Supplementary Material
Political orientation and climate concern shape visual attention to climate change
Jennifer C. Whitman1,2, Jiaying Zhao1.3, Kevin H. Roberts1, & Rebecca M. Todd1
1Department of Psychology, University of British Columbia2Department of Psychology, Northwestern University
3Institute for Resources, Environment and Sustainability, University of British Columbia
Corresponding Author. Please address all correspondence to Jennifer C. Whitman, PhD, Department of Psychology at Northwestern University, 102 Swift Hall, 2029 Sheridan Rd, Evanston IL USA, 60208-2710, e-mail: [email protected].
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List of Climate-Related Words Used as Targets: gasoline, oil, storm, extreme, resources,
hurricane, melting, global, flooding, CO2, carbon, warming, climate, drilling, habitats, ozone,
typhoon, drought, footprint, pollution, dioxide, wildfire, rainstorm, glacier, emissions, depletion,
hydrocarbon, earth.
List of Neutral Words Used as Targets: collection, equivalent, decorate, calculator, direction,
container, machinery, intuition, geography, bookshelf, shop, paint, download, optional, overalls,
tutelage, bottle, hammer, pencil, sleeve, mixing, kettle, packet, puddle, lower, cable, upper, lock.
Note. Each target word appeared twice in the full experiment, with the ordering of trials
randomized. This allowed for 56 trials from each word category.
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Supplemental Fig. S1. Histogram depicting how participants in Experiment 1 vary in the
magnitude of AB sparing at Lag 1. A positive value on the x-axis represents AB sparing for
Climate-Related words, while a negative value represents suppression of Climate-Related
information, relative to Neutral words.
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Supplementary Fig. S2. Scree Plot from Principal Component Analysis in Experiment 2
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Supplemental Fig. S3. Histogram depicting how participants in Experiment 2 vary in the
magnitude of AB sparing. A positive value on the x-axis represents AB sparing for Climate-
Related words, while a negative value represents suppression of Climate-Related information,
relative to Neutral words.
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Rationale for Samples Sizes and Analyses of Statistical Power in Experiments 1 and 2
In planning and running Experiment 1, we aimed to schedule N = 100 participants, based
on a rule of thumb, employed by social psychologists, that N = 80 participants is a bare minimum
for any correlational analysis of individual differences. N = 95 of our participants kept their
appointments and participated in the Experiment. We considered N = 500 to be a bare minimum
for identifying individual differences in a community sample, with wider variability in age,
education level, health, intelligence, visual acuity, and reading speed in a study with multiple
predictors. At the time of the study design, we had expected to identify multiple orthogonal
principal components each accounting for substantial portions of the variance in the survey data,
rather than the single dominant principal component identified in our results (see Fig. S2). These
general rules of thumb consider not only statistical power, discussed in more detail below, but
also the consideration that a sample should be large enough to have a reasonable chance of being
representative of the population about which inferences are made. Thus, our rules of thumb
prescribe larger samples for the more diverse populations in the general community.
Here, using G-Power software, we report a series of [post-hoc] power analyses to
examine the sample sizes we would need to detect different sizes of population effects at the p
< .05 level (two-tailed). This is in keeping with an approach suggested by O’Keefe (O'Keefe
2007). Detecting a population correlation of ρ = .10 would require a sample of at least N = 1293.
For a population correlation of ρ = .20, we would require a sample of at least N = 319; for a
population correlation of ρ = .30, a sample of at least N = 138; for a population correlation of ρ =
.40, a sample of at least N = 75; and, for a population correlation of ρ = .50 we would require a
sample of at least N = 46.
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Based on the observed correlation of r = .19 in Experiment 1, we conducted a power
analysis which suggested that a sample of N = 354 would be necessary to detect the effect in
Experiment 2 (assuming a population correlation of ρ = .19). This indicates that our sample of N
= 578 in Experiment 2 was adequate.
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Supplemental Table S1. Correlations between survey variables and AB sparing at Early Lags.
Criterion Variable from SurveyCorrelation
Coefficient r p-value
Human Caused (Supplemental Material Q 29) .030 .466
Climate Urgency (Supplemental Material Q 30) .012 .771
Climate Effects Vancouver Gen Area (Supplemental Material Q 33) .123** .003
Climate Effects Canada (Supplemental Material Q 34) .189** .000
Climate Effects Continent (Supplemental Material Q 35) .164** .000
Climate Effects World (Supplemental Material Q 36) .204** .000
Slope Climate Effects Geog. (slope from SM Q 33 to 36 above) .193** .000
Climate Effects 5years (Supplemental Material Q 37) .056 .179
Climate Effects 25years (Supplemental Material Q 38) .120** .004
Climate Effects 50years (Supplemental Material Q 39) .127** .002
Climate Effects 100years (Supplemental Material Q 40) .160** .000
Slope Climate Effects Time (calculated from above questions) .162** .000
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ABQ2 negative impact likelihood (end of AB Task in Cogent, Q 2) .074 .074
Age (Supplemental Material Q 2) .057 .170
Years Here (Supplemental Material Q 6) -.007 .863
Income (Supplemental Material Q 7) .052 .212
Income Percentile (calculated from above, Q 7) .079 .057
Schooling Level General (Supplemental Material Q 10) .066 .114
Schooling Level Math (Supplemental Material Q 11) -.011 .787
Longest Stay in One Town (Supplemental Material Q 13) .081 .052
Transit Frequency (transit never/rarely/sometimes/daily) -.030 .470
Bike Frequency (bike never/rarely/sometimes/daily) .090* .031
Child’s Age Category (<6, 6-10, 11-14, 15-17, 18+) .041 .328
Grandchild’s Age Category (<6, 6-10, 11-14, 15-17, 18+) -.037 .380
Subjective Independence (Supplemental Material Q 25) .047 .263
Anxiety General (Supplemental Material Q 26) .001 .989
Work Outdoors (Supplemental Material Q 20) .023 .587
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Subjective Climate Knowledge (Supplemental Material Q 27) .051 .219
Enviro Concern Friends & Family (Supplemental Material Q 31) .079 .058
Climate Concern Friends & Family (Supplemental Material Q 32) .097* .020
Environmental Concern (Supplemental Material Q 28) .115** .006
Political or Not (Supplemental Material Q 23) .052 .216
Political Debater (Supplemental Material Q 22) .068 .100
Politics Self Left vs. Right (Supplemental Material Q 41) -.014 .739
Politics Friends & Fam Left vs. Right (Supplemental Material Q 24) -.062 .138
BC Liberal (Supplemental Material Q 42) -.038 .363
BC NDP (Supplemental Material Q 43) .060 .149
BC Green (Supplemental Material Q 44) .073 .080
BC SoCred (Supplemental Material Q 45) -.046 .270
CDN Liberal (Supplemental Material Q 46) -.032 .436
CDN NDP (Supplemental Material Q 47) .047 .258
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CDN Green (Supplemental Material Q 48) -.045 .276
CDN Conservative (Supplemental Material Q 49) -.104* .012
Religious Y/N and Involvement (Supplemental Material Q 15a, 15c) .021 .608
* p < .05, uncorrected** p < .01, uncorrected
Note that the ‘Politics Self Left vs. Right (Supplemental Material Q 41)’ variable has lower variance, relative to support for the ‘CDN Conservative’ party, due to a programming error on the first version of the survey made in psychoPy, which made it necessary to exclude that question for N = 119 participants. These missing values were replaced by the mean from the remaining participants. Left vs. Right-wing political orientation did correlate strongly with several questions indexing environmental concern, as can be seen in the Supplementary spreadsheet CorrCoefoutputs for Supplemtary Materials.xlsx, posted on figshare at https://figshare.com/s/9ff3587724cb8faf799c
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List of key survey questions in Experiment 2
1. Please specify your gender (gender identity even if different from biological sex).
Male / Female / Other – please specify
2. Please specify your age.
3. What country do you live in?
Canada / Other – please specify
4. What city do you live in?
5. What languages can you speak fluently?
6. How long have you been in the Vancouver General Area?
I'm just visiting / I've lived here less than a month / I've lived here less than a
year / I've lived here more than a year / I've lived here more than 5 years / I've
lived here more than 10 years
7. What is your approximate annual income (before taxes)?
8. What is your current occupation?
9. Which of the following jobs or industries have you worked in?
retail / food service / tourism / forestry / mining / oil or natural gas / education /
health / transportation / shipping / film or animation / programming or IT / mid-
level management, general office admin or clerical / Other – please specify
10. What is the highest level of schooling you've completed?
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some highschool / completed highschool / 1 year post-secondary / 2 years post-
secondary / Bachelor's degree / Master's degree / [Ph.D./M.D./J.D./LL.D.]
11. What is the highest level of schooling you've completed in math or statistics?
grade 10 / grade 11 / grade 12 / 1st year college/university / 2nd year
college/university / 3rd year university / 4th year university / graduate school
course
12. Please list several cities/towns you've lived in that have had an effect on who you are
(minimum of one place).
13. What is the longest time you've spent living in one town or city?
less than 5 years / between 5 and 10 years / between 10 and 20 years / more than
20 years
14. Please list any terms you feel describe your nationality, heritage, and culture. Be
specific. Some examples include:
Chinese Canadian, family mostly from Canton province & Hong Kong
African American
Canadian, probably mostly European ancestors
half Scottish, half Japanese
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15. Do you have a religion?
Yes / No
[If yes] 15b. : What is your religion?
[If yes] 15c. How often do you participate in activities with your religious community,
such as going to a church/mosque/synagogue/temple?
not applicable - no religion / less than once a year / a few times a year / almost
every week / more than once a week
16. Do you have children?
Yes / No
[If yes] 16b. How old are your children?
17. Do you have grandchildren?
Yes / No
[If yes] 17b. Please specify the age of your youngest grandchild.
18. Do you own property?
Yes / No
[If yes] 18b. Please specify the location(s) of your property (or properties) by naming the
nearest intersection(s).
[coded for vertical distance from sea level. No street addresses recorded, in
order to protect confidentiality]
[If yes] 18c. Do you plan to sell your property soon?
never; it'll be inherited / probably someday / in the next few years / as soon as
possible
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19. Please list your favourite news sources (e.g. CNN, The Province, etc…).
20. Does your job require you to work outdoors?
never / rarely / sometimes / almost always
21. Are you Canadian, planning to become Canadian, or planning to live a long time in
Canada?
Yes / No
22. Do you enjoy debating political issues?
not at all, never / somewhat, sometimes / yes, very much
Likert Scale Questions
23. Are you interested in politics?
not at all:
I don’t care
not very
interested
somewhat
interested
very
interested
extremely
interested
24. Politically, would you describe your close friends and family as
very
left-wing
on average
somewhat
left-wing
on average
evenly
mixed
somewhat
right-wing
on average
very
right-wing
on average
25. Do you consider yourself an independent thinker?
strongly
disagree
disagree maybe agree strongly
agree
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26. Do you tend to be an anxious person?
strongly
disagree
disagree maybe agree strongly
agree
27. How well-informed are you about climate change?
I know almost
nothing about
it
I know a little bit
about it
I’m somewhat
well-informed
I’m very well-
informed
I’m an expert
28. How concerned are you about the environment in general?
not at all
concerned
a tiny bit
concerned
somewhat
concerned
very concerned extremely
concerned
29. Do believe that the climate is being changed by human activity (i.e. carbon emissions)?
impossible very
unlikely
unlikely maybe likely very
likely
certain
30. Do you think climate change will get harder to prevent or slow down the longer we wait
to deal with it?
strongly
disagree
disagree don’t know agree strongly
agree
31. How concerned are your close friends and family about the environment in general?
not at all
concerned
a tiny bit
concerned
somewhat
concerned
very concerned extremely
concerned
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32. How concerned are your close friends and family about climate change?
not at all
concerned
a tiny bit
concerned
somewhat
concerned
very concerned extremely
concerned
33. How likely is it that people in the Vancouver General Area and Fraser Valley will be
negatively affected by climate change?
impossible very
unlikely
unlikely maybe likely very
likely
certain
34. How likely is it that people in Canada will be negatively affected by climate change?
impossible very
unlikely
unlikely maybe likely very
likely
certain
35. How likely is it that people on this continent will be negatively affected by climate
change?
impossible very
unlikely
unlikely maybe likely very
likely
certain
36. How likely is it that people anywhere in the world will be negatively affected by climate
change?
impossible very
unlikely
unlikely maybe likely very
likely
certain
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37. How likely is it that people will be negatively affected by climate change in the next 5
years?
impossible very
unlikely
unlikely maybe likely very
likely
certain
38. How likely is it that people will be negatively affected by climate change in the next 25
years?
impossible very
unlikely
unlikely maybe likely very
likely
certain
39. How likely is it that people will be negatively affected by climate change in the next 50
years?
impossible very
unlikely
unlikely maybe likely very
likely
certain
40. How likely is it that people will be negatively affected by climate change in the next 100
years?
impossible very
unlikely
unlikely maybe likely very
likely
certain
41. Politically, would you describe yourself as left-wing or right-wing?
far left socialist New
Democratic
Party of
Canada
Liberal
Party of
Canada
Conservative
Party of
Canada
USA
Tea
Party
far right
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If you didn't have to choose only one party to vote for in BC PROVINCIAL elections, and
instead you could support and rate several parties at once, how would you rate each of these
parties?"
42. Liberal Party of BC
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
43. New Democratic Party of BC
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
44. Green Party of BC
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
45. Social Credit Party (formerly) of BC
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
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If you didn't have to choose only one party to vote for in CANADIAN FEDERAL elections,
and instead you could support and rate several parties at once, how would you rate each of
these parties?"
46. Liberal Party of Canada
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
47. New Democratic Party of Canada
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
48. Green Party of Canada
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
49. Conservative Party of Canada
strongly
oppose
mildly oppose neutral mildly
support
strongly
support
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Questions with Check-box Options
50. Have you been personally affected by a natural disaster (e.g. forest fire, mud/land slide,
flood, storm surge)?
Yes / No
[If yes] 36b. Which natural disaster(s) have personally affected you? Please check all
that apply.
forest fire / mud slide / land slide / river flood / ocean flood, e.g. storm surge
51. Have any of your close friends or family members been affected by a natural disaster
(e.g. forest fire, mud/land slide, flood, storm surge)?
Yes / No
[If yes] 37b. Which natural disaster(s) have affected your close friends or family
members? Please check all that apply.
forest fire / mud slide / land slide / river flood / ocean flood, e.g. storm surge
52. Have any members of your community been affected by a natural disaster (eg.. forest
fire, mud/land slide, flood, storm surge)?
Yes / No
[If yes] 38b. Which natural disaster(s) have affected your community? Please check all
that apply.
forest fire / mud slide / land slide / river flood / ocean flood, e.g. storm surge
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References
O'Keefe DJ (2007) Brief report: post hoc power, observed power, a priori power, retrospective
power, prospective power, achieved power: sorting out appropriate uses of statistical
power analyses. Communication methods and measures 1:291-299
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