watch in slide show mode to observe (modest) animation. comments questions: dan.kahan@yale

Watch in slide show mode to observe (modest) animation.

comments questions: [email protected]

papers,etc: www.culturalcognition.net

mailto:[email protected]

http://www.culturalcognition.net/

Dan M. Kahan

Yale Law School

& many many others!

www.culturalcognition.net

Research Supported by: National Science Foundation, SES-0242106, -0621840 & -0922714 Woodrow Wilson Int’l Center for Scholars Oscar M. Ruebhausen Fund at Yale Law School

Cultural Cognition and Science Communication

I. A simple model: Cultural cognition of risk

II. Some evidence: Mechanisms of cultural cognitionA. Nanotechnology: culturally biased search, assimilationB. Scientific consensus: cultural availabilityC. Climate change risk “fast” and “slow”: cultural dual process

III. Solution: Two channel communication strategy

The science communication problem:

PriorFactualBelief

NewEvidence

RevisedFactualBelief

prior odds X likelihood ratio = posterior odds

Unbiased Evidence Assessment

PriorFactualBelief

NewEvidence


Confirmation Bias


PriorFactualBelief

NewEvidence


CulturalPredisposition

Cultural Cognition


PriorFactualBelief

NewEvidence



Cultural Cognition


PriorFactualBelief

NewEvidence


Cultural Cognition



Nanotechnology Risk Perception: Study Design

1,850 adults drawn from nationally representative on-line panel

Worldviews Self-reported familiarity with nanotechnology Nanotechnology risks v. benefits Other risk perceptions

No information vs. balanced information (between-subject design)

Sample

Measures

Experimental Manipulation

Kahan , Braman, Slovic, Gastil & Cohen Cultural Cognition of Nanotechnology Risks and Benefits, Nature Nanotechnology, 4(2), 87-91 (2009)




Sample

Measures




Climate ChangeNuclear Power


Guns/Gun Control

Risk Perception Key:Low RiskHigh Risk

Mary Douglas’s “Group-Grid” Worldview Scheme

Environmental Risk

Environmental Risk

Abortion

Abortion

Compulsory psychiatric treatment

Compulsory psychiatriac treatment

Guns/Gun Control

HPV Vaccination

HPV Vaccination

Hierarchy

Egalitarianism

Individualism Communitarianism





Sample

Measures



0%

25%

50%

75%

100%

No Information Information-Exposed

Bene

ifts >

Risk

s

Experiment Condition Experiment ConditionNo Info. No Info.Info.-Exposed

0%

25%

50%

75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*

63%Unfamiliar with Nano

Familiar with Nano

Figure 1

EgalitarianCommunitarian

HierarchicalIndividualist

Ben

efits

> R

isks

Source: Kahan , Braman, Slovic, Gastil & Cohen Cultural Cognition of Nanotechnology Risks and Benefits, Nature Nanotechnology, 4(2), 87-91 (2009)

Perc

eive

Ben

efits

> R

isks

* Change across conditions significant at p < 0.05

0%

25%

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100%

0%

25%

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100%



0%

25%

50%

75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

50%

75%

100%



0%

25%

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100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

50%

75%

100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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100%



0%

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85%77%

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Info.-Exposed

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Familiar with Nano

Figure 1



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> R

isks

0%

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0%

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85%77%

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Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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50%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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100%


Bene

ifts >

Risk

s


0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks



0%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

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> R

isks

0%

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0%

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85%77%

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86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

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Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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100%



0%

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100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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100%



0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

0%

25%

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0%

25%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

Perc

eive

Ben

efits

> R

isks

0%

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Bene

ifts >

Risk

s


0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks



0%

25%

50%

75%

100%

Perc

eive

Ben

efits

> R

isks




Sample

Measures



0%

25%

50%

75%

100%



0%

25%

50%

75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

63%

77%

61%

85%

0%

25%

50%

75%

100%

No Information Information-ExposedExperimental Condition

Bene

ifts >

Risk

s

Unfamiliar with Nano

Familiar with Nano86%

61%

23%

0%

25%

50%

75%

100%


Bene

ifts >

Risk

s

Hierarchical Individualist

Egalitarian Communitarian

*

*


Source: Kahan , Braman, Slovic, Gastil & Cohen Cultural Cognition ofNanotechnology Risks and Benefits, Nature Nanotechnology, 4(2), 87-91 (2009)

0%

25%

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75%

100%

No Infor matio n Infor mation- Exp osed

Bene

ifts >

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s

0%

25%

50%

75%

1 00%

No Inf ormatio n Infor mation-E xpo sed

Bene

ifts >

Risk

s

Experiment Condition Experiment ConditionNo Info. No Info.Info. -Exposed

0%

25%

50%

75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Fami liar wi th Nano

Figure 1

Egali tarianCommuni tarian

HierarchicalIndividualis t

Ben

efits

> R

isks

0%

25%

50%

75%

100%



Familiar with Nano

0%

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100%


Bene

ifts >

Risk

s



*

*



0%

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Familiar with Nano

0%

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100%


Bene

ifts >

Risk

s



*

*



Information effect: familiarity Information effect: culture

Perc

eive

Ben

efits

> R

isks

0%

25%

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75%

100%



0%

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75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

63%

77%

61%

85%

0%

25%

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100%


Bene

ifts >

Risk

s



61%

23%

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Bene

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s



*

*



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s

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1 00%


Bene

ifts >

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s


0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*



Figure 1



Ben

efits

> R

isks

0%

25%

50%

75%

100%



Familiar with Nano*

*



0%

25%

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75%

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Familiar with Nano*

*




Perc

eive

Ben

efits

> R

isks

0%

25%

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100%



0%

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50%

75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

63%

77%

61%

85%

0%

25%

50%

75%

100%


Bene

ifts >

Risk

s



61%

23%

0%

25%

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75%

100%


Bene

ifts >

Risk

s



*

*



0%

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100%


Bene

ifts >

Risk

s

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1 00%


Bene

ifts >

Risk

s


0%

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100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*



Figure 1



Ben

efits

> R

isks


Perc

eive

Ben

efits

> R

isks

High Risk

ModerateRisk

SlightRisk

Almost NoRisk

1.00

2.00

3.00

4.00

Internet Mad CowDisease

NuclearPower

GeneticallyModifiedFoods

Private GunOwnership

Familiar with NanotechnologyUnfamiliar with Nanotechnology

n = 1,820 to 1,830. Risk variables are 4-pt measures of “risk to people in American Society” posed by indicated risk. Differences between group means all significant at p ≤ .01.

0%

25%

50%

75%

100%



0%

25%

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75%

100%

85%77%

61% 61%

Info.-Exposed

86%*

23%*


Familiar with Nano

Figure 1



Ben

efits

> R

isks

63%

77%

61%

85%

0%

25%

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100%


Bene

ifts >

Risk

s



61%

23%

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ifts >

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s



*

*



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ifts >

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s

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1 00%


Bene

ifts >

Risk

s


0%

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85%77%

61% 61%

Info.-Exposed

86%*

23%*



Figure 1



Ben

efits

> R

isks


Perc

eive

Ben

efits

> R

isks

1 2 3 4 5 6 7 8 9 10

0.9%2.2%

3.6%

5.8%

19.5%

-1.4%-0.9%-0.9%-0.5%-2.6%

0%

-5%

10%

15%

20%

25%

5%

Incr

ease

in P

redi

cted

Lik

elih

ood

of S

elf-

Rep

orte

d Fa

mili

arity

with

Nan

otec

hnol

ogy

Hierarch

Egalitarian

20th 40th 60th 80th 99th

Communitarian IndividualisticPercentile

Figure S1

1st


PriorFactualBelief

NewEvidence


Cultural Cognition



PriorFactualBelief


Cultural Cognition

ScientificConsensus





Guns/Gun Control


Guns/Gun Control

Hierarchy

Egalitarianism


Cultural Cognition Worldviews



Most agree 4x Most disagree

8x

Divided

4x

Most agree 5x

Most disagree

6x Divided

2x

Most agree 2x

Most disagree

2x Divided =

=

Most agree

5x

Most disagree 4x Divided =

=

2x =

2x =

2x =

2x =

Global temperatures are increasing.

Human activity is causing global warming.

Radioactive wastes from nuclear power can be safely disposed of in deep underground storage facilities.

Permitting adults without criminal records or histories of mental illness to carry concealed handguns in public decreases violent crime.

57%

“What is the position of expert scientists?”How much more likely to believe

5x

2x =

12x3x

6x

Source: Kahan, D.M., Jenkins-Smith, H. & Braman, D. Cultural Cognition of Scientific Consensus. J. Risk Res. 14, 147-74 (2011).

randomly assign 1 “It is now beyond reasonable scientific dispute that human activity is causing ‘global warming’ and other dangerous forms of climate change. Over the past century, atmospheric concentration of carbon dioxide (CO2)—called a “greenhouse gas” because of its contribution to trapping heat—has increased to historically unprecedented levels. Scientific authorities at all major universities agree that the source of this increase is human industrial activity. They agree too that higher C02 levels are responsible for steady rises in air and ocean temperatures over that period, particularly in the last decade. This change is resulting in a host of negative consequences: the melting of polar ice caps and resulting increases in sea levels and risks of catastrophic flooding; intense and long-term droughts in many parts of the world; and a rising incidence of destructive cyclones and hurricanes in others.”

Robert Linden

Position: Professor of Meteorology, Massachusetts Institute of Technology Education: Ph.D., Harvard University Memberships:

American Meteorological Society National Academy of Sciences

“Judged by conventional scientific standards, it is premature to conclude that human C02 emissions—so-called ‘greenhouse gasses’—cause global warming. For example, global temperatures have not risen since 1998, despite significant increases in C02 during that period. In addition, rather than shrinking everywhere, glaciers are actually growing in some parts of the world, and the amount of ice surrounding Antarctica is at the highest level since measurements began 30 years ago. . . . Scientists who predict global warming despite these facts are relying entirely on computer models. Those models extrapolate from observed atmospheric conditions existing in the past. The idea that those same models will accurately predict temperature in a world with a very different conditions—including one with substantially increased CO2 in the atmosphere—is based on unproven assumptions, not scientific evidence. . . .”

Robert Linden

Position: Professor of Meteorology, Massachusetts Institute of Technology Education: Ph.D., Harvard University Memberships:

American Meteorological Society National Academy of Sciences

High Risk(science conclusive)

Low Risk(science inconclusive)

Climate Change

randomly assign 1 “Radioactive wastes from nuclear power plants can be disposed of without danger to the public or the environment through deep geologic isolation. In this method, radioactive wastes are stored deep underground in bedrock, and isolated from the biosphere for many thousands of years. Natural bedrock isolation has safely contained the radioactive products generated by spontaneous nuclear fission reactions in Oklo, Africa, for some 2 billion years. Man-made geologic isolation facilities reinforce this level of protection through the use of sealed containers made of materials known to resist corrosion and decay. This design philosophy, known as ‘defense in depth,’ makes long-term disposal safe, effective, and economically feasible.”

Oliver Roberts

Position: Professor of Nuclear Engineering, University of California, Berkeley Education: Ph.D., Princeton University Memberships:

American Association of Physics National Academy of Sciences

“Using deep geologic isolation to dispose of radioactive wastes from nuclear power plants would put human health and the environment at risk. The concept seems simple: contain the wastes in underground bedrock isolated from humans and the biosphere. The problem in practice is that there is no way to assure that the geologic conditions relied upon to contain the wastes won’t change over time. Nor is there any way to assure the human materials used to transport wastes to the site, or to contain them inside of the isolation facilities, won’t break down, releasing radioactivity into the environment. . . . These are the sorts of lessons one learns from the complex problems that have plagued safety engineering for the space shuttle, but here the costs of failure are simply too high.

Oliver Roberts



Low Risk(safe)

High Risk(not safe)

Geologic Isolation of Nuclear Wastesrandomly assign 1 “Radioactive wastes from nuclear power plants can be disposed of without danger to the public or the environment through deep geologic isolation. In this method, radioactive wastes are stored deep underground in bedrock, and isolated from the biosphere for many thousands of years. Natural bedrock isolation has safely contained the radioactive products generated by spontaneous nuclear fission reactions in Oklo, Africa, for some 2 billion years. Man-made geologic isolation facilities reinforce this level of protection through the use of sealed containers made of materials known to resist corrosion and decay. This design philosophy, known as ‘defense in depth,’ makes long-term disposal safe, effective, and economically feasible.”

Oliver Roberts



“Using deep geologic isolation to dispose of radioactive wastes from nuclear power plants would put human health and the environment at risk. The concept seems simple: contain the wastes in underground bedrock isolated from humans and the biosphere. The problem in practice is that there is no way to assure that the geologic conditions relied upon to contain the wastes won’t change over time. Nor is there any way to assure the human materials used to transport wastes to the site, or to contain them inside of the isolation facilities, won’t break down, releasing radioactivity into the environment. . . . These are the sorts of lessons one learns from the complex problems that have plagued safety engineering for the space shuttle, but here the costs of failure are simply too high.

Oliver Roberts



“So-called ‘concealed carry’ laws increase violent crime. The claim that allowing people to carry concealed handguns reduces crime is not only contrary to common-sense, but also unsupported by the evidence. . . . Looking at data from 1977 to 2005, the 22 states that prohibited carrying handguns in public went from having the highest rates of rape and property offenses to having the lowest rates of those crimes. . . .To put an economic price tag on the issue, I estimate that the cost of “concealed carry laws” is around $500 million a year in the U.S.”

James Williams Position: Professor of Criminology, Stanford University Education: Ph.D., Yale University Memberships:

American Society of Criminologists National Academy of Sciences

“Overall, ‘concealed carry’ laws decrease violent crime. The reason is simple: potential criminals are less likely to engage in violent assaults or robberies if they think their victims, or others in a position to give aid to those persons, might be carrying weapons. . . . Based on data from 1977 to 2005, I estimate that states without such laws, as a group, would have avoided 1,570 murders; 4,177 rapes; and 60,000 aggravated assaults per year if they had they made it legal for law-abiding citizens to carry concealed handguns. Economically speaking, the annual gain to the U.S. from allowing concealed handguns is at least $6.214 billion.”

James Williams

Position: Professor of Criminology, Stanford University Education: Ph.D., Yale University Memberships:

American Society of Criminologists National Academy of Sciences

High Risk(Increase crime)

Low Risk(Decrease Crime)

Concealed Carry Laws



Guns/Gun Control


Guns/Gun Control

Hierarchy

Egalitarianism



-80% -60% -40% -20% 0% 20% 40% 60% 80%

Climate Change

Nuclear Waste

Gun Control

Low RiskHigh Risk

N = 1,500. Derived from ordered-logit regression analysis, controlling for demographic and political affiliation/ideology variables. Culture variables set 1 SD from mean on culture scales. CIs reflect 0.95 level of confidence

ConcealedCarry

ClimateChange

NuclearPower 31%

54%

22%

58%61%

72%

Pct. Point Difference in Likelihood of Selecting Response

60% 40% 20% 0 20% 40% 60%

-80%

-60%

-40%

-20%

0%20

%40

%60

%80

%

Clim

ate

Cha

nge

Nucl

ear W

aste

Gun

Con

trol

Low RiskHigh Risk

Egalitarian CommunitarianMore Likely to Agree

Hierarchical IndividualistMore Likely to Agree

Featured scientist is a knowledgeable and credible expert on ...



Most agree 4x Most disagree

8x

Divided

4x

Most agree 5x

Most disagree

6x Divided

2x

Most agree 2x

Most disagree

2x Divided =

=

Most agree

5x

Most disagree 4x Divided =

=

2x =

2x =

2x =

2x =

Global temperatures are increasing.

Human activity is causing global warming.

Radioactive wastes from nuclear power can be safely disposed of in deep underground storage facilities.

Permitting adults without criminal records or histories of mental illness to carry concealed handguns in public decreases violent crime.

57%

“What is the position of expert scientists?”How much more likely to believe

5x

2x =

12x3x

6x

PriorFactualBelief


Cultural Cognition


ScientificConsensus


The “public irrationality thesis” (PIT)

1. Science illiteracy

2. “Bounded rationality”

The “Public Irrationality Thesis”

1 + 2 + 3 =

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

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0.00

0.25

0.50

0.75

1.00

low high-1.00

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low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci

“How much risk do you believe climate change poses to human health, safety, or prosperity?”

U.S. general population survey, N = 1,500. Knowledge Networks, Feb. 2010. Scale 0 (“no risk at all”) to 10 (“extreme risk”), M = 5.7, SD = 3.4. CIs reflect 0.95 level of confidence.

-1.00

-0.75

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0.00

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low high

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low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

PIT prediction: Science Illiteracy & Bounded Rationality

-1.00

-0.75

-0.50

-0.25

0.00

0.25

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1.00

point 1 point 2

low vs. high sci

High Sci. litearcy/System 2

Low Sci. litearcy/System 1



-1.00

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0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci

Lesser Risk

Greater Risk

Science literacy Numeracylow high

perc

eive

d ris

k (z

-sco

re)

low high

PIT prediction PIT prediction

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

30b 30t 30b 30t

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

30b 30t 30b 30t

actual varianceactual variance

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci



-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci



PIT prediction

Scilit/num Scalelow high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Actual variance

Low Sci lit/numeracy

High Sci lit/numeracy

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci





Cultural Variance...

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high



-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)




-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high



PIT prediction: Culture as heuristic substitute

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low highHierarchical Individualist

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci




Actual interaction of culture & sci-lit/num...


-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num

High Sci lit/numeracyEgal Comm

Low Sci/lit numeracyEgal Comm

Low Sci lit/num.Hierarc Individ

High Sci lit/numeracyHierarch Individ

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci





-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num




-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high


Actual interaction of culture & sci-lit/num...

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

Greater

Lesser

perc

eive

d ris

k (z

-sco

re)

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

point 1 point 2

low vs. high sci





-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high

sci_num


POLARIZATION INCREASES as scil-lit/numeracy increases



-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

low high


PriorFactualBelief

NewEvidence


Cultural Cognition


System 1 and System 2


Communication

channel 1: content

channel 2: meaning

PriorFactualBelief


CulturalWorldview

NewEvidence

Two Channel Communication Strategy


4. Experimental response items

A. Evidence Skepticism Module

13. Convincing. We would like to know what you think of the Nature Science study, excerpts of which you just read. In your view, how convincing was the study on a scale of 0-10 with 0 meaning “completely unconvincing” to 10 meaning “completely convincing”?

Please indicate how strongly you disagree or agree with the following statements concerning the study. [Strongly disagree, moderately disagree, slightly disagree, slightly agree, moderately agree, strongly agree]

14. Biased. The scientists who did the study were biased. 15. Computers. Computer models like those relied on in the study are not a

reliable basis for predicting the impact of CO2 on the climate. 16. Moredata. More studies must be done before policymakers rely on the

findings of the Nature Science study.

study_dismiss scale (α = 0.85)

Hierarchy

Egalitarianism

Individualism

Climate change


Communitarianism

Climate change

Risk Perception KeyLow RiskHigh Risk

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20

control pollution geoengineering

HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit

Study dismissiveness

Hierarch IndividEgal Commun

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

anti-pollution

Control Condition

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

anti-pollution

Anti-pollution Condition

Geoengineering Condition

4. Experimental response items

A. Evidence Skepticism Module

13. Convincing. We would like to know what you think of the Nature Science study, excerpts of which you just read. In your view, how convincing was the study on a scale of 0-10 with 0 meaning “completely unconvincing” to 10 meaning “completely convincing”?

Please indicate how strongly you disagree or agree with the following statements concerning the study. [Strongly disagree, moderately disagree, slightly disagree, slightly agree, moderately agree, strongly agree]

14. Biased. The scientists who did the study were biased. 15. Computers. Computer models like those relied on in the study are not a

reliable basis for predicting the impact of CO2 on the climate. 16. Moredata. More studies must be done before policymakers rely on the

findings of the Nature Science study.

study_dismiss scale (α = 0.85)

Anti-pollution Condition

Communication

channel 1: content

channel 2: meaning

PriorFactualBelief


CulturalWorldview

NewEvidence



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

anti-pollution

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

anti-pollution

Geoengineering Condition

Communication

channel 1: content

channel 2: meaning

PriorFactualBelief


CulturalWorldview

NewEvidence



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit



-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

anti-pollution

-1.20-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20


HI

EC

z_St

udy

dism

iss 2

Dismiss

Credit



anti-pollution

1.0

1.5

2.0

2.5


more polarization

lesspolarization

Polarizationz_

Stud

y di

smiss

2

anti-pollution

0.0

0.5

1.0

1.5

2.0

2.5

3.0

control anti-pollution geoengineering

US

UKDi

ff. in

stu

dy_v

alid

ity

lesspolarization

more polarization

anti-pollutioncontrol geoengineering

U.S.

England

Communication

channel 1: content

channel 2: meaning

PriorFactualBelief


CulturalWorldview

NewEvidence



I. A simple model: Risk and cultural polarization

II. Some evidence: (Two) mechanisms of cultural cognition

III. Climate changeA. “Scientific consensus”B. Thinking “fast” or “slow”

IV. Solution: two channel communication

The science communication problem

Cultural Cognition Cat Scan Experiment

Go to www.culturalcognition.net!

Individualism-Communitarianism

CHARM. Sometimes government needs to make laws that keep people from hurting themselves.

IPROTECT. It's not the government's business to try to protect people from themselves.

IPRIVACY. The government should stop telling people how to live their lives.

CPROTECT. The government should do more to advance society's goals, even if that means limiting the freedom and choices of individuals.

CLIMCHOI. Government should put limits on the choices individuals can make so they don't get in the way of what's good for society.

Hierarchy-Egalitarianism

HEQUAL. We have gone too far in pushing equal rights in this country.

EWEALTH. Our society would be better off if the distribution of wealth was more equal.

ERADEQ. We need to dramatically reduce inequalities between the rich and the poor, whites and people of color, and men and women.

EDISCRIM. Discrimination against minorities is still a very serious problem in our society.

HREVDIS2. It seems like blacks, women, homosexuals and other groups don't want equal rights, they want special rights just for them.

HFEMININ. Society as a whole has become too soft and feminine.

Figure 1. Short form culture scales. Short forms for Individualism-communitarianism (Cronbach’s α = 0.76) and Hierarchy-egalitarianism (Cronbach’s α = 0.84), each of which consists of six items loading on orthogonal principal components.

[UK SET] People in our society often disagree about how far to let individuals go in making decisions for themselves. How strongly you agree or disagree with each of these statements?

13. IINTRSTS. The government interferes far too much in our everyday lives. 14. IPRIVACY. The government should stop telling people how to live their lives. 15. IPROTECT. It’s not the government’s business to try to protect people from themselves. 16. SHARM. Sometimes government needs to make laws that keep people from hurting themselves. 17. SLIMCHOI. Government should put limits on the choices individuals can make so they don’t

interfere with what’s good for society. 18. SPROTECT. The government should do more to advance society’s goals, even if that means

limiting the freedom and choices of individuals. People in our society often disagree about issues of equality and discrimination. How strongly you agree or disagree with each of these statements?

19. HEQUAL. We have gone too far in pushing equal rights in this country. 20. HFEMININ. Society as a whole has become too soft and feminine. 21. HREVDIS2. It seems like ethnic minorities, women, homosexuals and other groups don’t want

equal rights, they want special rights just for them. 22. EDISCRIM. Discrimination against minorities is still a very serious problem in our society. 23. ERADEQ. We need to dramatically reduce inequalities between the rich and the poor, whites and

ethnic minorities, and men and women. 24. EWEALTH. Our society would be better off if the distribution of wealth was more equal.

CCP: UK Scale Performance

0

1

2

3

4

5

6

7

8

9

10

VACC

INES

GUNR

ISK

PRES

S LI

ABIL

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NANO

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POW

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SYNB

IO

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RISK

GWRI

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EXCE

SSRE

G

EDCU

TS

GMFO

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CIGS

MO

KE

IMM

IGRA

NT

AFGH

AN

TEEN

PREG

NUCW

ASTE

AIRP

OLL

UTIO

N

HATE

SPEE

CH

FOO

DADD

WAT

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LLUT

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TERR

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GOVS

PEND

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DRUG

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0 1 2 3 4 5 6 7 8 9 10

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

n’s = 1373-1420. CIs are 0.95 level of confidence

“How much risk do you believe each of the following poses to human health, safety, or prosperity?”

no risk at all extreme risk0 1 2 3 4 5 6 7 8 9 10

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

0

1

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VACC

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GUNR

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SK

POW

ERLI

NES

SYNB

IO

NUKE

RISK

GWRI

SK

EXCE

SSRE

G

EDCU

TS

GMFO

OD

CIGS

MO

KE

IMM

IGRA

NT

AFGH

AN

TEEN

PREG

NUCW

ASTE

AIRP

OLL

UTIO

N

HATE

SPEE

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FOO

DADD

WAT

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DRUG

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VACCINES

GUNRISK

PRESS LIABILITY

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MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG


no risk at all extreme risk0 1 2 3 4 5 6 7 8 9 10

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

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TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

0 1 2 3 4 5 6 7 8 9 10

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

n’s = 1373-1420. CIs are 0.95 level of confidence

-1.20 -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

NUKERISK

GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

ECEIHCHI

-1.20 -1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20

VACCINES

GUNRISK

PRESS LIABILITY

NANO

MARYJRISK

POWERLINES

SYNBIO

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GWRISK

EXCESSREG

EDCUTS

GMFOOD

CIGSMOKE

IMMIGRANT

AFGHAN

TEENPREG

NUCWASTE

AIRPOLLUTION

HATESPEECH

FOODADD

WATERPOLLUTION

TERROR

GOVSPENDING

DRUG

-1.0

0-0

.80

-0.6

0-0

.40

-0.2

00.

000.

200.

400.

600.

801.

00

VACC

INES

NANO

SYNB

IOEX

CESS

REG

CIGS

MO

KETE

ENPR

EGHA

TESP

EECH

TERR

OR

EC

EI

HC

HI


less risk less risk more riskmore risk

United States England

Scores are group means for groups identified by dividing subjects into 4 groups based on culture-scale values.n’s = 307-383. CIs are 0.95 level of confidence

zscorezscore

Hierarchy

Australia

_cons -1.27e-17 .0223086 -0.00 1.000 -.0437576 .0437576 individ -.22243 .0223157 -9.97 0.000 -.2662014 -.1786586 hierarch -.4039863 .0223157 -18.10 0.000 -.4477577 -.3602149 Zccrisk Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1583 1583 1 Root MSE = .88787 Adj R-squared = 0.2117 Residual 1246.32745 1581 .788315906 R-squared = 0.2127 Model 336.672553 2 168.336276 Prob > F = 0.0000 F( 2, 1581) = 213.54 Source SS df MS Number of obs = 1584

ccri

sk (z

-sco

re)

hierarchical individualist egalitarian communitarian

more concerned

less concerned

note: Derived from multivariate regression below. “Hierarchical individualist” reflects +1 SD on hierarchy and individ scales; “egalitarian communitarians” reflects -1 SD on both. CIs reflects 0.95 level of confidence.

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

1 2

Q23#Q24#Q25#

U.S., Jan. 2010

Australia, July 2011

U.K., March 2011

Item

% correct

EVENROLL.

Imagine that we roll a fair, six-sided die 1,000 times. (That would mean that we roll one die from a pair of dice.) Out of 1,000 rolls, how many times do you think the die would come up as an even number?

58%

PCTTOFREQUENCY1.

In the BIG BUCKS LOTTERY, the chances of winning a $10.00 prize are 1%. What is your best guess about how many people would win a $10.00 prize if 1,000 people each buy a single ticket from BIG BUCKS?

60%

FREQUENCYTOPCT1.

In the ACME PUBLISHING SWEEPSTAKES, the chance of winning a car is 1 in 1,000. What percent of tickets of ACME PUBLISHING SWEEPSTAKES win a car?

28%

COMPFREQUENCY.

Which of the following numbers represents the biggest risk of getting a disease?

86%

COMPPCT.

Which of the following numbers represents the biggest risk of getting a disease?

88%

DOUBLEPCT.

If Person A’s risk of getting a disease is 1% in ten years, and Person B’s risk is double that of A’s, what is B’s risk?

64%

DOUBLEFREQUENCY.

If Person A’s chance of getting a disease is 1 in 100 in ten years, and person B’s risk is double that of A, what is B’s risk?

21%

PCTTOFREQUENCY2.

If the chance of getting a disease is 10%, how many people would be expected to get the disease:

A: Out of 100? 84%

B: Out of 1000? 81%

FREQUENCYTOPCT2.

If the chance of getting a disease is 20 out of 100, this would be the same as having a __% chance of getting the disease.

72%

VIRAL.

The chance of getting a viral infection is .0005. Out of 10,000 people, about how many of them are expected to get infected?

48%

BAYESIAN.

Suppose you have a close friend who has a lump in her breast and must have a mammogram. Of 100 women like her, 10 of them actually have a malignant tumor and 90 of them do not. Of the 10 women who actually have a tumor, the mammogram indicates correctly that 9 of them have a tumor and indicates incorrectly that 1 of them does not have a tumor. Of the 90 women who do not have a tumor, the mammogram indicates correctly that 81 of them do not have a tumor and indicates incorrectly that 9 of them do have a tumor. The table below summarizes all of this information. Imagine that your friend tests positive (as if she had a tumor), what is the likelihood that she actually has a tumor?

3%

SHANE1. A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?

12%

SHANE2.

In a lake, there is a patch of lilypads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?

27%

SI Table 1. Numeracy measures and responses. N = 1540.

Individualists, and 6.0 (SEM = 0.10) for Egalitarian Communitarians.

items % correct

EARTHOT The center of the Earth is very hot [true/false]. 86%

HUMANRADIO All radioactivity is man-made [true/false]. 84%

LASERS Lasers work by focusing sound waves [true/false]. 68%

ELECATOM Electrons are smaller than atoms [true/false]. 62%

COPERNICUS1 Does the Earth go around the Sun, or does the Sun go around the Earth? 72%

COPERNICUS2 How long does it take for the Earth to go around the Sun? [one day, one month, one year] 45%

DADGENDER It is the father’s gene that decides whether the baby is a boy or a girl [true/false]. 69%

ANTIBIOTICS Antibiotics kill viruses as well as bacteria [true/false]. 68%

SI Table 1. Science literacy items. N = 1540.

Climate Change 1 2 3 z_Sci/Num -0.09 (-3.35) -0.03 (-1.43) -0.04 (-1.70) Hierarch

-0.46 (-21.06) -0.46 (-20.41)

Individ

-0.30 (-13.97) -0.30 (-13.57) hierarch x z_Sci/Num

-0.05 (-2.30)

individ x z_Sci/Num

-0.02 (-1.12) constant 0.00 (-0.02) 0.00 (0.00) 0.00 (0.14) F (1, 1538) 11.23 (3, 1536) 221.99 (5, 1534) 134.62 Δ F (2, 1536) 320.73 (2, 1534) 3.10

SI Table 1. Multivariate regression analysis of climate change risk perceptions. N = 1540. Predictors are unstandardized OLS regression coefficients with t-statistic indicated parenthetically. Outcome variable is standardized (z-score) responses to “How much risk do you believe climate change poses to human health, safety, or prosperity?” Bolded indicates that the coefficient, F statistic, or the change in F statistic is significant at p < 0.05. Note that because all predictors are centered at 0, the regression coefficients for the predictor and moderator variables in models that contain cross-product interaction terms indicate the effect of the relevant variable when the other is at its mean value (J accard & Turrisi 2003, pp. 15-16). Missing values for individual cultural worldview items and for GWRISK were replaced using multiple imputation (Rubin 2004; Royston 2004).

US: Relative “dismissiveness” (HI v. EC)

3: 0.445 133.037(8,1326) 0.000 0.008 4.699(4,1326) 0.001 2: 0.437 258.499(4,1330) 0.000 0.437 516.449(2,1330) 0.000 1: 0.000 0.314(2,1423) 0.731Model R2 F(df) p R2 change F(df) change p

R-Square Diff. Model 3 - Model 2 = 0.008 F(4,1326) = 4.699 p = 0.001 _cons -.0204372 .0355048 -0.58 0.565 -.0900888 .0492145 ifxc -.0047235 .0505759 -0.09 0.926 -.103941 .0944941 ifxg -.1136344 .0503379 -2.26 0.024 -.212385 -.0148838 hfxc -.161833 .0507357 -3.19 0.001 -.2613641 -.062302 hfxg -.1429355 .0503273 -2.84 0.005 -.2416653 -.0442056 ifac .3399063 .0356013 9.55 0.000 .2700653 .4097473 hfac .6985416 .0357468 19.54 0.000 .6284152 .768668 geocon .0081998 .0501113 0.16 0.870 -.0901062 .1065059 controlcon .0419327 .0506473 0.83 0.408 -.0574248 .1412902 Zstudy_dis~2 Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1349.59492 1334 1.01169034 Root MSE = .75141 Adj R-squared = 0.4419 Residual 748.678246 1326 .564614062 R-squared = 0.4453 Model 600.91667 8 75.1145837 Prob > F = 0.0000 F( 8, 1326) = 133.04 Source SS df MS Number of obs = 1335

Adding : hfxg hfxc ifxg ifxc Variables in Model: controlcon geocon hfac ifac Model 3:

R-Square Diff. Model 2 - Model 1 = 0.437 F(2,1330) = 516.449 p = 0.000 _cons -.0184632 .0356726 -0.52 0.605 -.0884438 .0515174 ifac .2977866 .0207044 14.38 0.000 .2571699 .3384034 hfac .5946481 .0207161 28.70 0.000 .5540083 .6352879 geocon .008575 .0503661 0.17 0.865 -.0902306 .1073807 controlcon .0363353 .0508986 0.71 0.475 -.063515 .1361856 Zstudy_dis~2 Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1349.59492 1334 1.01169034 Root MSE = .75558 Adj R-squared = 0.4357 Residual 759.290581 1330 .570895174 R-squared = 0.4374 Model 590.304335 4 147.576084 Prob > F = 0.0000 F( 4, 1330) = 258.50 Source SS df MS Number of obs = 1335

Adding : hfac ifac Variables in Model: controlcon geocon Model 2:

_cons -.0005947 .045761 -0.01 0.990 -.0903609 .0891716 geocon -.0240968 .0643834 -0.37 0.708 -.1503933 .1021998 controlcon .027407 .0653458 0.42 0.675 -.1007775 .1555914 Zstudy_dis~2 Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1425 1425 1 Root MSE = 1.0005 Adj R-squared = -0.0010 Residual 1424.37162 1423 1.00096389 R-squared = 0.0004 Model .628380564 2 .314190282 Prob > F = 0.7307 F( 2, 1423) = 0.31 Source SS df MS Number of obs = 1426

Adding : controlcon geocon Variables in Model: Model 1:

. hireg Zstudy_dismiss2 (controlcon geocon )(hfac ifac) (hfxg hfxc ifxg ifxc)

Nanotechnology is the ability to measure, see, predict and make things on the extremely small scale of atoms and molecules. Materials created with nanotechnology can often be made to exhibit very different physical, chemical, and biological properties than their normal size counterparts.

“No information” Condition

The potential benefits of nanotechnology include the use of nanomaterials in products to make them stronger, lighter and more effective. Some examples are food containers that kill bacteria, stain-resistant clothing, high performance sporting goods, faster, smaller computers, and more effective skincare products and sunscreens. Nanotechnology also has the potential to provide new and better ways to treat disease, clean up the environment, enhance national security, and provide cheaper energy.

While there has not been conclusive research on the potential risks of nanotechnology, there are concerns that some of the same properties that make nanomaterials useful might make them harmful. It is thought that some nanomaterials may be harmful to humans if they are breathed in and might cause harm to the environment. There are also concerns that invisible, nanotechnology-based monitoring devices could pose a threat to national security and personal privacy.

“Information Exposed Condition”

Figure 1. Short form culture scales. Short forms for Individualism-communitarianism (Cronbach’s α = 0.76) and Hierarchy-egalitarianism (Cronbach’s α = 0.84), each of which consists of six items loading on orthogonal principal components.

GWREAL GWHUMAN NUKE GUN Step 1 Step 2 Step 1 Step 2 Step 1 Step 2 Step 1 Step 2 Most Expert Scientists Disagree Male (vs. Female) .39 (.19) .00 (.20) .21 (.18) -.17 (.19) -.81 (.15) -.70 (.15) -.80 (.16) -.62 (.16)

White (vs. Black) .01 (.37) -1.07 (.41) -.07 (.31) -1.04 (.34) .07 (.24) .35 (.25) .12 (.26) .67 (.28)

Nonwhite (vs. Black) .07 (.41) -.72 (.44) .05 (.35) -.62 (.37) .09 (.28) .30 (.29) .57 (.31) .97 (.32)

Age .00 (.01) -.01 (.01) .00 (.01) -.01 (.01) .00 (.01) .00 (.01) .00 (.01) .01 (.01)

Household Income .06 (.03) .02 (.03) .05 (.03) .02 (.03) -.05 (.03) -.04 (.03) -.03 (.03) -.01 (.03)

Education -.13 (.07) -.09 (.07) -.19 (.07) -.13 (.07) -.01 (.06) -.04 (.06) .18 (.06) .14 (.06)

No Religion (vs. some) .28 (.27) .33 (.28) -.34 (.26) -.32 (.27) .16 (.20) .13 (.20) .36 (.22) .36 (.22)

Church Attendance .19 (.08) .17 (.08) .13 (.07) .12 (.08) -.08 (.07) -.06 (.07) -.06 (.07) -.05 (.07)

Democrat (vs. Repub) -.26 (.23) -.17 (.24) -.20 (.23) -.07 (.24) .15 (.21) .10 (.21) .19 (.21) .10 (.22)

Ind. (vs. Repub) .35 (.35) .44 (.37) .51 (.33) .57 (.37) -.10 (.35) -.15 (.35) -.75 (.36) -.78 (.37)

Other Party (vs. Repub) -1.23 (.32) -.76 (.35) -.93 (.28) -.36 (.31) .28 (.24) .10 (.24) .79 (.24) .37 (.25)

Lib => Conservative .87 (.11) .41 (.13) .77 (.10) .30 (.11) -.25 (.09) -.07 (.10) -.64 (.09) -.33 (.10)

Hierarch 1.16 (.70) .49 (.61) .10 (.42) -.65 (.47)

Individ .24 (.75) -.20 (.63) .50 (.42) -.37 (.47)

Hierarch x Individ .05 (.13) .16 (.11) -.11 (.08) -.02 (.09)

Expert Scientists Divided Male (vs. Female) .29 (.13) .00 (.00) .17 (.13) -.04 (.13) -.57 (.14) -.49 (.14) -.74 (.14) -.60 (.15)

White (vs. Black) .19 (.22) .06 (.14) .08 (.20) -.42 (.21) .25 (.23) .42 (.24) -.14 (.25) .28 (.27)

Nonwhite (vs. Black) -.13 (.26) -.35 (.23) -.11 (.24) -.42 (.24) .10 (.27) .25 (.27) .15 (.30) .46 (.31)

Age .01 (.00) -.49 (.26) .00 (.00) .00 (.00) .00 (.00) .00 (.00) .00 (.00) .01 (.01)

Household Income .03 (.02) .00 (.00) .02 (.02) .00 (.02) -.05 (.02) -.05 (.02) -.01 (.02) .00 (.02)

Education -.10 (.05) .01 (.02) -.07 (.05) -.02 (.05) .04 (.05) .03 (.05) .13 (.05) .11 (.05)

No Religion (vs. some) .31 (.17) -.06 (.05) .10 (.16) .14 (.17) .32 (.19) .31 (.19) .48 (.20) .49 (.21)

Church Attendance .13 (.06) .39 (.18) .06 (.06) .06 (.06) .02 (.06) .03 (.06) -.03 (.06) -.03 (.06)

Democrat (vs. Repub) -.36 (.17) .13 (.06) -.47 (.18) -.32 (.19) .06 (.18) .05 (.18) -.02 (.18) -.04 (.18)

Ind (vs. Repub) -.09 (.29) -.25 (.18) -.43 (.31) -.35 (.33) .12 (.28) .08 (.28) -.45 (.29) -.45 (.29)

Other Party (vs. Repub) -.90 (.19) -.05 (.31) -1.08 (.20) -.66 (.21) -.08 (.21) -.14 (.22) .18 (.22) -.03 (.23)

Lib => Conservative .48 (.07) -.51 (.21) .41 (.07) .11 (.08) -.23 (.08) -.13 (.09) -.42 (.08) -.21 (.09)

Hierarch .17 (.09) .35 (.36) .42 (.39) -.42 (.45)

Individ -.10 (.40) .06 (.35) .73 (.40) -.14 (.45)

Hierarch x Individ -.45 (.40) .09 (.07) -.14 (.08) -.02 (.08)

Log likelihood ratio χ2 387.80 534.85 345.84 503.49 101.71 127.98 284.68 348.33 G-test (Δ likelihood ratio χ2) 147.05 157.65 26.27 63.65

Table 1. Multinomial regression analysis of influences on perceptions of expert consensus. N = 1500. Outcome variable is three-response measure: “most expert scientists agree,” “most expert scientists disagree,” and “scientists are divided.” Predictor estimates are multinomial logit coefficients. Standard errors are in parentheses. The regression coefficients indicate the contribution each predictor variable makes to the likelihood that a subject will select “most expert scientists disagree” or “scientists are divided,” respectively, as opposed to “most scientists agree.” Bolded typeface indicates predictor coefficient, model χ2, or G-statistic (incremental change in model χ2 associated with additional predictors) is statistically significant at p < 0.05.

Global Warming Nuclear Waste Disposal Concealed Carry Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 Risk (0=low risk, 1=high) -.31 (.09) -.32 (.09) 8.72 (2.78) .40 (.09) .40 (.09) 2.41 (2.75) -.47 (.09) -.47 (.09) 1.57 (2.69)

Male (vs. Female) -.21 (.10) -.18 (.10) -.07 (.10) .00 (.10) -.07 (.10) -.12 (.10)

White (vs. Black) -.22 (.15) -.07 (.16) .11 (.16) .19 (.16) .13 (.15) .09 (.16)

Nonwhite (vs. Black) -.04 (.18) .23 (.18) -.02 (.18) .05 (.18) .14 (.18) .07 (.18)

Age .00 (.00) .00 (.00) .00 (.00) .00 (.00) -.01 (.00) -.01 (.00)

Household Income .01 (.02) .01 (.02) -.02 (.01) -.01 (.02) .03 (.02) .02 (.02)

Education .02 (.04) -.01 (.04) .05 (.04) .02 (.04) -.05 (.04) -.03 (.04)

No Religion (vs. some) -.15 (.12) -.09 (.13) .05 (.13) .06 (.13) -.13 (.12) -.08 (.13)

Church Attendance -.06 (.04) -.07 (.04) -.04 (.04) -.04 (.04) .00 (.04) -.04 (.04)

Democrat (vs. Repub) .16 (.14) .01 (.14) .17 (.13) .18 (.13) .10 (.13) .07 (.14)

Independent (vs. Repub) .28 (.22) .31 (.22) .38 (.22) .25 (.21) .59 (.23) .53 (.24)

Other Party (vs. Repub) .25 (.14) .23 (.15) .30 (.15) .33 (.15) .30 (.15) .37 (.15)

Liberal => Conservative .05 (.06) .11 (.07) .08 (.05) .14 (.06) -.02 (.05) .00 (.06)

Hierarch .20 (.37) .03 (.36) .25 (.38)

Individ -.17 (.36) -.15 (.35) -.02 (.37)

Hierarch x Individ .16 (.07) .07 (.07) .14 (.07)

Hierarch x Risk -.47 (.54) .00 (.53) -.92 (.52)

Individ x Risk .24 (.53) .61 (.52) -.54 (.51)

Hierarch x Individ x Risk -.32 (.10) -.20 (.10) -.16 (.10)

LR χ2 11.20 29.74 618.72 18.50 31.60 172.69 25.84 46.33 499.60

G-test (delta LR χ2) 18.54 588.98 13.10 141.09 2.49 453.27

Table 2. Ordered logistic regression analysis of experiment results. N = 1500. Outcome variables are 6-point measure of disagreement-agreement with the statement that “I believe the author is a trustworthy and knowledgeable expert on” the indicated issue. Predictor estimates are logit coefficients. Standard errors are in parentheses. Bolded typeface indicates predictor coefficient, model χ2, or G-statistic (incremental change in model χ2 associated with additional predictors) is statistically significant at p < 0.05

0.1

.2.3

.4D

ensi

ty

1 2 3 4 5 6 7republican


Pop. Mean


7Strong

Republican

6Republican

5Leans

Republican

3Leans

Democrat

2

Democrat

1Strong

Democrat

4Ind.,

Other

-1 SD +1 SD

0.1

.2.3

.4D

ensi

ty

1 2 3 4 5 6 7XIDEO: Political Ideology



1Extremely

Liberal

2Liberal

3Slightly Liberal

7Extremely

Conserv

6Conserv

5SlightlyConserv

4MiddleRoad

Pop. Mean-1 SD +1 SD

No. correct on science literacy/numeracy

01

23

45

67

89

10

0 3 6 9 12 15 18 21n_scinum

n_gw lowess n_gw n_scinum

clim

ate

chan

ge ri

sk p

erce

ptio

n

01

23

45

67

89

10

0 3 6 9 12 15 18 21n_scinum

n_gw Fitted values

-2-1

01

23

-4 -2 0 2ifac

hfac lowess hfac ifac

-4-2

02

0 1 2 3 4 5 6 7n_conservative

ifac lowess ifac n_conservative

Cultural worldviews, liberal-conserv ideology

-2-1

01

23

0 1 2 3 4 5 6 7n_conservative

hfac lowess hfac n_conservative

01

23

45

67

89

1011

-2 -1 0 1 2hfac

n_gw lowess n_gw hfac

01

23

45

67

89

1011

1 2 3 4 5 6 7n_conservative

n_gw lowess n_gw n_conservative

Climate change risk perceptions by ideology/culture

05

1015

20

-2 -1 0 1 2 3hfac

n_scinum lowess n_scinum hfac

02

46

8

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14n_num

n_scilit lowess n_scilit n_num

05

1015

20

-4 -2 0 2ifac

n_scinum lowess n_scinum ifac

05

1015

20

-4 -2 0 2ifac

n_scinum lowess n_scinum ifac

Science literacy/numeracy

01

23

45

67

89

1011

low

ess

n_gw

hfa

c

-2 -1 0 1 2 3hfac

lowess n_gw hfac lowess n_gw hfac

01

23

45

67

89

1011

lowess n_gw hfac

-2 -1 0 1 2 3hf ac

low e ss n _gw hfa c low e ss n _gw hfa c

01

23

45

67

89

1011

lowess n_gw ifac

-4 -2 0 2ifac

lowess n_gw ifac lowess n_gw ifac

01

23

45

67

89

1011

lowes

s n_

gw if

ac

-4 -2 0 2ifac

lowess n_gw ifac lowess n_gw ifac

hierarchy

individualism

Interactions


study_validity cc_risk

-0.50

-0.25

0.00

0.25

0.50

control pol geo

main

main

-0.50

-0.25

0.00

0.25

0.50

control pol geo

main

main


Combined, US/UK

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

control pol geo

HI

EC

main

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

control pol geo

HI

EC

main

anti-pollutioncontrol geoengineering anti-pollutioncontrol geoengineering

study_validity cc_risk

-1.20

-0.80

-0.40

0.00

0.40

0.80

1.20


HI

EC

overall

Hierarch Individ

Egal Commun

-1.20

-0.80

-0.40

0.00

0.40

0.80

1.20


HI

EC

overall“Main effect”

-1.20

-0.80

-0.40

0.00

0.40

0.80

1.20


HI

EC

overall

Combined, US/UK

-1.00

-0.50

0.00

0.50

1.00

antipol geo

hi

ecHierarch individ

Egal communst

udy_

valid

ity

Anti-pollution Geoengineering

Credit

Dismiss

Nanotechnology is the ability to measure, see, predict and make things on the extremely small scale of atoms and molecules. Materials created with nanotechnology can often be made to exhibit very different physical, chemical, and biological properties than their normal size counterparts.

“No information” Condition

The potential benefits of nanotechnology include the use of nanomaterials in products to make them stronger, lighter and more effective. Some examples are food containers that kill bacteria, stain-resistant clothing, high performance sporting goods, faster, smaller computers, and more effective skincare products and sunscreens. Nanotechnology also has the potential to provide new and better ways to treat disease, clean up the environment, enhance national security, and provide cheaper energy.

While there has not been conclusive research on the potential risks of nanotechnology, there are concerns that some of the same properties that make nanomaterials useful might make them harmful. It is thought that some nanomaterials may be harmful to humans if they are breathed in and might cause harm to the environment. There are also concerns that invisible, nanotechnology-based monitoring devices could pose a threat to national security and personal privacy.

“Information Exposed Condition”

watch in slide show mode to observe (modest) animation. comments questions: dan.kahan@yale

Documents

cultural cognition of

cultural availabilityc

nature nanotechnology

cultural dual process

benefitsother risk perceptions

climate change risk

balanced information

science communication