that you want it answered to

446
00:24:31,000 --> 00:24:34,639
Speaker 1: confirm your thoughts. Another psychological challenge that can lead to

447
00:24:34,640 --> 00:24:38,119
Speaker 1: science denial is related to our social identity.

448
00:24:38,160 --> 00:24:41,520
Speaker 3: We are all tribal people. We all belong to certain groups,

449
00:24:41,520 --> 00:24:44,240
Speaker 3: and we draw our identity from those groups. And when

450
00:24:44,359 --> 00:24:47,200
Speaker 3: the groups believe certain things, we tend to believe certain things.

451
00:24:47,200 --> 00:24:49,720
Speaker 3: It's a shorthand for thinking about what to believe without

452
00:24:49,920 --> 00:24:52,119
Speaker 3: even maybe looking into it in a lot of depth.

453
00:24:52,280 --> 00:24:54,399
Speaker 3: So if you think about the things that many people

454
00:24:54,440 --> 00:24:59,800
Speaker 3: believe right now, about whether, for example, the vaccine causes infertility,

455
00:25:00,080 --> 00:25:02,880
Speaker 3: which it does not, we know that conclusively. But if

456
00:25:02,920 --> 00:25:05,440
Speaker 3: people have heard that on Facebook or heard it from

457
00:25:05,440 --> 00:25:08,240
Speaker 3: their friends or their neighbors or their identity group, they

458
00:25:08,280 --> 00:25:11,520
Speaker 3: go online, it's not hard to find confirming evidence for

459
00:25:11,640 --> 00:25:15,040
Speaker 3: that and just quit without looking at the fact that

460
00:25:15,240 --> 00:25:18,919
Speaker 3: there is no science evidence behind it. And so we

461
00:25:19,160 --> 00:25:23,520
Speaker 3: have seen some serious tribalism around science denial in ways

462
00:25:23,560 --> 00:25:26,000
Speaker 3: that shock even us who have been writing and thinking

463
00:25:26,040 --> 00:25:28,399
Speaker 3: about this for a long time, of looking at the

464
00:25:28,440 --> 00:25:31,159
Speaker 3: degree to which people will think, this is what my

465
00:25:31,240 --> 00:25:33,320
Speaker 3: people believe, this is what I'm going to believe. And

466
00:25:33,640 --> 00:25:36,560
Speaker 3: we were both dismayed to find that in Missouri last

467
00:25:36,560 --> 00:25:39,119
Speaker 3: week there were people wearing disguises when they went to

468
00:25:39,119 --> 00:25:43,080
Speaker 3: get vaccinations because they didn't want people they knew to

469
00:25:43,200 --> 00:25:46,800
Speaker 3: see them, violating the values that they had upheld that

470
00:25:46,960 --> 00:25:50,640
Speaker 3: masking was bad and that vaccinations were unnecessary.

471
00:25:50,760 --> 00:25:52,560
Speaker 1: You know, this reminds me of and it goes right

472
00:25:52,600 --> 00:25:55,959
Speaker 1: back to Missouri. There was this state representative, Bill Kidd,

473
00:25:56,080 --> 00:25:58,320
Speaker 1: and he had written this post. He said, no, we

474
00:25:58,359 --> 00:26:02,040
Speaker 1: didn't get the vaccine. We're Republican. That's like a social

475
00:26:02,080 --> 00:26:05,119
Speaker 1: identity thing, right. Yeah. I wonder if there was any

476
00:26:05,160 --> 00:26:09,720
Speaker 1: other time in the history of this country where things

477
00:26:09,800 --> 00:26:15,840
Speaker 1: are so strongly tied to a political affiliation where you

478
00:26:15,880 --> 00:26:20,439
Speaker 1: can guess someone's stance on a medical issue outside of

479
00:26:20,520 --> 00:26:23,800
Speaker 1: abortion based on their political party. That's wild to me.

480
00:26:23,920 --> 00:26:26,160
Speaker 1: I think the thing that we both understand, and we're

481
00:26:26,160 --> 00:26:28,880
Speaker 1: seeing more and more people start to understand, is that

482
00:26:29,080 --> 00:26:33,400
Speaker 1: all of this relates to emotions and attitudes and feelings.

483
00:26:33,560 --> 00:26:35,119
Speaker 1: A lot of times, as scientists were trying to just

484
00:26:35,160 --> 00:26:37,080
Speaker 1: look at the facts and only think about the facts,

485
00:26:37,359 --> 00:26:39,359
Speaker 1: and we think of people as these vessels that we

486
00:26:39,520 --> 00:26:41,480
Speaker 1: just pour the facts into. Okay, now, they got it.

487
00:26:41,680 --> 00:26:45,240
Speaker 1: But what we know is how we feel in our emotions.

488
00:26:45,359 --> 00:26:48,080
Speaker 1: They affect how we understand and feel about scientific evidence

489
00:26:48,080 --> 00:26:50,240
Speaker 1: when it's presented to us. Right, And that's the fifth

490
00:26:50,280 --> 00:26:51,439
Speaker 1: reason for science denial.

491
00:26:51,600 --> 00:26:55,160
Speaker 2: Our emotions are part of how we think and reason,

492
00:26:55,560 --> 00:26:58,160
Speaker 2: and they have to be You can't put your emotions

493
00:26:58,200 --> 00:27:00,359
Speaker 2: in a box. But you have to use use your

494
00:27:00,359 --> 00:27:03,280
Speaker 2: emotions in service of good thinking and reasoning, and you

495
00:27:03,680 --> 00:27:06,479
Speaker 2: have to be thoughtful about that. So you can't let

496
00:27:06,560 --> 00:27:11,200
Speaker 2: your emotions derail a good reasoning process. So if you're

497
00:27:11,240 --> 00:27:15,879
Speaker 2: too anxious about climate change, for example, you can shut

498
00:27:15,920 --> 00:27:19,680
Speaker 2: down and not want to engage. And if you're too

499
00:27:19,880 --> 00:27:24,320
Speaker 2: angry about climate change, maybe contributing to a change in

500
00:27:24,400 --> 00:27:27,359
Speaker 2: how you'd have to live your lifestyle. You also shut

501
00:27:27,400 --> 00:27:30,639
Speaker 2: down and don't want to engage. So you have to

502
00:27:30,760 --> 00:27:34,720
Speaker 2: think about your emotions and how they're affecting your thinking

503
00:27:35,040 --> 00:27:38,000
Speaker 2: and then use them in service of your thinking.

504
00:27:38,280 --> 00:27:40,760
Speaker 1: Yes, and is it just me or does it feel

505
00:27:40,800 --> 00:27:44,119
Speaker 1: like it could apply to many areas in our life

506
00:27:44,119 --> 00:27:48,160
Speaker 1: and not just science denial. It sounded like doctor Sinatra

507
00:27:48,320 --> 00:27:52,240
Speaker 1: was preaching a little bit. Maybe it is a read. Okay,

508
00:27:52,440 --> 00:27:54,920
Speaker 1: you already know some of y'all just got your edges

509
00:27:54,920 --> 00:27:57,639
Speaker 1: snatched and you don't even realize it. Check the mirror.

510
00:27:57,680 --> 00:28:02,719
Speaker 1: Are you bollved? So let's take a break and when

511
00:28:02,760 --> 00:28:05,320
Speaker 1: we come back, we'll get into some of the solutions

512
00:28:05,359 --> 00:28:28,159
Speaker 1: for challenging science denial. We're back and we've been talking

513
00:28:28,160 --> 00:28:31,640
Speaker 1: to doctor Gail Sinatra and doctor Barbara Hoefer about their

514
00:28:31,720 --> 00:28:35,760
Speaker 1: fascinating new book. It's called Science Detile, Why It Happens

515
00:28:35,800 --> 00:28:38,160
Speaker 1: and What to Do About It, out now from Oxford

516
00:28:38,240 --> 00:28:40,440
Speaker 1: University Press. In the first half of the dissection, we

517
00:28:40,560 --> 00:28:43,480
Speaker 1: learned what science denial is and what it isn't. Just

518
00:28:43,520 --> 00:28:46,440
Speaker 1: to recap, we went through five reasons for science denial,

519
00:28:46,720 --> 00:28:50,040
Speaker 1: mental shortcuts, and cognitive biases, beliefs on how and what

520
00:28:50,160 --> 00:28:54,640
Speaker 1: you know, motivated reasoning, social identity, and emotions and attitudes.

521
00:28:55,160 --> 00:28:57,920
Speaker 1: So now let's get into the solutions. What can we

522
00:28:57,960 --> 00:28:58,440
Speaker 1: do about it?

523
00:28:58,600 --> 00:29:01,040
Speaker 3: Often the solutions are talked about as though it's one

524
00:29:01,080 --> 00:29:04,400
Speaker 3: on one individuals making change in their own thinking, and

525
00:29:04,440 --> 00:29:07,600
Speaker 3: it's more than that. We need solutions at a higher level.

526
00:29:08,000 --> 00:29:11,280
Speaker 3: And for example, a couple of years ago, Twitter started

527
00:29:11,400 --> 00:29:14,360
Speaker 3: responding if you tried to retweet something that you had

528
00:29:14,360 --> 00:29:17,200
Speaker 3: not even opened, you just like the headline, that you

529
00:29:17,280 --> 00:29:19,600
Speaker 3: get a little message back that says would you like

530
00:29:19,640 --> 00:29:22,880
Speaker 3: to read it first? And that moves people from system

531
00:29:22,880 --> 00:29:24,760
Speaker 3: one to system two thinking in that moment.

532
00:29:25,000 --> 00:29:29,360
Speaker 1: Nobel Prize winning psychologist Daniel Khanneman talks about system one

533
00:29:29,480 --> 00:29:32,960
Speaker 1: and system two thinking in his book Thinking Fast and Slow.

534
00:29:33,240 --> 00:29:37,760
Speaker 3: So system one is that very quick intuitive response, that

535
00:29:38,000 --> 00:29:41,800
Speaker 3: is that gut level confirmation bias, for example, and system

536
00:29:41,840 --> 00:29:45,560
Speaker 3: two is the slower, analytical, thoughtful aspect of the mind.

537
00:29:46,000 --> 00:29:48,760
Speaker 3: And a lot of the times we're operating on system one,

538
00:29:48,880 --> 00:29:50,120
Speaker 3: and it works for us.

539
00:29:50,320 --> 00:29:52,719
Speaker 1: A lot of times we're using system one, and that's okay.

540
00:29:53,000 --> 00:29:55,760
Speaker 1: You often need to make fast decisions, and you don't

541
00:29:55,840 --> 00:29:58,360
Speaker 1: need to tire your brain out over and over. So,

542
00:29:58,400 --> 00:30:00,160
Speaker 1: for example, if you're driving and you need to make

543
00:30:00,160 --> 00:30:02,920
Speaker 1: a split second decision, System one is your go to then,

544
00:30:03,360 --> 00:30:03,920
Speaker 1: But it's.

545
00:30:03,880 --> 00:30:06,000
Speaker 3: Not a great thing when we're trying to figure out

546
00:30:06,040 --> 00:30:09,360
Speaker 3: should I inject bleach into my system in order to

547
00:30:09,520 --> 00:30:12,840
Speaker 3: address COVID do some more work. Don't just do it

548
00:30:12,920 --> 00:30:15,560
Speaker 3: because you just found it online. Are some friends said

549
00:30:15,560 --> 00:30:17,240
Speaker 3: to you or you saw it on Facebook?

550
00:30:17,480 --> 00:30:22,920
Speaker 1: Instead, slow down, yes, absolutely, take a beat and really

551
00:30:23,040 --> 00:30:26,880
Speaker 1: look for substantial evidence. Like it does not serve you

552
00:30:26,920 --> 00:30:28,920
Speaker 1: to get to the answer quickly if it is the

553
00:30:28,960 --> 00:30:31,480
Speaker 1: wrong answer. So this is great to think about in

554
00:30:31,520 --> 00:30:35,000
Speaker 1: this kind of System one versus System two. And it

555
00:30:35,080 --> 00:30:37,840
Speaker 1: seems like, you know, Twitter and even the things on

556
00:30:37,880 --> 00:30:40,640
Speaker 1: Instagram that say this is about vaccine blah blah blah,

557
00:30:40,680 --> 00:30:43,360
Speaker 1: those things are prompting system too, trying to get you

558
00:30:43,400 --> 00:30:45,720
Speaker 1: to engage more analytically. I mean, it's great to see

559
00:30:45,720 --> 00:30:47,960
Speaker 1: this kind of stuff on social media and where information

560
00:30:48,080 --> 00:30:50,160
Speaker 1: is being shared, but it still feels like there's a

561
00:30:50,200 --> 00:30:52,800
Speaker 1: lot we can do as individuals to combat science denial

562
00:30:52,840 --> 00:30:55,400
Speaker 1: as well. Yeah, and one of those things is practicing

563
00:30:55,480 --> 00:30:59,680
Speaker 1: more balanced and informed research, especially when you're doing your

564
00:30:59,720 --> 00:31:00,960
Speaker 1: goo do.

565
00:31:00,960 --> 00:31:05,000
Speaker 2: Your own research means google it. For most people, I

566
00:31:05,200 --> 00:31:09,760
Speaker 2: can't go do research on ice cores or ocean acidification.

567
00:31:10,080 --> 00:31:12,800
Speaker 2: That's just not going to happen. So when we say

568
00:31:12,880 --> 00:31:16,640
Speaker 2: do your own research, it's really not realistic because you

569
00:31:16,680 --> 00:31:20,480
Speaker 2: really can't dive into the research the way the scientists do.

570
00:31:20,840 --> 00:31:25,080
Speaker 2: You look for information online and you have to be

571
00:31:25,280 --> 00:31:30,160
Speaker 2: very discerning. That takes time, it takes effort, and you

572
00:31:30,280 --> 00:31:32,920
Speaker 2: have to know what you're looking for, what to be

573
00:31:33,000 --> 00:31:36,840
Speaker 2: aware of, for example, the source who paid for this research,

574
00:31:37,240 --> 00:31:41,160
Speaker 2: who's sharing this information, and to be able to evaluate

575
00:31:41,240 --> 00:31:46,000
Speaker 2: that takes a lot of awareness and education.

576
00:31:46,360 --> 00:31:50,120
Speaker 1: The whole point of googling something is to get answers quickly.

577
00:31:50,800 --> 00:31:52,880
Speaker 1: When you think of it that way, it's kind of

578
00:31:52,920 --> 00:31:56,320
Speaker 1: counterintuitive to slow your brain down and really approach a

579
00:31:56,360 --> 00:32:00,200
Speaker 1: subject analytically. And that's okay if you're looking for the

580
00:32:00,240 --> 00:32:03,920
Speaker 1: best fall boot right, But I think when it comes

581
00:32:03,960 --> 00:32:06,080
Speaker 1: to making big decisions about your health, that kind of

582
00:32:06,120 --> 00:32:08,760
Speaker 1: quick judgment is not going to serve you will. One

583
00:32:08,800 --> 00:32:10,840
Speaker 1: of my favorite things to do when I'm really trying

584
00:32:10,880 --> 00:32:14,040
Speaker 1: to get knee deep into the information is scholar dot

585
00:32:14,080 --> 00:32:17,880
Speaker 1: Google dot com. For peer reviewed research. Yes, you know,

586
00:32:17,920 --> 00:32:20,800
Speaker 1: when we think about it, that's what these PhDs are. Well,

587
00:32:21,040 --> 00:32:24,080
Speaker 1: at least a large part of it is in research

588
00:32:24,200 --> 00:32:27,880
Speaker 1: and the ability to look for information, judge it, combine

589
00:32:27,920 --> 00:32:30,640
Speaker 1: it with other pieces of information to figure out what

590
00:32:30,680 --> 00:32:32,640
Speaker 1: the landscape is and to say, here are some of

591
00:32:32,680 --> 00:32:34,920
Speaker 1: the holes or here are some of the unknowns, and

592
00:32:34,960 --> 00:32:37,160
Speaker 1: knowing whether or not you have the tools to answer

593
00:32:37,160 --> 00:32:39,840
Speaker 1: some of those questions. That's always what I say. Is

594
00:32:39,840 --> 00:32:42,160
Speaker 1: One thing that I learned from getting a PhD is

595
00:32:42,160 --> 00:32:45,400
Speaker 1: that I don't know anything. I'm skeptical of anybody who

596
00:32:45,440 --> 00:32:47,959
Speaker 1: thinks they know everything about a topic. I establish myself

597
00:32:48,040 --> 00:32:51,240
Speaker 1: as an expert in a very specific field. People come

598
00:32:51,240 --> 00:32:53,080
Speaker 1: to me and they ask me questions, and I feel

599
00:32:53,400 --> 00:32:58,720
Speaker 1: absolutely confident saying I don't know. That's one of my

600
00:32:58,760 --> 00:33:00,960
Speaker 1: favorite answers. But the next is saying, how do we

601
00:33:01,000 --> 00:33:01,800
Speaker 1: get to the right answer?

602
00:33:01,880 --> 00:33:02,320
Speaker 3: Right? Like?

603
00:33:02,400 --> 00:33:04,960
Speaker 1: I don't know? But what questions can we ask? Yes?

604
00:33:05,120 --> 00:33:08,760
Speaker 1: Like and we can do that together Dope labs. You know,

605
00:33:09,080 --> 00:33:12,280
Speaker 1: I think this really makes me think about how we

606
00:33:12,480 --> 00:33:17,520
Speaker 1: teach people to ask questions and even what we teach science,

607
00:33:17,560 --> 00:33:19,880
Speaker 1: as I think so often science is taught as this

608
00:33:19,960 --> 00:33:22,960
Speaker 1: series of facts, and the truth is that it should

609
00:33:22,960 --> 00:33:26,320
Speaker 1: be more of kind of probing questions, right to understand,

610
00:33:26,560 --> 00:33:28,600
Speaker 1: to find the boundaries of what you do and don't know,

611
00:33:28,680 --> 00:33:30,560
Speaker 1: like you just said. And I think that's been a

612
00:33:30,560 --> 00:33:33,000
Speaker 1: lot of the conversation, like, Oh, we've been lagging in

613
00:33:33,120 --> 00:33:36,040
Speaker 1: STEM and science education for so long. Is science education

614
00:33:36,120 --> 00:33:38,040
Speaker 1: the answer to all of this? I don't know. I

615
00:33:38,080 --> 00:33:40,680
Speaker 1: think maybe it's just a piece of the puzzle to

616
00:33:41,040 --> 00:33:42,479
Speaker 1: getting us to a better place.

617
00:33:42,560 --> 00:33:46,680
Speaker 2: We would argue, yes, let's improve science education, but you're right,

618
00:33:46,760 --> 00:33:50,120
Speaker 2: it's not just about more science content. What we think

619
00:33:50,160 --> 00:33:54,000
Speaker 2: students need to learn is more about how science is done,

620
00:33:54,280 --> 00:33:58,840
Speaker 2: the process of science. For example, at the beginning of COVID,

621
00:33:59,080 --> 00:34:03,080
Speaker 2: information kept shifting about masks and whether to wear them

622
00:34:03,200 --> 00:34:07,040
Speaker 2: or not, and whether you could contract COVID from touch

623
00:34:07,080 --> 00:34:10,080
Speaker 2: and surfaces and whether you had to spray down your groceries.

624
00:34:10,360 --> 00:34:12,960
Speaker 3: They didn't understand that this is what scientists do. They

625
00:34:13,000 --> 00:34:15,640
Speaker 3: chip away at a problem, they work on it, they

626
00:34:15,640 --> 00:34:18,719
Speaker 3: try to corroborate what they know, and that this has

627
00:34:18,760 --> 00:34:22,240
Speaker 3: been done very very well in this period of time.

628
00:34:22,400 --> 00:34:26,160
Speaker 3: But a lot of people have dismissed science because they think, ah,

629
00:34:26,239 --> 00:34:28,360
Speaker 3: what do they know? They just keep changing their minds.

630
00:34:28,400 --> 00:34:31,359
Speaker 2: But in fact, the strength of science is that it

631
00:34:31,480 --> 00:34:34,520
Speaker 2: does change based on new evidence, and I think we

632
00:34:34,600 --> 00:34:36,760
Speaker 2: have not taught that enough.

633
00:34:37,080 --> 00:34:41,520
Speaker 1: Absolutely, as doctor Sinatra and doctor Hoefer explain, it's also

634
00:34:41,680 --> 00:34:45,960
Speaker 1: about educating people on how science and the scientific process

635
00:34:46,000 --> 00:34:49,200
Speaker 1: actually works. And by the way, that's also why we

636
00:34:49,280 --> 00:34:52,600
Speaker 1: decided to structure this podcast the way that we do. Yeah.

637
00:34:52,600 --> 00:34:55,279
Speaker 1: I think we're constantly asking new questions and taking in

638
00:34:55,320 --> 00:34:57,719
Speaker 1: the information we have and saying, what kind of conclusions

639
00:34:57,719 --> 00:35:00,080
Speaker 1: do we come to based on what we learned, and

640
00:35:00,120 --> 00:35:02,319
Speaker 1: what else do we see that we don't know? You know,

641
00:35:02,400 --> 00:35:07,439
Speaker 1: often our conclusion is just more questions. And I think

642
00:35:07,480 --> 00:35:10,640
Speaker 1: we've also seen this over and over again during COVID, right. Yeah,

643
00:35:10,719 --> 00:35:12,760
Speaker 1: if you think back to the early stages of the pandemic,

644
00:35:12,840 --> 00:35:14,759
Speaker 1: people are like, we just want something to make this over,

645
00:35:14,840 --> 00:35:17,040
Speaker 1: and it's like, oh, hey, we have vaccines, and then

646
00:35:17,320 --> 00:35:18,680
Speaker 1: folks are saying, I don't know if I'm going to

647
00:35:18,760 --> 00:35:20,880
Speaker 1: have a vaccine. And then now people are saying we

648
00:35:20,880 --> 00:35:23,320
Speaker 1: should get a booster, should we not, whether it's effective,

649
00:35:23,320 --> 00:35:25,759
Speaker 1: who should get them? You know, I think we're constantly

650
00:35:25,920 --> 00:35:28,880
Speaker 1: just collecting data. We're seeing what's happening in other countries.

651
00:35:29,080 --> 00:35:31,360
Speaker 1: But we're also seeing that there are some things separate

652
00:35:31,400 --> 00:35:35,200
Speaker 1: from just the hardcore science, but around social interaction and

653
00:35:35,239 --> 00:35:38,640
Speaker 1: behavior that make some things transferable to the United States

654
00:35:38,680 --> 00:35:41,839
Speaker 1: and some things are not, you know, And all of

655
00:35:41,880 --> 00:35:45,600
Speaker 1: that is part of that reiteration, right, and that constant

656
00:35:45,640 --> 00:35:49,239
Speaker 1: morphing of science, of everybody bringing things in and some

657
00:35:49,280 --> 00:35:51,440
Speaker 1: people saying, oh that's no good, toss it out. You know,

658
00:35:51,480 --> 00:35:53,960
Speaker 1: the quality is poor there. All of that is the

659
00:35:54,320 --> 00:35:57,400
Speaker 1: constant proofreading and editing of the scientific narrative, I think.

660
00:35:57,480 --> 00:35:59,480
Speaker 3: And then the research that Gail and I have each

661
00:35:59,600 --> 00:36:04,240
Speaker 3: done independently and coincidentally, we've discovered that students are overly

662
00:36:04,280 --> 00:36:07,560
Speaker 3: schooled in the scientific method. They think that every scientist

663
00:36:08,160 --> 00:36:12,640
Speaker 3: does this controlled experiment with a hypothesis and a control group,

664
00:36:12,880 --> 00:36:15,840
Speaker 3: and so as a result, they dismiss some of the

665
00:36:15,880 --> 00:36:22,440
Speaker 3: findings that require more abstraction, more inferential reasoning, more observation. So,

666
00:36:22,600 --> 00:36:26,200
Speaker 3: for example, climate change is really confusing to people like that, Well,

667
00:36:26,239 --> 00:36:28,440
Speaker 3: how do they know they didn't do an experiment.

668
00:36:28,719 --> 00:36:31,400
Speaker 2: Well, that's why I think some people really were taken

669
00:36:31,440 --> 00:36:35,280
Speaker 2: aback when the science changed so quickly about COVID, because

670
00:36:35,320 --> 00:36:38,600
Speaker 2: perhaps they were taught that here's a textbook full of

671
00:36:38,920 --> 00:36:42,920
Speaker 2: facts about science, and they're the same textbook we use

672
00:36:43,040 --> 00:36:46,239
Speaker 2: five years ago and nothing's changed. Then this is how

673
00:36:46,280 --> 00:36:49,040
Speaker 2: science is. And of course science is not a collection

674
00:36:49,160 --> 00:36:52,640
Speaker 2: of facts. Science is a process. A science is an

675
00:36:52,680 --> 00:36:57,520
Speaker 2: approach to evidence. It's an attitude, as Barber said, and

676
00:36:57,800 --> 00:37:01,400
Speaker 2: we need to teach it like that. People understand that,

677
00:37:01,480 --> 00:37:05,640
Speaker 2: of course science changes. Of course there's new information, and

678
00:37:05,960 --> 00:37:08,680
Speaker 2: you can use a scientific attitude in your day to

679
00:37:08,760 --> 00:37:09,560
Speaker 2: day life.

680
00:37:09,719 --> 00:37:12,120
Speaker 1: TT you always say this, You've got to be willing

681
00:37:12,160 --> 00:37:15,440
Speaker 1: to change your mind. Yes, you've been talking about scientific

682
00:37:15,440 --> 00:37:18,520
Speaker 1: attitude all this time, and I really believe that for

683
00:37:18,600 --> 00:37:23,359
Speaker 1: most people, the hardest part is unlearning. Yes, going into

684
00:37:23,360 --> 00:37:26,279
Speaker 1: something feeling like you know something is a fact and

685
00:37:26,320 --> 00:37:29,279
Speaker 1: then finding out that it is not. Unlearning that fact.

686
00:37:29,360 --> 00:37:31,719
Speaker 1: It's really really difficult. I think that's something that's hard

687
00:37:31,800 --> 00:37:35,520
Speaker 1: for everyone. But you have to be open to the

688
00:37:35,560 --> 00:37:39,279
Speaker 1: idea of unlearning. And once you are open to it,

689
00:37:39,560 --> 00:37:43,240
Speaker 1: then you can really enter into these conversations and say, Okay,

690
00:37:43,280 --> 00:37:46,239
Speaker 1: I'm hoping to have in my mind change because new

691
00:37:46,280 --> 00:37:49,080
Speaker 1: information comes in. And the last piece of the puzzle,

692
00:37:49,120 --> 00:37:55,759
Speaker 1: beyond organizations and individuals, is science communicators, researchers and professionals themselves.

693
00:37:56,120 --> 00:37:58,480
Speaker 1: We need to open up the scientific community and make

694
00:37:58,520 --> 00:38:01,319
Speaker 1: it more accessible to everyone.

695
00:38:01,520 --> 00:38:04,759
Speaker 2: We have too many scientists who just talk to each other,

696
00:38:04,920 --> 00:38:09,360
Speaker 2: who publish in journals that only other scientists have access

697
00:38:09,400 --> 00:38:12,400
Speaker 2: to their behind firewalls, and then when they go to

698
00:38:12,480 --> 00:38:15,600
Speaker 2: talk to the general public, none of us humans can

699
00:38:15,680 --> 00:38:18,879
Speaker 2: understand them. So we need to do a better job

700
00:38:19,080 --> 00:38:23,880
Speaker 2: training our scientists to be science communicators. We need to

701
00:38:23,920 --> 00:38:28,640
Speaker 2: develop their ability to communicate better about their work. Dope

702
00:38:28,680 --> 00:38:31,919
Speaker 2: Labs is an excellent example of what we can do,

703
00:38:32,040 --> 00:38:36,680
Speaker 2: which is make science more accessible to the general public.

704
00:38:39,960 --> 00:38:41,480
Speaker 1: Yeah, I think we have a lot to do as

705
00:38:41,480 --> 00:38:44,240
Speaker 1: scientific communicators. We do a lot of work with this show,

706
00:38:44,640 --> 00:38:48,239
Speaker 1: trying to bring science to the people and do it

707
00:38:48,239 --> 00:38:51,080
Speaker 1: in a way that makes sense for everyone, in a

708
00:38:51,120 --> 00:38:54,080
Speaker 1: way that's fun for us and you know, hopefully fun

709
00:38:54,120 --> 00:38:56,359
Speaker 1: for everybody else to listen to. But I think that

710
00:38:56,600 --> 00:38:58,759
Speaker 1: for such a long time, the way that science was

711
00:38:58,800 --> 00:39:01,839
Speaker 1: communicated it was community in a way to big up

712
00:39:01,840 --> 00:39:05,239
Speaker 1: the scientists. But now we're finding that that does not

713
00:39:05,680 --> 00:39:09,120
Speaker 1: serve the people. No, and we do science in order

714
00:39:09,160 --> 00:39:13,640
Speaker 1: to advance our world, and if we don't include the

715
00:39:13,719 --> 00:39:17,520
Speaker 1: people we are trying to serve as scientists. What is

716
00:39:17,560 --> 00:39:18,760
Speaker 1: the point If we.

717
00:39:18,719 --> 00:39:23,200
Speaker 2: In education don't do a better job promoting digital literacy,

718
00:39:23,680 --> 00:39:29,040
Speaker 2: algorithmic literacy, critical literacy so that we can have critical

719
00:39:29,080 --> 00:39:33,120
Speaker 2: thinkers and students in K through twelve and higher education

720
00:39:33,320 --> 00:39:37,719
Speaker 2: who can evaluate evidence and think critically about it, then

721
00:39:38,160 --> 00:39:41,080
Speaker 2: we're going to continue to have these challenges.

722
00:39:41,480 --> 00:39:43,839
Speaker 1: So we're trying something new. Every now and then, TT

723
00:39:43,920 --> 00:39:48,399
Speaker 1: and I will share one thing that we either came across, experience,

724
00:39:48,680 --> 00:39:51,800
Speaker 1: want you to experience, or know about in our lives. TT,

725
00:39:51,880 --> 00:39:54,160
Speaker 1: what's your one thing this week? So my one thing

726
00:39:54,239 --> 00:39:57,480
Speaker 1: this week is that I actually saw on Instagram that

727
00:39:57,600 --> 00:40:01,319
Speaker 1: Jordan Peele was selling the get Out screenplay with all

728
00:40:01,360 --> 00:40:05,560
Speaker 1: this extra information and the entire script, and so I

729
00:40:05,640 --> 00:40:09,440
Speaker 1: jumped on that asap and it's really really cool. It

730
00:40:09,480 --> 00:40:12,799
Speaker 1: has some words from Tanana Revedo, which is a kid

731
00:40:12,840 --> 00:40:15,480
Speaker 1: I know you're a big fan, and then we get

732
00:40:15,520 --> 00:40:19,640
Speaker 1: some extra context from Jordan Peel. There's a section in

733
00:40:19,680 --> 00:40:22,600
Speaker 1: the back that has deleted scenes, so it lets you

734
00:40:22,680 --> 00:40:25,000
Speaker 1: know like what they were thinking about adding but ended

735
00:40:25,040 --> 00:40:28,480
Speaker 1: up on the cutting room floor, And there's an alternative

736
00:40:28,600 --> 00:40:31,720
Speaker 1: ending that's at the very end. So I'm really looking

737
00:40:31,760 --> 00:40:34,960
Speaker 1: forward to reading this and just seeing all the little

738
00:40:35,000 --> 00:40:38,359
Speaker 1: notes from each scene that made get Out become what

739
00:40:38,400 --> 00:40:40,799
Speaker 1: we know it today. Awesome. I didn't even know that

740
00:40:40,960 --> 00:40:43,600
Speaker 1: was happening. What's your one thing? My one thing is

741
00:40:43,680 --> 00:40:47,000
Speaker 1: really based on preparing for this lab. When I started

742
00:40:47,000 --> 00:40:50,920
Speaker 1: reading Science Denial, I really became interested in what I

743
00:40:51,000 --> 00:40:55,040
Speaker 1: considered irrational behavior, and so I picked up a book

744
00:40:55,080 --> 00:40:56,800
Speaker 1: that was already on my shelf. It came out in

745
00:40:56,840 --> 00:40:59,600
Speaker 1: two thousand and eight, but it felt so timely and

746
00:41:00,040 --> 00:41:03,960
Speaker 1: felt like it read me for filth Okay, Predictably Irrational

747
00:41:04,000 --> 00:41:07,000
Speaker 1: by Dan Airily, who is actually at Duke right now.

748
00:41:07,680 --> 00:41:10,160
Speaker 1: There when we were there, I don't think. But it's

749
00:41:10,200 --> 00:41:13,000
Speaker 1: like behavioral economics. It helps us understand why we do

750
00:41:13,040 --> 00:41:14,520
Speaker 1: some of the things that we do, and how we

751
00:41:14,560 --> 00:41:18,160
Speaker 1: actually are irrational, and we can predict some of our

752
00:41:18,160 --> 00:41:21,120
Speaker 1: irrational decision making. I love that. Okay, So when you're

753
00:41:21,120 --> 00:41:23,919
Speaker 1: finished with your book, I'll give you the get Out book.

754
00:41:23,920 --> 00:41:25,560
Speaker 1: We'll do a book exchange and so that I can

755
00:41:25,600 --> 00:41:27,160
Speaker 1: get my lap with your and you'll have all my

756
00:41:27,200 --> 00:41:29,759
Speaker 1: notes and highlights. I love that. That's my favorite thing.

757
00:41:43,560 --> 00:41:46,000
Speaker 1: That's it for LAP thirty seven. If you have some

758
00:41:46,040 --> 00:41:48,560
Speaker 1: other stuff to think about, some more questions, please be

759
00:41:48,719 --> 00:41:51,680
Speaker 1: sure to call us at two O two five six

760
00:41:51,800 --> 00:41:54,040
Speaker 1: seven seven zero two eight and tell us what you thought.

761
00:41:54,200 --> 00:41:55,799
Speaker 1: We'll give us an idea for a lap you think

762
00:41:55,840 --> 00:41:57,880
Speaker 1: we should do this semester. You know we like to

763
00:41:57,880 --> 00:42:01,200
Speaker 1: hear from you. That's two O two five seven zero

764
00:42:01,239 --> 00:42:03,799
Speaker 1: two eight. If you love today's episode, there's so much

765
00:42:03,840 --> 00:42:06,960
Speaker 1: more for you to dig into on our website. There

766
00:42:06,960 --> 00:42:09,760
Speaker 1: will be a cheat sheet for today's lab, additional links

767
00:42:09,760 --> 00:42:12,759
Speaker 1: and resources in the show notes. Plus you can sign

768
00:42:12,840 --> 00:42:15,600
Speaker 1: up for our newsletter check it out at Dope labspodcast

769
00:42:15,719 --> 00:42:18,440
Speaker 1: dot com. You can find us on Twitter and Instagram

770
00:42:18,480 --> 00:42:21,480
Speaker 1: at Dope Labs Podcast, and TT's on Twitter and Instagram

771
00:42:21,520 --> 00:42:25,319
Speaker 1: at dr Underscore t Sho, and you can find Zakia

772
00:42:25,360 --> 00:42:28,719
Speaker 1: on Twitter and Instagram at z Said So. And don't

773
00:42:28,760 --> 00:42:30,960
Speaker 1: forget to follow Dope Labs on Spotify and tap the

774
00:42:30,960 --> 00:42:33,280
Speaker 1: bill icon so you never miss when a new episode

775
00:42:33,320 --> 00:42:37,279
Speaker 1: drops special thanks to today's guest experts, doctor Gail M.

776
00:42:37,400 --> 00:42:41,360
Speaker 1: Sinatra and doctor Barbara K. Hoefer. Their book Sigence Denial,

777
00:42:41,440 --> 00:42:43,520
Speaker 1: Why It Happens and What to Do About It is

778
00:42:43,560 --> 00:42:47,799
Speaker 1: available now from Oxford University Press. Check out IndieBound dot org,

779
00:42:47,800 --> 00:42:50,719
Speaker 1: where you can find your nearest independent bookstore and pick

780
00:42:50,760 --> 00:42:54,040
Speaker 1: it up. Dope Labs is a Spotify original production from

781
00:42:54,080 --> 00:42:57,720
Speaker 1: Mega Ownmedia Group. Our producers are Jenny Ratlickmast and Lydia

782
00:42:57,760 --> 00:43:01,239
Speaker 1: Smith of Wave Runner Studios. Editing in sound design by

783
00:43:01,360 --> 00:43:05,920
Speaker 1: Rob Smerciak, Mixing by Cannis Brown. Original music composed and

784
00:43:05,960 --> 00:43:10,000
Speaker 1: produced by Taka Yasuzawa and Alex Sugier from Spotify. Our

785
00:43:10,040 --> 00:43:13,400
Speaker 1: executive producer is Gina Delveack, and creative producers are Baron

786
00:43:13,440 --> 00:43:17,680
Speaker 1: Farmer and Candace Manriquez Rinn Special thanks to Shirley Ramos

787
00:43:17,840 --> 00:43:22,280
Speaker 1: Yasmin of Fifi, camu Elolia, Till krat Key and Brian

788
00:43:22,360 --> 00:43:25,799
Speaker 1: Marquis executive producers from Mega Own Media Group all Right Us,

789
00:43:25,880 --> 00:43:35,480
Speaker 1: T T Show Dia and Zakiah Wattley