My remarks, rationally reconstructed, at the AAAS Panel on “Fake News and Social Media: Impacts on Science Communication and Education” (slides here).
1. Putting the bottom line on top. If one is trying to assess the current health of science communication in our society, then they should likely regard the case of “fake news” as akin to a bad head cold.
The systematic propogation of false information that President Trump is engaged in, on the other hand, is a cancer on the body politic of enlightened self-government.
2. Conjectures inviting refutation. I’ll tell you why I see the “alternative facts presidency” as so much more serious than “fake news.” But before I continue, I want to issue a proviso: namely, that everything I think on these matters is in the nature of informed conjecture.
I will be drawing on the dynamic of identity-protective reasoning to advance my claims (Flynn et al. 2017; Kahan 2010). Because we have learned so much about mass opinion from studies featuring this dynamic, it makes perfect sense to suspect this form of information processing will determine how people react to fake news and to the stream of falsehoods that flow continuously from the Trump administration.
But we should recognize that these phenomena are different from the ones that have supplied the focus for the study of identity-protective reasoning.
Other dynamics—including ones that also reflect well-established mechanisms of cognition—might support competing hypotheses.
Accordingly, it’s not appropriate to stand up in front of you and say “here is what social science tells us about fake news and presidential misinformation . . . .” Social science hasn’t spoken yet. Unless he or she has data that directly address these phenomena, anyone who tells you that “social science says” this or that about “fake news” is engaged in story-telling, a practice that can itself mislead the public and distort scholarly inquiry.
I will, for purposes of exposition, speak with a tone of conviction. But I’m willing to do that only because I can now be confident that you’ll understand my position to be a provisional one, reflecting how things look to me at the Bayesian periphery of a frontier that warrants (demands) empirical exploration. Once valid studies start to accumulate, I am prepared to pull up stakes and move in the direction they prescribe, should it turn out that the ground I’m standing on now is insecure.
3. Models. I’m going to use two simple models to guide my exposition. I’ll call one the “passive aggregator theory” (PAT). PAT envisions a credulous public that is pushed around by misinformation emanating from powerful economic and political interest groups.
That model, I will contend, is simply wrong.
The truth is something closer to the second model I want you to consider. This one can be called the “motivated public theory” (MPT). According to MPT, members of the public are unconsciously impelled to seek out information that supports the view of the identity-defining group they belong to and to dismiss as non-credible any information that challenges that position.
Where the public is motivated to see things in an identity-reinforcing way, it will be very profitable to create misinformation that gives members of the public what they want—namely, corroboration that their group’s positions are right, and those of their benighted rival wrong.
In my view, that’s what the fake news we saw during the election was all about. Some smart people in Macedonia or wherever set up sites with scandalous—in fact, outright incredible—headlines to direct traffic to websites that had agreed to pay them to do exactly that. Indeed, every fake news story was ringed with classic click bait features on overcoming baldness, restoring wrinkled skin, curing erectile dysfunction, and the like.
On the MPT account, the only people who’d be enticed to read such material would be people already predisposed to believe (or maybe fantasize) that the subjects of the stories (Hillary Clinton and Donald Trump, for the most part) were evil or stupid enough to engage in the behavior the stories describe. The incremental effect of these stories in shaping their opinions would be nil.
Same for those predisposed not to believe the stories. They’d be unlikely to see most of them because of the insularity of political-news networks in social media. But even if they saw them, they’d dismiss them out of hand as noncredible.
On net, no one’s view of the world would change in any meaningful way.
4. Empirics. Consider some data that makes a conjecture like this plausible.
a. In the study (Kahan et al., in press), ordinary members of the public were instructed to determine the results of an experiment by looking at a two-by-two contingency table. The right way to interpret information presented in this form (a common one for presenting experimental research) is to look at the ratios of positive to negative impacts conditional on the treatment. The subjects who did this would get the correct answer.
But most people don’t correctly interpret 2x2 contingency tables or alternative formulations that convey the same information. Instead the simply compare the number of positive and negative results in the cells for the treatment condition. Or if they are a little smarter, they do that and look at the number of positive results in both the treatment and the untreated control.
Anyone following that strategy would get the “wrong” answer.
The design also had an experimental component. Half the subjects were told that the 2x2 summarized results—better or worse complexions—for a new skin-rash treatment. The other half that it reflected the results—violent crime up versus violent crime down—of a law that permitted citizens to carry concealed weapons in public.
In the skin-rash condition, the likelihood of getting the answer right turned only on the Numeracy (quantitative-rezoning proficiency) of the subjects, regardless of whether were right-leaning or left-.
But in the gun-control condition, high-numeracy subjects were likely to get the answer right only when the data, properly interpreted, supported the position that was dominant in their ideological group. When the data, property interpreted supported their ideological rival’s position, the subjects highest in Numeracy were no more likely to get the answer correct than those who were low in Numeracy. Essentially they used their reasoning proficiencies to pry open a confabulatory escape hatch to the logic trap they found themselves trapped in.
As a result, the highest Numeracy subjects were the most divided on what the data signified.
This is a result consistent with MPT. If it captures the way that people reason outside the lab, then we should expect to see not only that members of opposing affinity groups are polarized on contentious empirical issues. We should expect to see the degree of polarization between their members increasing in lockstep with diverse citizens’ science comprehension capacities.
And indeed, that is what we see (Kahan 2016).
b. Now consider the significance of this for fake news.
From this simple model, we can see how identity-protective reasoning can profoundly divide opposing cultural groups. Yet no one was being misled about the relevant information. Instead, the subjects were misleading themselves—to avoid the dissonance of reaching a conclusion contrary to their political identifies.
Nor was the effect a result of credulity or any like weakness in critical reasoning.
On the contrary, the very best reasoners—the ones best situated to make sense of the evidence—were the ones who displayed the strongest tendency toward identity-protective reasoning.
Because biased information-search is also a consequence of identity-protective cognition, we should expect that people who reason this way will be much more likely to encounter information that reinforces rather than undermines their predispositions.
Of course, people might now and again stumble across “fake news” that goes against their predispositions, too. But because we know such people are already disposed to bend even non-misleading information into a shape that affirms rather than threatens their identities, there is little reason to expect them to credit “fake news” when the gist of it defies their political preconceptions.
These are inferences that support MPT over PAT.
5. As I stated the outset, we shouldn’t equate the Trump Administration’s persistent propagation of misinformation with the misinformation of the cartoonish “fake news” providers. The influence of the latter, I’ve just explained, are likely to have only a small or no effect on the science communication environment; the former, however, fills that environment with toxins that enervate human reason.
Return to the “motivated public theory.” We shouldn’t be satisfied to treat a “motivated public” as exogenous. How do people become motivated, identity-protective reasoners?
They aren’t, after all, on myriad issues (e.g., GM foods) on which we could easily imagine conflict—indeed, on whether there actually is in other places (e.g., GM foods in Europe).
Memes are self-propagating ideas or practices that enjoy wide circulation by virtue of their salience.
Culturally toxic memes are ones that fuse positions on risks or similar policy-relevant facts to individual identities. The operate primarily by stigmatizing those who hold such positions as stupid and evil.
When that happens, people gravitate toward habits of mind that reinforce their commitment to their groups’ positions. They do that because holding a position consistent with others in their groups is more important to them—more consequential for their well-being—than is holding a positon that is correct.
What an ordinary member of the public thinks about climate change, e.g., will not affect the risk that it poses to her or to anyone she cares The impact she as an individual consumer or an individual voter will be too small to make any real difference.
But given what holding such a position has come to signify about who one is—whose side one is on in a vicious struggle between competing groups for cultural ascendency—forming a belief (an attitude, really) that estranges her from her peers could have devastating psychic and material consequences.
Of course, when everyone resorts to this form of reasoning simultaneously, we’re screwed. Under these conditions, citizens of pluralistic democratic society will fail to converge, or converge as quickly as they should, on valid empirical evidence about the dangers they face and how to avert them (Kahan et al. 2012).
The study we conducted modeled how exposure to toxic memes (ones linking the spread of Zika to global warming or to illegal immigrants) could rapidly polarize cultural groups that are now largely in agreement about the dangers posed by the Zika virus.
This is why we should worry about Trump: his form of misinformation, combined with the office that he holds, makes him a toxic-meme propagator of unparalleled influence.
When Trump spews forth with lies, the media can’t simply ignore him, as they would a run-of-the-mill crank. What the President of the United States says always compels coverage.
Such coverage, in turn, impels those who want to defend the truth to attack Trump in order to try to undo the influence his lies could have on public opinion.
But because the ascendency of Trump is itself a symbol of the status of the cultural groups that propelled him to the White House, any attack on him for lying is likely to invest his position with the form of symbolic significance that generates identity-protective cognition: the fight communicates a social meaning—this is what our group believes, and that what our enemies believe—that drowns out the facts (Nyhan et al 2010, 2013).
We aren’t polarized today on the safety of universal childhood immunization (Kahan 2013; CCP 2014). But we could easily become so if Trump continues to lie about the connection between vaccinations and autism.
We aren’t polarized today on the means appropriate to counteract the threat of the Zika virus (Kahan et al. 2017). But if Trump tries to leverage public fear of Zika into support for tightening immigration laws, we could become politically polarized—and cognitively impeded from recognizing the best scientific evidence on spread of this disease.
Trump is uniquely situated, and apparently emotionally or strategically driven, to enlarge the domain of issues on which this reason-effacing dynamic degrades our society’s capacity to recognize and give proper effect to decision-relevant science.
6. Trump, in sum, is our nation’s science-communication environment polluter-in-chief. We shouldn’t let concern over “fake news” on Facebook to distract us from the threat he uniquely poses to enlightened self-government or from identifying the means by which the threat his style of political discourse can be repelled.
CCP, Vaccine Risk Perceptions and Ad Hoc Risk Communication: An Experimental Investigation (Jan. 27, 2014).
Flynn, D.J., Nyhan, B. & Reifler, J. The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics. Political Psychology 38, 127-150 (2017).
Kahan, D. Fixing the Communications Failure. Nature 463, 296-297 (2010).
Kahan, D.M., Peters, E., Wittlin, M., Slovic, P., Ouellette, L.L., Braman, D. & Mandel, G. The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change 2, 732-735 (2012).
Kahan, D.M. A Risky Science Communication Environment for Vaccines. Science 342, 53-54 (2013).
Kahan, D.M. Culturally antagonistic memes and the Zika virus: an experimental test. J Risk Res 20, 1-40 (2017).
Kahan, D.M. The Politically Motivated Reasoning Paradigm, Part 1: What Politically Motivated Reasoning Is and How to Measure It. in Emerging Trends in the Social and Behavioral Sciences (John Wiley & Sons, Inc., 2016).
Kahan, D.M., Peters, E., Dawson, E. & Slovic, P. Motivated Numeracy and Enlightened Self Government. Behavioural Public Policy (in press).
Nyhan, B. & Reifler, J. When corrections fail: The persistence of political misperceptions. Polit Behav 32, 303-330 (2010).
Nyhan, B., Reifler, J. & Ubel, P.A. The Hazards of Correcting Myths About Health Care Reform. Medical Care 51, 127-132 110.1097/MLR.1090b1013e318279486b (2013).
So everyone probably is familiar with the “conjunction fallacy.” It figures in Tversky & Kahneman’s famous “Linda problem”:
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.
Which is more probable?
1. Linda is a bank teller.
2. Linda is a bank teller and is active in the feminist movement.
According to T&K (1983), about 85% of people select 2. This is a mistake, in their view because “Linda is a bank teller” subsumes all the cases in which she is a bank teller and thus logically includes both the cases in which she is a “bank teller active in the feminist movement” and all the cases in which she is a “bank teller not active in the feminist movement.” On this reading, belonging to class 2 cannot logically be more probable than belong to class 1.
Nevertheless, people make the mistake because 2 is more concrete and conveys a picture that is more vivid than 1. Those who over-rely on heuristic, “System 1” information processing are thus likely to seize on it as the “right answer.” Individuals who score higher in conscious, effortful, “System 2” processing tend to be more likely to supply the correct answer (Toplak, West & Stanovich 2011).
What happens, though, when the individual actor featured in the problem behaves in a manner that evinces bad character, and the more vivid “choice 2” includes information that he possesses certain political outlooks? People tend to attribute bad character to those who disagree with them politically. So will the likelihood of their picking choice 2 be higher if the actor’s political outlooks differ from their own?
We wanted to figure this out. So in our variant of the “Linda problem,” we informed our subjects, approximately 1200 ordinary people, that
Richard is 31 years old. On his way to work one day, he accidentally backed his car into a parked van. Because pedestrians were watching, he got out of his car. He pretended to write down his insurance information. He then tucked the blank note into the van’s window before getting back into his car and driving away.
Later the same day, Richard found a wallet on the sidewalk. Nobody was looking, so he took all of the money out of the wallet. He then threw the wallet in a trash can.
We then assigned them to one of three conditions:
“Which of these two possibilities do you think is more likely?
1. ex-felon condition
Which of these two possibilities do you think is more likely?
(a) Richard is self-employed ____
(b) Richard is self-employed and a convicted felon ___
Which of these two possibilities do you think is more likely?
(a) Richard is self-employed ____
(b) Richard is self-employed and a very strong supporter of strict gun control laws? ___
Which of these two possibilities do you think is more likely?
(a) Richard is self-employed ____
(b) Richard is self-employed and a very strong opponent of strict gun control laws? ___
The motivation to test this proposition originated in a cool article by Will Gervais (et al. 2011), who found that when “Richard” is described as an atheist, people are more likely to display the “conjunction fallacy” than when he is described as an “atheist” or as a “rapist”; we adapted the “Richard” vignette from their study.
What did we find?
Well, first of all, the probability of the conjunction fallacy was highest, regardless of political outlooks, when Richard was described as a convicted felon. Moreover, this bias grew in magnitude as subjects became more right-leaning in their politics.
But when Richard was described as either a "strong opponent"or a "strong supporter" of gun control laws, left-leaning subjects were slightly more likely to display a bias congenial to their political outlooks. Right-leaning ones displayed no meaningful bias in their appraisals.
So there you go. Make of this what you will!
Gervais, W.M., Shariff, A.F. & Norenzayan, A. Do you believe in atheists? Distrust is central to anti-atheist prejudice. Journal of Personality and Social Psychology 101, 1189 (2011).
Toplak, M., West, R. & Stanovich, K. The Cognitive Reflection Test as a predictor of performance on heuristics-and-biases tasks. Memory & Cognition 39, 1275-1289 (2011).
Tversky, A. & Kahneman, D. Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review 90, 293-315 (1983).
To make real progress, the science of science communication must leave the lab (at least now and again)
1. Group conflict over policy-relevant science is not due to limitations on individual rationality. Rather they reflect the consequence of a polluted science-communication environment, in which the entanglement of group identity in contested factual positions forces people to choose between being who they are and knowing what’s known by science. In such an environment it is perfectly rational for an ordinary member of the public to choose the former: his or her personal actions cannot meaningfully contribute to mitigating (or aggravating) societal risks (e.g., climate change); yet because of what positions on such issues have come to signify about who one is and whose side one is on in acrimonious cultural status conflict, he or she can pay a steep reputational cost for forming beliefs contrary to the ones that prevail in that person’s cultural group.
Fixing the science communication environment requires communication strategies that dissolve the conflict between the two things people do with their reason -- be who they are culturally speaking, and know what is known by science.
2. The two-channel model of science communication is one strategy for disentangling identity and positions on societal risks. According to the model, individuals process scientific information along both a content channel, where the issue is the apparent validity of the information, and a social-meaning channel, which address whether accepting such information is consistent with one’s identity. The CCP study reported in Kahan, D.M., Hank, J.-S., Tarantola, T., Silva, C. & Braman, D. Geoengineering and Climate Change Polarization, Testing a Two-Channel Model of Science Communication. Annals of the American Academy of Political and Social Science 658, 192-222 (2015), illustrates this point: after reading a news story that stressed the need for greater carbon emission limits, individuals culturally disposed to climate skepticism reacted closed-mindedly to evidence of climate change; those who first read a story on the call for greater research on geo-entering, in contrast, responded more open-mindedly to the same climate-change research. The difference can plausibly be linked to the stories’ impact in threatening and affirming the group identity, respectively, of those who are culturally disposed to climate skepticism.
3. It’s time to get out of the lab and get into the field. The two-channel model of science communication is just that—a model of how science communication dynamics work. It doesn’t by itself tell anyone exactly what he or she should do to promote better public engagement with controversial forms of decision-relevant science in particular circumstances. To figure that out, social scientists, working with field communicators, must collaborate to determine through additional empirical study how positive results in the lab can be reproduced in the field.
There are more plausible accounts of how to apply such study in real-world circumstances than can plausibly true—just as there was (and still are) more accounts of why public conflict over science exists in the first place. Just as valid empirical testing was needed to extract the true mechanisms from the sea of merely plausible in the lab, so valid empirical testing is needed to extract the true accounts of how to make science communication work in the real world.
CCP’s local-government and science filmmaking initiatives are guided by that philosophy. The great work that is being done by Pew-supported scientists and science advocates deserves the same sort of evidence-based science communication support.
Okay, I think I get this "alternative facts" business:
Panels (A) and (B) show what it looks like when culturally diverse citizens use their knowledge of facts to do the best they can on a test of their “climate science literacy.”
In contrast, panels (C) and (D) show what it looks like when diverse citizens use their knowledge of fact to be a competent member of a cultural tribe.
Sadly, politics puts the question—who are you, whose side are you on—posed by (C) and (D).
Aren't you curious to see the published version of "Science Curiosity and Political Information Processing"?!
Here it is-- & it's free for all 14 billion subscribers to this blog!
This is approximately the 2,92nd episode in the insanely popular CCP series, "Wanna see more data? Just ask!," the game in which commentators compete for world-wide recognition and fame by proposing amazingly clever hypotheses that can be tested by re-analyzing data collected in one or another CCP study. For "WSMD?, JA!" rules and conditions (including the mandatory release from defamation claims), click here.
[I]t may well be possible that the increased polarisation (visible in the left-hand graph [from Science Curiosity & Political Inforamtion Processing]) is a result not so much of OSI [Ordinary Science Intelligence], but rather of a selection effect: as OSI increases, many people are convinced of higher risk and hence “switch” camp towards the liberal/democrat voters. Only the “stubborn” republicans remain and, by implication, the perceived risk by highly scientifically intelligent republicans decreases.
In other words: in the “high” OSI group, there would be much more democrats than republicans compared to the “low” OSI group?
It must be easy for you to prove this hypothesis wrong (or to confirm it) but i don’t seem to find these data very explicitly mentioned in your paper(s).
That's an interesting surmise; for sure it is worth considering whether this kind of endogeneity could be creeping in when one assess how ideological or cultural values influence risk perception.
But here I'd say that the evidence we have on hand makes it unlikely that the results you are curious (science curious, in fact) about reflect flight from the Republican to the Democratic party, thereby causing the Ordinary Science Intelligence (OSI) to become top heavy with left-leaning Americans.
Maybe first I should explain what you obviously know, which is why that possibility wouldn't show up in the figure you are looking at. The two graphs are comparing concern about climate change among left- and right-leaning subjects conditional on their having same OSI scores. So even if there were a disparity in the proportion of right-leaning who score high on OSI, the figures would look exactly the same.
But we can easily look & see if there is such a disparity lurking in the data. Here's what we'd see on relationship of OSI to partisanship:
As reflected in these probability density distributions, those on left & those on right don't differ to any meaningful degree in their OSI scores. The correlation between OSI and scores on the "Left_right" political disposition scale (which is formed by aggregating resposes to liberal-conservative & party-identification items) is - 0.06-- it's hard to get much closer to zero than that! (Indeed,people can look pretty foolishif they think a "statistically significant" difference that paltry matters).
Or at least that's how it looks to me.
It's obviously a problem if one's research strategy involves aimlessly collecting a shitload of data and then fitting a story to whatever one finds.
But for a presentation, it can be a fun change of pace to start with the data and then ask the audience what the research question was. I'll call this the "Research Presentation 'Jeaopardy Opening.' "
I tried this strategy at the the Society for Personality and Social Psychology meeting panel I was on on last Saturday. If I hadn't been on a 15-min clock -- if, say, the talk had been a longer one for a paper workshop or seminar -- I'd have actually called on members of the audience to offer and explain their guesses. Instead I went forward indicating what questions I, as the Alex Trubek of the proceedings, would count as "correct."
But there's no such constraint here on the CCP Blog. So consider these slides & then tell me what question you think the data are the answer too! For my answers/questions, check out the entire slide show.
I usually don't post these until day before or of, but it occurs to me that that's wasting the opportunity to solicit feedback form the 14 billion subscribers to this site, who might well suggest something that improves my actual presentation.
For presentation this Saturday at the Society for Personality and Social Psychology meeting in San Antonio:
Cognitive Dualism and Science Comprehension
I will present evidence of cognitive dualism: the use of one set of information-processing strategies to form beliefs (e.g., in divine creation; the nonexistence of climate change) essential to a cultural identity and another to form alternative beliefs (in evolution; or climate change) esential to instrumental ends (medical practice; adaptation).
Then these at the American Association for the Advancment of Science in Boston on Feb. 17 & 18:
America's Two Climate Changes
There are two climate changes in America: the one people “believe” or “disbelieve” in order to express their cultural identities; and the one about which people acquire and use scientific knowledge in order to make decisions of consequence, individual and collective. I will present various forms of empirical evidence—including standardized science literacy tests, lab experiments, and real-world field studies in Southeast Florida—to support the “two climate changes” thesis.
Does "fake news" matter?
The advent of “fake news” disseminated by social media is a relatively novel phenomenon, the impact of which has not been extensively studied. Rather than purporting to give an authoritative account, then, I will describe two competing models that can be used to structure empirical investigation of the effect of “fake news” on public opinion. The information aggregator account (IA) sees individuals’ beliefs as a register of the sum total of information sources to which they’ve been exposed. The motivated processor account (MP), in contrast, treats individuals’ predispositions as driving both their search for information and the weight they assign any information they are exposed to. These theories generate different predictions about “fake news”: that it will significantly distort public opinion, in the view of IA; or that it will be near irrelevant, in the view of MP. In addition to discussing the provenance of these theories in the science of science communication, I will identify some of the key measurement challenges they pose for researchers and how those challenges can be surmounted.
First session, on HPV vaccine, is tomorrow.
I"ve posted exerpts from this "general information" document before, but having consulted the rulebook on blogs, I found there is no provision that bars repeating oneself (over & over & over, in fact).
I don't think I'll post summaries for every session this yr. Thanks to Tamar Wilner (e.g., here), that worked incredibly well the last time I taught this seminar. But precisely b/c it did, the utility of a "virtual" companion for this yr's run strikes me as low.
Of course, if anyone wants to argue that I'm wrong, I could change my mind. Especially if they agree to be this yr's Tamar Wilner (Tamar Wilner is prohibited from doing so, in fact!)
From the course "general information" document:
1. Overview. The most effective way to communicate the nature of this course is to identify its motivation. We live in a place and at a time in which we have ready access to information—scientific information—of unprecedented value to our individual and collective welfare. But the proportion of this information that is effectively used—by individuals and by society—is shockingly small. The evidence for this conclusion is reflected in the manifestly awful decisions people make, and outcomes they suffer as a result, in their personal health and financial planning. It is reflected too not only in the failure of governmental institutions to utilize the best available scientific evidence that bears on the safety, security, and prosperity of its members, but in the inability of citizens and their representatives even to agree on what that evidence is or what it signifies for the policy tradeoffs acting on it necessarily entails.
This course is about remedying this state of affairs. Its premise is that the effective transmission of consequential scientific knowledge to deliberating individuals and groups is itself a matter that admits of, and indeed demands, scientific study. The use of empirical methods is necessary to generate an understanding of the social and psychological dynamics that govern how people (members of the public, but experts too) come to know what is known to science. Such methods are also necessary to comprehend the social and political dynamics that determine whether the best evidence we have on how to communicate science becomes integrated into how we do science and how we make decisions, individual and collective, that are or should be informed by science.
Likely you get this already: but this course is not simply about how scientists can avoid speaking in jargony language when addressing the public or how journalists can communicate technical matters in comprehensible ways without mangling the facts. Those are only two of many science communication” problems, and as important as they are, they are likely not the ones in most urgent need of study (I myself think science journalists have their craft well in hand, but we’ll get to this in time). Indeed, in addition to dispelling (assaulting) the fallacy that science communication is not a matter that requires its own science, this course will self-consciously attack the notion that the sort of scientific insight necessary to guide science communication is unitary, or uniform across contexts—as if the same techniques that might help a modestly numerate individual understand the probabilistic elements of a decision to undergo a risky medical procedure were exactly the same ones needed to dispel polarization over climate science! We will try to individuate the separate domains in which a science of science communication is needed, and take stock of what is known, and what isn’t but needs to be, in each.
The primary aim of the course comprises these matters; a secondary aim is to acquire a facility with the empirical methods on which the science of science communication depends. You will not have to do empirical analyses of any particular sort in this class. But you will have to make sense of many kinds. No matter what your primary area of study is—even if it is one that doesn’t involve empirical methods—you can do this. If you don’t yet understand that, then perhaps that is the most important thing you will learn in the course. Accordingly, while we will not approach study of empirical methods in a methodical way, we will always engage critically the sorts of methods that are being used in the studies we examine, and I from time to time will supplement readings with more general ones relating to methods. Mainly, though, I will try to enable you to see (by seeing yourself and others doing it) that apprehending the significance of empirical work depends on recognizing when and how inferences can be drawn from observation: if you know that, you can learn whatever more is necessary to appreciate how particular empirical methods contribute to insight; if you don’t know that, nothing you understand about methods will furnish you with reliable guidance (just watch how much foolishness empirical methods separated from reflective, grounded inference can involve).
B/c some folks are apprently keen to follow the course on-line, here is a reading list for Session 1. I'll post these every week & people who are interested should definitely offer their perspectives, as @Gaythia already has done for tomorrow's class! (saves me from having to prepare my class notes!)
So, what to say about Trump’s despicable stance on vaccines? Well, how about this:
1. Despite the regularity of empirically uniformed assertions to the contrary, the policy of universal vaccination, carried out by means of school-enrollment mandates, is not a politically contentious policy. On the contrary, the vast majority of the public --including Democrats and Republicans, climate change skeptics and nonskeptics, evolution believers and evolution nonbelievers—all support this policy.
The universal-vaccination pubic consensus can be, and has been, measured by public opinion polls. But the best evidence is just how high vaccination rates are in the U.S. today, and have been for more than a decade.
Yes, this policy is opposed by a fringe, which various narcissistic public figures and a gaggle of professional conflict entrepreneurs jockey to lead. But the fringe is a fringe; “anti-vaxers”—people who really are committed to rolling back universal childhood vaccinations, the most successful public health policy ever devised—are definitely outliers In whatever culturally identifiable group they come from.
2. This doesn’t mean, though, that the policy of universal childhood vaccinations is immune to political polarization. For proof, consider the HPV vaccine. Designed to protect against most of the strains of the human papilloma virus that cause cervical cancer, the proposal to add HVP to the universal-vaccine schedule splintered the American pubic along familiar political and cultural lines. As a result, this vaccine, even some ten years after the political battle abated, continues to bear a stigma that inhibits states from adding it to the mandatory list, and parents from assenting to the administration of it to their sons and daughters (Gollust et al. 2010; Gollust et al. 2015a, 2015b; Kahan et al. 2010).
3. The key to protecting public confidence in and support for universal childhood vaccinations is the quality of the “vaccine science communication environment.” Consider the HBV vaccine. Like the HPV vaccine, the HBV one is designed to confer immunity to a cancer-causing pathogen, hepatitis-b. Only a few years before its recommendation on the HPV vaccine, the CDC identified it, too, as appropriate for inclusion in schedule of mandatory vaccines (for infants now but initially for adolescents). At the time that the HPV vaccine was an object of intense, and intensely politicized, issue (roughly 2007-2010), the rate for HBV vaccines was between 90% and 95% on a national basis.
The difference in public reactions reflected the difference in the science communication environments in which they learned of these respective vaccines (Kahan 2013, 2016).
Unable (understandably, inevitably) to determine on the basis of personal research and experience all the science that they must accept in order for them to flourish in their lives, ordinary members of the public sensibly become experts on identifying who really knows what about what.
When they applied that form of rational perception to the HBV vaccine, all the cues—from the recommendations of their own pediatricians to the actions of their peers—vouched for the good sense of getting the shot.
But when they first encountered the HPV vaccine, the situation was quite different: they were bombarded with information that emphasized partisan division mirroring the divide over already polarized issues, including climate change, evolution, etc.
The reason for the difference was a risky marketing decision by the manufacturer of the HPV vaccine (Kahan 2013). Keen to accelerate the addition of its own HPV vaccination to the universal-childhood vaccination schedules, and to lock up its control of the market for supplying the vaccine for use in the public-school enrollment programs before approval of a rival firm’s competing vaccination was approved, the manufacturer orchestrated a poorly disguised political marketing campaign, one that included adoption of vaccine mandates in state legislatures. The process attracted the usual conflict entrepreneurs—right and left.
In sum, the company recklessly pushed the HPV vaccine into the political arena, which is ripe with cues that attached a partisan brand to the vaccine. Such cues—ones that make a contested science issue a symbolic test of who one is culturally, and whose side one is on—predictably displace and erode the habits of mind that diverse members of the public use to identify who knows what about what.
The HBV vaccine, in contrast, avoided this dynamic. Like other childhood vaccines, it travelled a depoliticized administrative route to adoption, in which public health authorities insulated from politics added the vaccine to the states’ universal-vaccination schedules. As a result, parents learned of the HBV vaccine from their pediatricians, people the trust, in a normal, unpolluted science communication environment that enabled rather than enfeebled their rational power to discern what is known to science (Kahan 2016).
With the HBV vaccine, they never had to make a choice, in sum, between knowing what science knows and being who they are as members of diverse cultural meanings (Fowler et al. 2015).
But with the HPV one, they did. When they are put in that situation, bet consistently that they will choose to “be who they are” (Kahan 2015), and you will become a very rich person (as conflict entrepreneurs well know).
4. Trump as science communication environment polluter. That’s what makes Trump’s actions—his appointment of the crank Robert Kennedy Jr. --to head up an absurd “vaccines & autism” commission so dangerous. From his bully(bull shit) pulpit, he has a unique power to enmesh the facts on the safety childhood vaccines in the toxic memes (Kahan et al. 2016) that transform a science issue into a cultural-identity one.
His actions also create a condition ideal to the flourishing of conflict entrepreneurs, who profit from the anxieties that cultural conflicts over science provoke, and who until now have floundered about without drawing large followings (CCP 2014).
Fighting back w/ true factual information – while certainly appropriate—is unlikely to do be sufficient once positions on vaccine risks have become fused with personal identity (Nyhan et al. 2014; Nyhan, 2016).
5. To public’s confidence in universal vaccination, we—all the people who aren’t part of the existing anti-vax fringe—need to resist Trump’s toxic stratagems. There’s only one effective remedy for Trump’s vile behavior: to refuse to take the bait. Aside from the HPV disaster, politicians on both the right and the left have for the most part refused to make mandatory childhood-vaccination into a partisan issue. They must do the same now. Indeed, they must band together, across party lines, to condemn Trump for the threat to public health that his actions pose.
And the same goes for those outside the government. Media and interest groups must be discouraged from using Trump’s behavior as an occasion to assimilate childhood-vaccines into the set of toxic issues that put ordinary people to the choice of being who they are or knowing what science knows about how to protect their well-being.
Of course, such groups can be expected to do what is in their interest. So citizens, too, must show that polluting the science communication environment around vaccines is something they won’t tolerate from those whose job it is to inform them.
6. This is the biggest test yet of our society’s science communication literacy. I’m aware, of course, about how empty, how naïve an injunction like the one I just propounded can be. We know a lot more about how and why certain issues become entangled in toxic, science-communication-environment degrading memes than we know about how to stifle that process.
But we must use all we know, and seek to add to it through experience as well as research (Pemberton 2013; Mnookin 2011), to block Trump’s effort to pollute the science communication environment on vaccines, and hope we can learn more from the experience.
The alternative to not even trying is to put at risk what is likely the greatest public-health asset—the broad level of U.S. general public confidence in childhood vaccines—that we possess. . . .
Fowler, E.F. & Gollust, S.E. The content and effect of politicized health controversies. The ANNALS of the American Academy of Political and Social Science 658, 155-171 (2015).
Gollust, S.E., Attanasio, L., Dempsey, A., Benson, A.M. & Fowler, E.F. Political and news media factors shaping public awareness of the HPV vaccine. Women's Health Issues 23, e143-e151 (2013).
Gollust, S.E., Dempsey, A.F., Lantz, P.M., Ubel, P.A. & Fowler, E.F. Controversy undermines support for state mandates on the human papillomavirus vaccine. Health Affair 29, 2041-2046 (2010).
Gollust, S.E., LoRusso, S.M., Nagler, R.H. & Fowler, E.F. Understanding the role of the news media in HPV vaccine uptake in the United States: Synthesis and commentary. Human vaccines & immunotherapeutics, 1-5 (2015).
Kahan, D., Braman, D., Cohen, G., Gastil, J. & Slovic, P. Who Fears the HPV Vaccine, Who Doesn’t, and Why? An Experimental Study of the Mechanisms of Cultural Cognition. Law Human Behav 34, 501-516 (2010).
Nyhan, B., Reifler, J., Richey, S. & Freed, G.L. Effective Messages in Vaccine Promotion: A Randomized Trial. Pediatrics (2014).
Mnookin, S. The panic virus : a true story of medicine, science, and fear (Simon & Schuster, New York, 2011).
Pemberton. Jabbed: Love, Fear and Vaccines (2013).
I'm off to Chicago for this event, where I will present our new paper on disgust's influene on vaccine risk and GM food risk perceptions. If in neighborhood, stop by!
Will try to remember to send a postcard.
The 14 billion regular readers of this blog know that I really despise "null hypothesis tesing." There are lots of reasons but one of the principal ones is that it short circuits practical inference. Sure, a hypothesis might imply/entail rejection of the null; but rejection of the null still might not support the hypothesis -- either because the effect is smaller than one would expect if the hypothesis were true or, even more importantly, because numerous other alternative hypotheses might also entail rejection of the null.
That problem supplied the motivation for the latest CCP paper on the relationship between pathogen-disgust sensitivity and the perceived risks of vaccines and GM foods: the correlations between the disgust scale and those two putative risk sources were no different from the correlation between the scale and myriad other risks that have nothing to do with disgust.
Here's an excerpt that expressly connects the research findings to this defect in NHT.
3.1. Inference strategy
This paper rests on a simple theoretical premise: that rejection of a “null hypothesis” with respect to the correlation between pathogen disgust sensitivity, on the one hand, and GM-food and vaccine risk perceptions, on the other, is not sufficient to support the conclusion that disgust sensitivity meaningfully explains these risk perceptions (Rozeboom 1960; Ziliak & McCloskey 2008). Like all valid latent variable instruments, any scale used to measure pathogen disgust sensitivity will be imperfect. Such a scale should be highly correlated with, and thus reliably measure, a particular form of disgust sensitivity. But such a scale can still be expected to correlate weakly or even modestly with additional negative affective dispositions (Chapman & Anderson 2013). As a result, there can be modest yet practically meaningless correlations between the pathogen disgust sensitivity scale and all manner of risk perceptions that excite negative affective reactions unrelated to disgust.
A comparative analysis is thus appropriate. If disgust genuinely explains perceived risks of vaccines and GM foods, the degree of the correlation between such concerns and a valid measure of pathogen disgust should be comparable to the relatively large correlation between PDS and attitudes already understood to be grounded in disgust. By the same token, one can infer that PD is not a particularly important source of variance in GM-food and vaccine risk perceptions if the correlation between PDS and these putative risk sources is comparable to correlations between pathogen disgust sensitivity and risk sources that do not plausibly excite disgust.
This was the inference strategy that informed design of this study.
* * *
5. Discussion and Conclusion
In assessing risk perceptions, simple correlations can be misleading. Bare null-hypothesis testing doesn’t in itself support inferences without benchmarks to help interpret the uniqueness and magnitude of observed “significant” correlations.
This paper supplied benchmarks for appraising the relationship between pathogen disgust sensitivity and perceptions of vaccine and GM food risks. With respect to both, the correlations with an established disgust-sensitivity scale were no greater than the correlations of myriad risks that were unrelated to disgust, such as the danger of a crash of a commercial airliner or the catastrophic malfunctioning of an elevator in a high-rise building.
In addition, the analyses revealed at least some reason to doubt the discriminant validity of one of the disgust measure that is being used in the study of childhood-vaccine and of GM-food risk perceptions. The conventional PDS scale, it turns out, is even better for predicting who will worry about carjacking and mass shootings than it is for predicting who will worry about the hazards of consuming food additives or being exposed to noxious wastes, not to mention who will be afraid of vaccines and GM foods.
Obviously, this is only one study of many examining the sources of variance in these risk perceptions. A thoughtful reader ought to weigh all of them in forming an opinion, which itself should be open to revision as new evidence arises. We submit, however, that the weight of the evidence presented here ought to be placed on the side of the balance suggesting that disgust is not a meaningful influence on GM-food and vaccine risk perceptions at the general population level.
Chapman, H.A. & Anderson, A.K. Things rank and gross in nature: A review and synthesis of moral disgust. Psychological Bulletin 139, 300 (2013).
Rozeboom, W.W. The fallacy of the null-hypothesis significance test. Psychological bulletin 57, 416-428 (1960).
Ziliak, S.T. & McCloskey, D.N. The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (University of Michigan Press, 2008).
I received this pieces of correspondence from a science journalist, who puts the emminently reasonable question, So what do I, as science journalists, do to combat or avoid the forms of toxic polarization associated with cultural cognition? I offer a few leads in my response, but it occurred to me that the most likely way that Dieter would get a fully satisfying answer would be to invite the 14 billion (with Dieter, make that 14 billion & one) reader of this blog to weigh in.
So read read this earnest science journalist's note & give him your 2 cents worth (it's not much but it can really add up if anything close to all 14 billion of you reply).
Dear Mr. Kahan,
I'm a belgian science journalist working on a presentation about communicating about scientific topics that tend to polarize society (nuclear power, gmo's, vaccines,...). The public will mainly consist of scientists and science communicators.
While looking for information about this I came across your name and some of your research on cultural cognition and I must say it has been a real eye-opener. I'm one of those people who thought it is mainly about spreading the facts. And your research seems to imply this is all wrong. A question that has however so far remained unanswered, is what this means for my work as a science journalist. What can I do to get it right? What should the scientists themselves pay attention to? Could you be so kind to direct me to your papers that are most relevant for answering these questions?
Thanks in advance.
Kind regards, ...
Oh sure, ask me an easy question, why don't you?!
If you don't mind, I'm going to post your question on the CCP blog & see what the 14 billion regular subscribers have say.
But in the meantime, here are some relevant previous blog entries...Climate change & the media: what's the story? (Answer: expressive rationality)
How about this one, which is a classic in study of critical reasoning? What's answer & more importantly what percent of general public get it right? Why don't 100% get the correct answer? How do self-described "tea party" membes do (whatever happened to those guys?) Answers anon . . . .
Answer: 1 & 2--those being the two cards that could contain information falsifying the proposition.
15%--the fraction of the general popultion that can answer this problem correctly
This problem, the Wason Selection Task, is a classic in cognitive science