Method

Participants completed the following blocks in a random order: (1) Value priorities and ratings and (2) randomly ordered attitude scales (anti-establishment, confidence in democratic institutions, and support for change). Then, they indicated their ideologies and completed a demographic questionnaire.

In the priorities block, they first indicated their perceived priorities of the US on paper (like the constitution). Then, they indicated their own priorities if they were to design a country from scratch (and be randomly born into it). And then, for each value, they indicated on a 0-100 scale the extent to which they believe the US provides this value (regardless of party).

In the scales block, they just completed some randomly ordered likert scales.

Demographics

Race

race N Perc
asian 30 7.50
black 48 12.00
hispanic 23 5.75
multiracial 21 5.25
white 272 68.00
NA 6 1.50

Gender

gender N Perc
man 231 57.75
woman 168 42.00
NA 1 0.25

Education

edu N Perc
GED 113 28.25
2yearColl 44 11.00
4yearColl 179 44.75
MA 43 10.75
PHD 14 3.50
NA 7 1.75

Income

Age

m sd
36.85 10.22

Political ideology

County-level data

We also asked them which county they live in. And then, with census data, we got their county’s GINI coefficient, median income, and population density.

GINI

Median income

Population density

Measures

US on paper

Participants were shown the following prompt:

First, we want you to think of the United States.

Since its independence and onwards, the formation of the US as a sovereign country was based on a number of values, all of which were inscribed in the constitution. This document, importantly, has evolved since its inception.

ON PAPER (in the constitution), what are the values that the US stands for? We want you to indicate the United State’s priorities ON PAPER.

To that end, you have a sum of 100 points. Please allocate those points to the following values based on how important you think they are to the US ON PAPER.

The values, presented in alphabetical order, are: Capitalism, Compassion, Equality, Freedom, Happiness, National Pride, Progress, and Security.

So, If you think a certain value is more important than another value, then the first value would get more points than the second. If you think a certain value is not important at all, it would get zero points. Must total 100 points.

value mean_weight
capitalism 13.72
compassion 8.00
equality 15.31
freedom 24.42
happiness 10.21
nationalpride 8.24
progress 8.26
security 11.84

By ideology

I’ll categorize anyone who is over 50 on a certain ideology as part of that ideological group.

value con demsoc lbrtn lib prog rwn
capitalism 13.49 13.50 16.53 12.79 14.20 13.50
compassion 8.06 8.03 8.21 8.39 8.35 9.05
equality 13.42 16.45 13.53 16.55 14.34 11.86
freedom 24.68 23.31 21.08 23.62 22.63 23.43
happiness 10.66 10.12 10.44 10.21 9.84 11.40
nationalpride 9.33 8.35 9.08 8.65 9.08 9.55
progress 8.24 8.75 8.50 8.88 9.93 8.88
security 12.13 11.49 12.64 10.92 11.63 12.33

Ideal

Participants were shown the following prompt:

Now, we want you to imagine your ideal country.

Importantly, imagine this ideal state as if you are randomly born into its population. You can end up in any level of its citizenry.

So, if you could design a country completely from scratch and write its constitution, what would be its guiding values?

To that end, you have a sum of 100 points. Please allocate those points to the following values based on how important they are TO YOU.

The values, presented in alphabetical order, are: Capitalism, Compassion, Equality, Freedom, Happiness, National Pride, Progress, and Security.

So, If you think a certain value is more important than another value, then the first value would get more points than the second. If you think a certain value is not important at all, it would get zero points. Must total 100 points.

value mean_weight
capitalism 6.70
compassion 12.48
equality 18.10
freedom 20.99
happiness 14.28
nationalpride 5.02
progress 10.77
security 11.67

By ideology

value con demsoc lbrtn lib prog rwn
capitalism 11.64 4.09 10.30 4.87 4.89 11.69
compassion 9.91 14.53 11.11 14.71 13.57 8.07
equality 12.38 22.34 14.74 21.13 21.09 11.62
freedom 22.84 17.67 21.91 18.24 17.98 22.26
happiness 12.98 15.11 13.70 14.89 15.24 13.45
nationalpride 7.95 3.73 7.21 4.15 4.33 10.02
progress 8.92 12.73 9.67 11.84 12.89 9.00
security 13.38 9.80 11.36 10.17 10.01 13.88

US in Practice

We then asked participants to indicate the extent to which they think the US provides each of these values. They were shown the following prompt:

Now, please indicate the extent to which the US government, regardless of party, is providing each of these values, IN PRACTICE.

In the scale below, 0 means that the US does not provide what this value stands for at all (it cannot get any worse) and 100 means that the US does provide what this value stands for to a great extent (it cannot get any better).

By ideology

value con demsoc lbrtn lib prog rwn
capitalism 62.69 73.20 67.91 71.99 72.62 56.40
compassion 38.91 25.98 36.44 26.38 26.86 44.45
equality 49.06 30.89 40.94 31.83 32.04 49.76
freedom 57.82 49.21 54.82 51.48 50.67 53.55
happiness 46.46 27.66 43.58 30.62 31.68 47.38
nationalpride 48.92 52.02 52.50 53.03 53.08 47.14
progress 50.40 36.79 47.67 39.20 38.28 51.36
security 60.83 55.53 62.97 56.58 56.02 55.40

Anti-establishment

A combination of items from ISPP international surveys (used here: https://www.cogitatiopress.com/politicsandgovernance/article/viewFile/3949/3949) and a recent IPSOS survey (https://www.ipsos.com/en/broken-system-sentiment-2022).

Participants indicated their agreement (1-7) with the following statements:

1. The US’s economy is rigged to advantage the rich and powerful
2. Traditional politicians and parties don’t care about people like me
3. Experts in this country don’t understand the lives of people like me
4. Most of the time we can trust people in the government to do what is right (R)

R indicates a reverse-scored item

Cronbach’s alpha = 0.788

Confidence in Democratic Institutions

These items were taken from the World Values Survey.

Participants indicated how confident they are (1-5) in the following institutions:

1. Justice System / Courts
2. The Government
3. Congress

Cronbach’s alpha = 0.89

Support for change

Items used here (https://journals.sagepub.com/doi/epub/10.1177/0032321719874362), but also appears, in various forms, in other surveys (including the WVS).

Participants indicated their agreement (1-7) with the following items:

change_rad: The way this country works needs to be radically changed.
change_grad: Our society must be gradually improved by reforms.
change_def: Our present society must be valiantly defended against all subversive forces.

“Values Met” scores

With participants’ indication of priorities for the US on paper, their own ideal priorities, and the extent to which they believe the US provides each of the values, we can create a weighted “values met” score per participant per perspective.

What we’ll do is weigh every US In Practice score by the weight the participant assigned to it and then take that weighted mean. So, for each perspective, we’ll have a score of 0-100 that takes into account what they believe they should get and what they believe they do get.

I’ll leave the code visible for this next part:

df_valuesmet <- df_amd %>% 
  select(PID:security_practice) %>% 
  mutate(weighted_score = case_when(value == "capitalism" ~ weight*capitalism_practice/100,
                                    value == "compassion" ~ weight*compassion_practice/100,
                                    value == "equality" ~ weight*equality_practice/100,
                                    value == "freedom" ~ weight*freedom_practice/100,
                                    value == "happiness" ~ weight*happiness_practice/100,
                                    value == "nationalpride" ~ weight*nationalpride_practice/100,
                                    value == "progress" ~ weight*progress_practice/100,
                                    value == "security" ~ weight*security_practice/100)) %>% 
  select(PID:type,weighted_score) %>% 
  group_by(PID,type) %>% 
  summarise(values_met = sum(weighted_score)) %>% 
  ungroup()
  
df_amd <- df_amd %>% 
  mutate(weighted_score = case_when(value == "capitalism" ~ weight*capitalism_practice/100,
                                    value == "compassion" ~ weight*compassion_practice/100,
                                    value == "equality" ~ weight*equality_practice/100,
                                    value == "freedom" ~ weight*freedom_practice/100,
                                    value == "happiness" ~ weight*happiness_practice/100,
                                    value == "nationalpride" ~ weight*nationalpride_practice/100,
                                    value == "progress" ~ weight*progress_practice/100,
                                    value == "security" ~ weight*security_practice/100)) %>% 
  left_join(df_valuesmet,by = c("PID","type")) 

Great, and now their distributions:

Analysis

Correlation plot

Let’s start with some correlations.

V cool

Linear Models

Predicting anti-establishment sentiment

Main IV: “Values Met” US

JUST VALUES MET

(#tab:unnamed-chunk-28)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
ScalevaluesMet US -0.35 [-0.44, -0.25] -7.34 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-29)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.01 [-0.10, 0.09] -0.10 361 .917
ScalevaluesMet US -0.27 [-0.37, -0.18] -5.57 361 < .001
Scaleideo con -0.19 [-0.28, -0.09] -3.78 361 < .001

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-30)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.17 [-0.32, -0.02] -2.18 359 .030
ScalevaluesMet US -0.27 [-0.36, -0.17] -5.48 359 < .001
Scaleideo con -0.27 [-0.41, -0.14] -3.90 359 < .001
Party idIndependent 0.37 [0.13, 0.61] 3.02 359 .003
Party idRepublican 0.29 [-0.05, 0.63] 1.69 359 .091

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-31)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.34 [-0.76, 0.07] -1.62 309 .105
ScalevaluesMet US -0.24 [-0.35, -0.14] -4.65 309 < .001
Scaleideo con -0.20 [-0.35, -0.05] -2.56 309 .011
Party idIndependent 0.29 [0.03, 0.55] 2.21 309 .028
Party idRepublican 0.18 [-0.19, 0.55] 0.95 309 .342
Scaleage 0.00 [-0.10, 0.11] 0.04 309 .964
Genderwoman -0.03 [-0.25, 0.18] -0.31 309 .757
Scaleedu num -0.07 [-0.18, 0.04] -1.30 309 .193
Scaleincome num -0.20 [-0.32, -0.09] -3.49 309 < .001
Raceblack 0.11 [-0.38, 0.60] 0.45 309 .652
Racehispanic 0.47 [-0.12, 1.05] 1.57 309 .118
Racemultiracial 0.38 [-0.18, 0.94] 1.33 309 .184
Racewhite 0.21 [-0.21, 0.63] 0.99 309 .323
Scalecounty gini -0.01 [-0.15, 0.12] -0.21 309 .830
Scalecounty medianincome -0.04 [-0.15, 0.07] -0.77 309 .443
Scalecounty density 0.04 [-0.09, 0.18] 0.61 309 .541
Orderofblocksvalues first 0.07 [-0.14, 0.27] 0.65 309 .519

Main IV: “Values Met” Ideal

JUST VALUES MET

(#tab:unnamed-chunk-32)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
ScalevaluesMet IDEAL -0.49 [-0.57, -0.40] -11.08 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-33)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.01 [-0.10, 0.08] -0.18 361 .859
ScalevaluesMet IDEAL -0.43 [-0.52, -0.33] -8.66 361 < .001
Scaleideo con -0.08 [-0.17, 0.02] -1.52 361 .129

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-34)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.14 [-0.28, 0.01] -1.86 359 .064
ScalevaluesMet IDEAL -0.41 [-0.51, -0.32] -8.36 359 < .001
Scaleideo con -0.15 [-0.29, -0.01] -2.16 359 .031
Party idIndependent 0.29 [0.06, 0.51] 2.46 359 .014
Party idRepublican 0.24 [-0.09, 0.56] 1.43 359 .154

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-35)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.27 [-0.66, 0.13] -1.33 309 .183
ScalevaluesMet IDEAL -0.39 [-0.50, -0.29] -7.31 309 < .001
Scaleideo con -0.08 [-0.24, 0.07] -1.11 309 .267
Party idIndependent 0.22 [-0.03, 0.46] 1.70 309 .090
Party idRepublican 0.14 [-0.22, 0.50] 0.77 309 .442
Scaleage 0.00 [-0.10, 0.10] 0.03 309 .975
Genderwoman -0.07 [-0.27, 0.14] -0.64 309 .523
Scaleedu num -0.03 [-0.13, 0.07] -0.56 309 .577
Scaleincome num -0.21 [-0.32, -0.10] -3.83 309 < .001
Raceblack 0.01 [-0.45, 0.48] 0.06 309 .955
Racehispanic 0.45 [-0.11, 1.01] 1.59 309 .113
Racemultiracial 0.38 [-0.15, 0.92] 1.40 309 .162
Racewhite 0.19 [-0.21, 0.59] 0.93 309 .353
Scalecounty gini -0.01 [-0.14, 0.11] -0.17 309 .865
Scalecounty medianincome -0.03 [-0.13, 0.07] -0.58 309 .563
Scalecounty density 0.04 [-0.08, 0.17] 0.69 309 .490
Orderofblocksvalues first 0.05 [-0.15, 0.25] 0.50 309 .619

Predicting confidence in democratic institutions

Main IV: “Values Met” US

JUST VALUES MET

(#tab:unnamed-chunk-36)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
ScalevaluesMet US 0.38 [0.29, 0.47] 8.20 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-37)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] -0.02 361 .987
ScalevaluesMet US 0.33 [0.23, 0.42] 6.77 361 < .001
Scaleideo con 0.20 [0.10, 0.29] 4.03 361 < .001

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-38)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.18 [0.03, 0.33] 2.34 359 .020
ScalevaluesMet US 0.32 [0.23, 0.42] 6.69 359 < .001
Scaleideo con 0.30 [0.16, 0.43] 4.25 359 < .001
Party idIndependent -0.40 [-0.63, -0.16] -3.30 359 .001
Party idRepublican -0.33 [-0.67, 0.01] -1.93 359 .054

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-39)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.07 [-1.66, 1.81] 0.08 309 .936
ScalevaluesMet US 0.34 [0.24, 0.44] 6.70 309 < .001
Scaleideo con 0.23 [0.08, 0.38] 3.09 309 .002
Party idIndependent -0.29 [-0.54, -0.03] -2.20 309 .028
Party idRepublican -0.24 [-0.60, 0.13] -1.27 309 .205
Age -0.01 [-0.02, 0.00] -1.32 309 .189
Genderwoman 0.17 [-0.04, 0.38] 1.63 309 .104
Edu num 0.13 [0.03, 0.22] 2.66 309 .008
Income num 0.01 [-0.03, 0.06] 0.57 309 .572
Raceblack -0.10 [-0.58, 0.38] -0.42 309 .678
Racehispanic -0.49 [-1.07, 0.08] -1.69 309 .093
Racemultiracial -0.35 [-0.90, 0.20] -1.26 309 .210
Racewhite -0.24 [-0.65, 0.17] -1.14 309 .253
County gini 1.12 [-2.13, 4.36] 0.68 309 .499
County medianincome 0.00 [0.00, 0.00] -1.30 309 .193
County density 0.00 [0.00, 0.00] -0.17 309 .868
Orderofblocksvalues first -0.27 [-0.47, -0.07] -2.62 309 .009

Main IV: “Values Met” Ideal

JUST VALUES MET

(#tab:unnamed-chunk-40)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.08, 0.08] 0.00 398 > .999
ScalevaluesMet IDEAL 0.52 [0.44, 0.61] 12.21 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-41)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.08, 0.09] 0.07 361 .948
ScalevaluesMet IDEAL 0.49 [0.39, 0.58] 10.01 361 < .001
Scaleideo con 0.08 [-0.02, 0.17] 1.54 361 .124

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-42)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.15 [0.00, 0.29] 2.00 359 .047
ScalevaluesMet IDEAL 0.47 [0.37, 0.57] 9.70 359 < .001
Scaleideo con 0.16 [0.03, 0.30] 2.35 359 .020
Party idIndependent -0.31 [-0.53, -0.08] -2.68 359 .008
Party idRepublican -0.27 [-0.59, 0.05] -1.66 359 .098

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-43)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.10 [-1.53, 1.74] 0.13 309 .900
ScalevaluesMet IDEAL 0.49 [0.38, 0.59] 9.38 309 < .001
Scaleideo con 0.10 [-0.04, 0.25] 1.37 309 .170
Party idIndependent -0.19 [-0.43, 0.05] -1.56 309 .119
Party idRepublican -0.18 [-0.53, 0.16] -1.05 309 .292
Age -0.01 [-0.02, 0.00] -1.39 309 .166
Genderwoman 0.20 [0.01, 0.40] 2.03 309 .043
Edu num 0.08 [-0.01, 0.17] 1.85 309 .066
Income num 0.02 [-0.02, 0.06] 0.89 309 .375
Raceblack 0.04 [-0.41, 0.49] 0.18 309 .859
Racehispanic -0.46 [-1.00, 0.08] -1.67 309 .096
Racemultiracial -0.34 [-0.86, 0.18] -1.29 309 .196
Racewhite -0.20 [-0.59, 0.19] -1.02 309 .307
County gini 1.09 [-1.97, 4.16] 0.70 309 .483
County medianincome 0.00 [0.00, 0.00] -1.61 309 .108
County density 0.00 [0.00, 0.00] -0.23 309 .821
Orderofblocksvalues first -0.24 [-0.43, -0.05] -2.47 309 .014

Predicting support for radical change

Main IV: “Values Met” US

JUST VALUES MET

(#tab:unnamed-chunk-44)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
ScalevaluesMet US -0.25 [-0.34, -0.15] -5.14 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-45)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.02 [-0.12, 0.08] -0.44 361 .663
ScalevaluesMet US -0.18 [-0.28, -0.08] -3.56 361 < .001
Scaleideo con -0.20 [-0.30, -0.10] -3.94 361 < .001

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-46)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.02 [-0.18, 0.14] -0.27 359 .788
ScalevaluesMet US -0.18 [-0.28, -0.08] -3.55 359 < .001
Scaleideo con -0.22 [-0.37, -0.08] -3.00 359 .003
Party idIndependent -0.06 [-0.31, 0.19] -0.48 359 .633
Party idRepublican 0.07 [-0.29, 0.43] 0.39 359 .696

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-47)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.68 [-1.22, 2.58] 0.70 309 .483
ScalevaluesMet US -0.17 [-0.28, -0.06] -3.10 309 .002
Scaleideo con -0.18 [-0.35, -0.02] -2.22 309 .027
Party idIndependent -0.06 [-0.34, 0.22] -0.43 309 .669
Party idRepublican 0.10 [-0.30, 0.50] 0.51 309 .609
Age -0.02 [-0.03, 0.00] -2.81 309 .005
Genderwoman 0.06 [-0.17, 0.29] 0.49 309 .623
Edu num 0.01 [-0.09, 0.11] 0.16 309 .870
Income num -0.06 [-0.10, -0.01] -2.25 309 .025
Raceblack 0.38 [-0.14, 0.91] 1.43 309 .153
Racehispanic 0.34 [-0.29, 0.97] 1.07 309 .286
Racemultiracial -0.06 [-0.66, 0.55] -0.19 309 .851
Racewhite 0.22 [-0.23, 0.67] 0.95 309 .344
County gini -0.36 [-3.92, 3.21] -0.20 309 .844
County medianincome 0.00 [0.00, 0.00] 0.03 309 .973
County density 0.00 [0.00, 0.00] 1.40 309 .163
Orderofblocksvalues first -0.02 [-0.24, 0.20] -0.17 309 .864

Main IV: “Values Met” Ideal

JUST VALUES MET

(#tab:unnamed-chunk-48)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
ScalevaluesMet IDEAL -0.35 [-0.44, -0.25] -7.38 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-49)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept -0.02 [-0.12, 0.07] -0.49 361 .626
ScalevaluesMet IDEAL -0.28 [-0.39, -0.18] -5.32 361 < .001
Scaleideo con -0.13 [-0.23, -0.02] -2.42 361 .016

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-50)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.16, 0.16] 0.00 359 .998
ScalevaluesMet IDEAL -0.29 [-0.39, -0.18] -5.37 359 < .001
Scaleideo con -0.14 [-0.28, 0.01] -1.79 359 .074
Party idIndependent -0.12 [-0.37, 0.13] -0.94 359 .349
Party idRepublican 0.03 [-0.32, 0.38] 0.17 359 .863

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-51)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.60 [-1.25, 2.46] 0.64 309 .523
ScalevaluesMet IDEAL -0.29 [-0.41, -0.17] -4.90 309 < .001
Scaleideo con -0.10 [-0.27, 0.07] -1.19 309 .236
Party idIndependent -0.12 [-0.39, 0.16] -0.84 309 .401
Party idRepublican 0.07 [-0.32, 0.47] 0.37 309 .711
Age -0.02 [-0.03, -0.01] -2.88 309 .004
Genderwoman 0.03 [-0.19, 0.26] 0.28 309 .780
Edu num 0.04 [-0.07, 0.14] 0.71 309 .481
Income num -0.06 [-0.11, -0.01] -2.41 309 .017
Raceblack 0.31 [-0.20, 0.83] 1.20 309 .231
Racehispanic 0.33 [-0.28, 0.95] 1.06 309 .289
Racemultiracial -0.06 [-0.65, 0.54] -0.18 309 .855
Racewhite 0.20 [-0.24, 0.64] 0.91 309 .366
County gini -0.28 [-3.76, 3.20] -0.16 309 .874
County medianincome 0.00 [0.00, 0.00] 0.19 309 .848
County density 0.00 [0.00, 0.00] 1.46 309 .144
Orderofblocksvalues first -0.03 [-0.25, 0.18] -0.29 309 .773

Predicting support for gradual change

Main IV: “Values Met” US

JUST VALUES MET

(#tab:unnamed-chunk-52)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
ScalevaluesMet US -0.11 [-0.21, -0.02] -2.29 398 .023

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-53)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.03 361 .973
ScalevaluesMet US -0.05 [-0.15, 0.05] -0.96 361 .335
Scaleideo con -0.14 [-0.24, -0.04] -2.72 361 .007

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-54)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.13 [-0.04, 0.29] 1.53 359 .126
ScalevaluesMet US -0.06 [-0.16, 0.05] -1.06 359 .289
Scaleideo con -0.05 [-0.19, 0.10] -0.61 359 .544
Party idIndependent -0.19 [-0.44, 0.06] -1.47 359 .142
Party idRepublican -0.33 [-0.69, 0.04] -1.77 359 .078

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-55)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.72 [-1.19, 2.62] 0.74 309 .460
ScalevaluesMet US -0.07 [-0.18, 0.04] -1.23 309 .221
Scaleideo con -0.03 [-0.19, 0.14] -0.32 309 .750
Party idIndependent -0.21 [-0.49, 0.07] -1.45 309 .148
Party idRepublican -0.27 [-0.67, 0.13] -1.34 309 .180
Age -0.01 [-0.02, 0.00] -1.19 309 .236
Genderwoman -0.13 [-0.36, 0.10] -1.11 309 .269
Edu num -0.04 [-0.14, 0.07] -0.68 309 .500
Income num 0.01 [-0.04, 0.05] 0.20 309 .839
Raceblack 0.33 [-0.20, 0.86] 1.23 309 .220
Racehispanic 0.13 [-0.50, 0.76] 0.40 309 .688
Racemultiracial 0.17 [-0.43, 0.78] 0.56 309 .576
Racewhite 0.05 [-0.40, 0.50] 0.23 309 .817
County gini -0.66 [-4.22, 2.91] -0.36 309 .716
County medianincome 0.00 [0.00, 0.00] -0.07 309 .942
County density 0.00 [0.00, 0.00] 1.38 309 .168
Orderofblocksvalues first -0.02 [-0.24, 0.21] -0.14 309 .886

Main IV: “Values Met” Ideal

JUST VALUES MET

(#tab:unnamed-chunk-56)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
ScalevaluesMet IDEAL -0.19 [-0.29, -0.10] -3.91 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-57)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.02 361 .980
ScalevaluesMet IDEAL -0.12 [-0.23, -0.01] -2.15 361 .032
Scaleideo con -0.11 [-0.21, 0.00] -1.91 361 .057

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-58)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.14 [-0.02, 0.30] 1.69 359 .092
ScalevaluesMet IDEAL -0.13 [-0.24, -0.02] -2.36 359 .019
Scaleideo con 0.00 [-0.15, 0.15] 0.01 359 .990
Party idIndependent -0.22 [-0.47, 0.04] -1.69 359 .091
Party idRepublican -0.35 [-0.71, 0.01] -1.90 359 .059

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-59)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.65 [-1.24, 2.53] 0.67 309 .502
ScalevaluesMet IDEAL -0.14 [-0.26, -0.03] -2.41 309 .017
Scaleideo con 0.02 [-0.15, 0.19] 0.23 309 .821
Party idIndependent -0.23 [-0.51, 0.04] -1.66 309 .099
Party idRepublican -0.29 [-0.69, 0.11] -1.43 309 .155
Age -0.01 [-0.02, 0.00] -1.21 309 .228
Genderwoman -0.15 [-0.38, 0.08] -1.26 309 .208
Edu num -0.02 [-0.12, 0.08] -0.38 309 .704
Income num 0.00 [-0.04, 0.05] 0.18 309 .855
Raceblack 0.30 [-0.22, 0.83] 1.14 309 .254
Racehispanic 0.13 [-0.50, 0.76] 0.41 309 .684
Racemultiracial 0.18 [-0.42, 0.78] 0.59 309 .559
Racewhite 0.05 [-0.40, 0.50] 0.22 309 .825
County gini -0.58 [-4.12, 2.96] -0.32 309 .746
County medianincome 0.00 [0.00, 0.00] 0.03 309 .979
County density 0.00 [0.00, 0.00] 1.41 309 .159
Orderofblocksvalues first -0.02 [-0.24, 0.20] -0.17 309 .867

Predicting support for defending the status quo

Main IV: “Values Met” US

JUST VALUES MET

(#tab:unnamed-chunk-60)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
ScalevaluesMet US 0.19 [0.10, 0.29] 3.91 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-61)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.09] -0.05 361 .959
ScalevaluesMet US 0.13 [0.03, 0.23] 2.61 361 .010
Scaleideo con 0.34 [0.24, 0.44] 6.79 361 < .001

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-62)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.10 [-0.06, 0.25] 1.20 359 .230
ScalevaluesMet US 0.13 [0.03, 0.22] 2.53 359 .012
Scaleideo con 0.42 [0.27, 0.56] 5.77 359 < .001
Party idIndependent -0.15 [-0.39, 0.10] -1.17 359 .243
Party idRepublican -0.26 [-0.61, 0.09] -1.46 359 .144

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-63)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.70 [-1.15, 2.55] 0.75 309 .456
ScalevaluesMet US 0.13 [0.02, 0.23] 2.34 309 .020
Scaleideo con 0.41 [0.25, 0.56] 5.03 309 < .001
Party idIndependent -0.10 [-0.37, 0.17] -0.75 309 .456
Party idRepublican -0.19 [-0.58, 0.20] -0.98 309 .330
Age -0.01 [-0.02, 0.00] -1.12 309 .266
Genderwoman 0.03 [-0.20, 0.25] 0.24 309 .812
Edu num 0.01 [-0.09, 0.11] 0.25 309 .800
Income num -0.01 [-0.06, 0.03] -0.53 309 .598
Raceblack 0.24 [-0.27, 0.75] 0.92 309 .359
Racehispanic 0.09 [-0.52, 0.71] 0.30 309 .762
Racemultiracial -0.14 [-0.73, 0.45] -0.47 309 .640
Racewhite -0.16 [-0.60, 0.28] -0.72 309 .475
County gini -0.74 [-4.19, 2.72] -0.42 309 .676
County medianincome 0.00 [0.00, 0.00] -0.04 309 .972
County density 0.00 [0.00, 0.00] 1.47 309 .142
Orderofblocksvalues first 0.00 [-0.21, 0.22] 0.05 309 .964

Main IV: “Values Met” Ideal

JUST VALUES MET

(#tab:unnamed-chunk-64)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
ScalevaluesMet IDEAL 0.28 [0.18, 0.37] 5.76 398 < .001

ADJUSTING FOR CONSERVATISM

(#tab:unnamed-chunk-65)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.09] -0.02 361 .983
ScalevaluesMet IDEAL 0.19 [0.08, 0.29] 3.55 361 < .001
Scaleideo con 0.29 [0.19, 0.40] 5.56 361 < .001

ADJUSTING FOR CONSERVATISM AND PARTY ID

(#tab:unnamed-chunk-66)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.08 [-0.07, 0.24] 1.05 359 .297
ScalevaluesMet IDEAL 0.18 [0.08, 0.28] 3.40 359 < .001
Scaleideo con 0.37 [0.22, 0.51] 4.89 359 < .001
Party idIndependent -0.11 [-0.36, 0.13] -0.90 359 .370
Party idRepublican -0.24 [-0.59, 0.11] -1.34 359 .181

ADJUSTING FOR EVERYTHING ELSE

(#tab:unnamed-chunk-67)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.73 [-1.10, 2.56] 0.79 309 .433
ScalevaluesMet IDEAL 0.19 [0.08, 0.31] 3.32 309 .001
Scaleideo con 0.35 [0.19, 0.51] 4.25 309 < .001
Party idIndependent -0.07 [-0.34, 0.20] -0.48 309 .632
Party idRepublican -0.17 [-0.56, 0.21] -0.88 309 .379
Age -0.01 [-0.02, 0.00] -1.12 309 .263
Genderwoman 0.04 [-0.18, 0.26] 0.37 309 .714
Edu num 0.00 [-0.10, 0.10] -0.09 309 .925
Income num -0.01 [-0.06, 0.04] -0.45 309 .656
Raceblack 0.29 [-0.21, 0.80] 1.13 309 .257
Racehispanic 0.10 [-0.50, 0.71] 0.34 309 .735
Racemultiracial -0.14 [-0.72, 0.44] -0.47 309 .641
Racewhite -0.15 [-0.58, 0.29] -0.67 309 .506
County gini -0.76 [-4.19, 2.66] -0.44 309 .662
County medianincome 0.00 [0.00, 0.00] -0.13 309 .899
County density 0.00 [0.00, 0.00] 1.46 309 .144
Orderofblocksvalues first 0.02 [-0.20, 0.23] 0.14 309 .886

Supplementary

Breaking it down by value

US PAPER: Value met

Capitalism

(#tab:unnamed-chunk-68)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalecapitalism 0.09 [-0.01, 0.18] 1.73 398 .084
(#tab:unnamed-chunk-69)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 1.01 [-0.81, 2.82] 1.09 310 .276
Scalecapitalism 0.07 [-0.03, 0.17] 1.33 310 .184
Scaleideo con -0.23 [-0.39, -0.08] -2.95 310 .003
Party idIndependent 0.27 [0.00, 0.54] 1.95 310 .053
Party idRepublican 0.15 [-0.23, 0.54] 0.78 310 .435
Income num -0.09 [-0.14, -0.05] -3.89 310 < .001
Edu num -0.08 [-0.18, 0.02] -1.66 310 .098
Raceblack -0.05 [-0.56, 0.46] -0.19 310 .846
Racehispanic 0.39 [-0.21, 0.99] 1.29 310 .198
Racemultiracial 0.33 [-0.25, 0.90] 1.11 310 .267
Racewhite 0.16 [-0.27, 0.58] 0.72 310 .475
Genderwoman 0.04 [-0.18, 0.25] 0.32 310 .748
Age 0.00 [-0.01, 0.01] 0.15 310 .879
County gini -0.99 [-4.39, 2.41] -0.57 310 .566
County density 0.00 [0.00, 0.00] 0.56 310 .578
County medianincome 0.00 [0.00, 0.00] -1.09 310 .277

Compassion

(#tab:unnamed-chunk-70)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scalecompassion -0.32 [-0.41, -0.23] -6.70 398 < .001
(#tab:unnamed-chunk-71)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 1.14 [-0.60, 2.89] 1.29 310 .199
Scalecompassion -0.26 [-0.36, -0.16] -5.14 310 < .001
Scaleideo con -0.18 [-0.33, -0.03] -2.30 310 .022
Party idIndependent 0.19 [-0.07, 0.45] 1.46 310 .146
Party idRepublican 0.11 [-0.26, 0.48] 0.60 310 .550
Income num -0.10 [-0.14, -0.05] -4.21 310 < .001
Edu num -0.06 [-0.15, 0.03] -1.25 310 .211
Raceblack 0.06 [-0.43, 0.54] 0.22 310 .823
Racehispanic 0.39 [-0.18, 0.97] 1.34 310 .181
Racemultiracial 0.29 [-0.26, 0.85] 1.04 310 .298
Racewhite 0.15 [-0.26, 0.56] 0.72 310 .474
Genderwoman -0.02 [-0.23, 0.18] -0.22 310 .823
Age 0.00 [-0.01, 0.01] 0.25 310 .801
County gini -1.20 [-4.47, 2.07] -0.72 310 .469
County density 0.00 [0.00, 0.00] 0.92 310 .359
County medianincome 0.00 [0.00, 0.00] -1.40 310 .161

Equality

(#tab:unnamed-chunk-72)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scaleequality -0.26 [-0.35, -0.16] -5.29 398 < .001
(#tab:unnamed-chunk-73)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.69 [-1.10, 2.48] 0.76 310 .448
Scaleequality -0.17 [-0.27, -0.07] -3.31 310 .001
Scaleideo con -0.20 [-0.36, -0.05] -2.58 310 .010
Party idIndependent 0.29 [0.02, 0.55] 2.14 310 .033
Party idRepublican 0.11 [-0.27, 0.49] 0.58 310 .565
Income num -0.09 [-0.14, -0.05] -3.99 310 < .001
Edu num -0.06 [-0.16, 0.04] -1.23 310 .221
Raceblack -0.04 [-0.53, 0.46] -0.15 310 .883
Racehispanic 0.43 [-0.16, 1.02] 1.43 310 .155
Racemultiracial 0.33 [-0.23, 0.90] 1.15 310 .249
Racewhite 0.17 [-0.25, 0.59] 0.80 310 .423
Genderwoman 0.01 [-0.20, 0.22] 0.09 310 .931
Age 0.00 [-0.01, 0.01] 0.17 310 .868
County gini -0.63 [-3.98, 2.72] -0.37 310 .713
County density 0.00 [0.00, 0.00] 0.61 310 .539
County medianincome 0.00 [0.00, 0.00] -0.68 310 .497

Freedom

(#tab:unnamed-chunk-74)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalefreedom -0.18 [-0.28, -0.09] -3.75 398 < .001
(#tab:unnamed-chunk-75)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.86 [-0.95, 2.67] 0.94 310 .350
Scalefreedom -0.10 [-0.21, 0.00] -1.98 310 .049
Scaleideo con -0.23 [-0.39, -0.08] -2.98 310 .003
Party idIndependent 0.30 [0.03, 0.56] 2.19 310 .029
Party idRepublican 0.18 [-0.20, 0.56] 0.91 310 .364
Income num -0.08 [-0.13, -0.04] -3.55 310 < .001
Edu num -0.08 [-0.18, 0.02] -1.65 310 .101
Raceblack -0.05 [-0.55, 0.46] -0.18 310 .854
Racehispanic 0.42 [-0.18, 1.02] 1.38 310 .169
Racemultiracial 0.33 [-0.25, 0.90] 1.12 310 .264
Racewhite 0.16 [-0.27, 0.58] 0.72 310 .472
Genderwoman 0.03 [-0.18, 0.24] 0.28 310 .781
Age 0.00 [-0.01, 0.01] 0.20 310 .841
County gini -0.83 [-4.22, 2.55] -0.49 310 .628
County density 0.00 [0.00, 0.00] 0.45 310 .655
County medianincome 0.00 [0.00, 0.00] -1.01 310 .313

Happiness

(#tab:unnamed-chunk-76)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scalehappiness -0.42 [-0.51, -0.33] -9.21 398 < .001
(#tab:unnamed-chunk-77)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.77 [-0.95, 2.49] 0.88 310 .378
Scalehappiness -0.31 [-0.41, -0.21] -5.97 310 < .001
Scaleideo con -0.14 [-0.29, 0.01] -1.86 310 .064
Party idIndependent 0.25 [-0.01, 0.50] 1.91 310 .057
Party idRepublican 0.15 [-0.21, 0.51] 0.81 310 .419
Income num -0.09 [-0.14, -0.05] -4.11 310 < .001
Edu num -0.06 [-0.15, 0.04] -1.17 310 .243
Raceblack -0.07 [-0.55, 0.40] -0.31 310 .759
Racehispanic 0.34 [-0.23, 0.91] 1.18 310 .239
Racemultiracial 0.32 [-0.23, 0.87] 1.15 310 .250
Racewhite 0.10 [-0.31, 0.51] 0.48 310 .634
Genderwoman 0.03 [-0.18, 0.23] 0.25 310 .804
Age 0.00 [-0.01, 0.01] 0.03 310 .972
County gini -0.49 [-3.71, 2.74] -0.30 310 .766
County density 0.00 [0.00, 0.00] 0.51 310 .612
County medianincome 0.00 [0.00, 0.00] -1.08 310 .280

National Pride

(#tab:unnamed-chunk-78)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalenationalpride -0.04 [-0.14, 0.05] -0.88 398 .378
(#tab:unnamed-chunk-79)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.83 [-0.99, 2.65] 0.90 310 .371
Scalenationalpride -0.08 [-0.19, 0.04] -1.23 310 .218
Scaleideo con -0.24 [-0.39, -0.08] -3.00 310 .003
Party idIndependent 0.28 [0.01, 0.55] 2.04 310 .042
Party idRepublican 0.17 [-0.21, 0.55] 0.86 310 .389
Income num -0.09 [-0.13, -0.04] -3.69 310 < .001
Edu num -0.08 [-0.18, 0.02] -1.66 310 .098
Raceblack 0.03 [-0.47, 0.54] 0.12 310 .901
Racehispanic 0.42 [-0.18, 1.02] 1.37 310 .171
Racemultiracial 0.33 [-0.25, 0.91] 1.13 310 .261
Racewhite 0.17 [-0.26, 0.60] 0.78 310 .436
Genderwoman 0.03 [-0.18, 0.25] 0.30 310 .761
Age 0.00 [-0.01, 0.01] -0.11 310 .910
County gini -0.62 [-4.04, 2.80] -0.36 310 .722
County density 0.00 [0.00, 0.00] 0.46 310 .645
County medianincome 0.00 [0.00, 0.00] -1.04 310 .301

Progress

(#tab:unnamed-chunk-80)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scaleprogress -0.26 [-0.35, -0.16] -5.33 398 < .001
(#tab:unnamed-chunk-81)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.98 [-0.80, 2.75] 1.09 310 .279
Scaleprogress -0.20 [-0.31, -0.10] -3.94 310 < .001
Scaleideo con -0.19 [-0.35, -0.04] -2.48 310 .014
Party idIndependent 0.21 [-0.06, 0.47] 1.52 310 .130
Party idRepublican 0.09 [-0.28, 0.47] 0.48 310 .629
Income num -0.09 [-0.13, -0.04] -3.81 310 < .001
Edu num -0.07 [-0.17, 0.02] -1.51 310 .131
Raceblack 0.15 [-0.35, 0.64] 0.58 310 .565
Racehispanic 0.49 [-0.10, 1.08] 1.64 310 .103
Racemultiracial 0.45 [-0.12, 1.02] 1.56 310 .119
Racewhite 0.26 [-0.16, 0.68] 1.22 310 .223
Genderwoman 0.00 [-0.21, 0.21] -0.02 310 .981
Age 0.00 [-0.01, 0.01] -0.11 310 .912
County gini -1.04 [-4.37, 2.28] -0.62 310 .537
County density 0.00 [0.00, 0.00] 0.72 310 .474
County medianincome 0.00 [0.00, 0.00] -1.13 310 .260

Security

(#tab:unnamed-chunk-82)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalesecurity -0.10 [-0.20, 0.00] -2.00 398 .046
(#tab:unnamed-chunk-83)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.87 [-0.95, 2.68] 0.94 310 .350
Scalesecurity -0.05 [-0.16, 0.05] -0.96 310 .336
Scaleideo con -0.25 [-0.40, -0.09] -3.17 310 .002
Party idIndependent 0.30 [0.03, 0.57] 2.21 310 .028
Party idRepublican 0.19 [-0.20, 0.57] 0.96 310 .336
Income num -0.09 [-0.14, -0.04] -3.82 310 < .001
Edu num -0.08 [-0.18, 0.02] -1.63 310 .104
Raceblack 0.02 [-0.48, 0.53] 0.10 310 .923
Racehispanic 0.40 [-0.20, 1.00] 1.31 310 .191
Racemultiracial 0.34 [-0.24, 0.91] 1.14 310 .256
Racewhite 0.18 [-0.25, 0.61] 0.81 310 .419
Genderwoman 0.01 [-0.20, 0.23] 0.13 310 .896
Age 0.00 [-0.01, 0.01] 0.15 310 .881
County gini -0.82 [-4.22, 2.58] -0.47 310 .636
County density 0.00 [0.00, 0.00] 0.60 310 .552
County medianincome 0.00 [0.00, 0.00] -1.01 310 .313

IDEAL: Value met

Capitalism

(#tab:unnamed-chunk-84)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalecapitalism -0.25 [-0.35, -0.16] -5.22 398 < .001
(#tab:unnamed-chunk-85)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.96 [-0.83, 2.76] 1.05 310 .293
Scalecapitalism -0.16 [-0.27, -0.05] -2.78 310 .006
Scaleideo con -0.20 [-0.36, -0.04] -2.51 310 .013
Party idIndependent 0.32 [0.05, 0.58] 2.34 310 .020
Party idRepublican 0.21 [-0.17, 0.59] 1.09 310 .275
Income num -0.08 [-0.13, -0.04] -3.49 310 < .001
Edu num -0.06 [-0.16, 0.03] -1.28 310 .201
Raceblack -0.06 [-0.56, 0.44] -0.25 310 .804
Racehispanic 0.31 [-0.29, 0.91] 1.01 310 .314
Racemultiracial 0.22 [-0.36, 0.79] 0.74 310 .457
Racewhite 0.07 [-0.35, 0.50] 0.34 310 .735
Genderwoman -0.01 [-0.22, 0.21] -0.06 310 .952
Age 0.00 [-0.01, 0.01] -0.01 310 .993
County gini -0.92 [-4.28, 2.44] -0.54 310 .591
County density 0.00 [0.00, 0.00] 0.57 310 .568
County medianincome 0.00 [0.00, 0.00] -1.01 310 .312

Compassion

(#tab:unnamed-chunk-86)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scalecompassion -0.28 [-0.38, -0.19] -5.92 398 < .001
(#tab:unnamed-chunk-87)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.95 [-0.81, 2.70] 1.06 310 .289
Scalecompassion -0.23 [-0.33, -0.14] -4.71 310 < .001
Scaleideo con -0.20 [-0.35, -0.05] -2.66 310 .008
Party idIndependent 0.20 [-0.06, 0.46] 1.51 310 .133
Party idRepublican 0.12 [-0.25, 0.49] 0.62 310 .535
Income num -0.09 [-0.14, -0.05] -4.02 310 < .001
Edu num -0.07 [-0.17, 0.02] -1.55 310 .123
Raceblack 0.02 [-0.47, 0.51] 0.08 310 .936
Racehispanic 0.36 [-0.22, 0.95] 1.23 310 .219
Racemultiracial 0.33 [-0.23, 0.89] 1.16 310 .248
Racewhite 0.15 [-0.26, 0.56] 0.71 310 .478
Genderwoman 0.00 [-0.21, 0.21] 0.01 310 .992
Age 0.00 [-0.01, 0.01] 0.23 310 .817
County gini -0.87 [-4.16, 2.42] -0.52 310 .603
County density 0.00 [0.00, 0.00] 0.89 310 .373
County medianincome 0.00 [0.00, 0.00] -1.13 310 .260

Equality

(#tab:unnamed-chunk-88)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scaleequality -0.19 [-0.29, -0.09] -3.85 398 < .001
(#tab:unnamed-chunk-89)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.77 [-1.03, 2.57] 0.84 310 .400
Scaleequality -0.14 [-0.24, -0.04] -2.66 310 .008
Scaleideo con -0.23 [-0.38, -0.08] -2.94 310 .003
Party idIndependent 0.28 [0.02, 0.55] 2.09 310 .038
Party idRepublican 0.14 [-0.24, 0.52] 0.72 310 .471
Income num -0.09 [-0.14, -0.05] -3.95 310 < .001
Edu num -0.07 [-0.17, 0.02] -1.47 310 .144
Raceblack -0.02 [-0.52, 0.48] -0.08 310 .935
Racehispanic 0.37 [-0.22, 0.97] 1.23 310 .221
Racemultiracial 0.32 [-0.25, 0.89] 1.11 310 .269
Racewhite 0.15 [-0.27, 0.58] 0.70 310 .483
Genderwoman 0.03 [-0.18, 0.25] 0.29 310 .769
Age 0.00 [-0.01, 0.01] 0.06 310 .953
County gini -0.60 [-3.97, 2.77] -0.35 310 .726
County density 0.00 [0.00, 0.00] 0.47 310 .637
County medianincome 0.00 [0.00, 0.00] -0.84 310 .400

Freedom

(#tab:unnamed-chunk-90)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalefreedom -0.23 [-0.32, -0.13] -4.61 398 < .001
(#tab:unnamed-chunk-91)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.79 [-1.02, 2.59] 0.86 310 .392
Scalefreedom -0.13 [-0.24, -0.02] -2.36 310 .019
Scaleideo con -0.23 [-0.38, -0.07] -2.87 310 .004
Party idIndependent 0.31 [0.04, 0.57] 2.28 310 .024
Party idRepublican 0.20 [-0.18, 0.58] 1.02 310 .307
Income num -0.09 [-0.13, -0.04] -3.73 310 < .001
Edu num -0.07 [-0.17, 0.02] -1.49 310 .137
Raceblack -0.05 [-0.55, 0.46] -0.18 310 .856
Racehispanic 0.43 [-0.17, 1.03] 1.42 310 .155
Racemultiracial 0.32 [-0.26, 0.89] 1.09 310 .278
Racewhite 0.15 [-0.28, 0.57] 0.69 310 .489
Genderwoman 0.02 [-0.20, 0.23] 0.17 310 .864
Age 0.00 [-0.01, 0.01] 0.32 310 .751
County gini -0.73 [-4.10, 2.65] -0.42 310 .672
County density 0.00 [0.00, 0.00] 0.44 310 .657
County medianincome 0.00 [0.00, 0.00] -1.03 310 .303

Happiness

(#tab:unnamed-chunk-92)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scalehappiness -0.38 [-0.47, -0.28] -8.08 398 < .001
(#tab:unnamed-chunk-93)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.88 [-0.83, 2.60] 1.01 310 .312
Scalehappiness -0.31 [-0.41, -0.21] -6.06 310 < .001
Scaleideo con -0.17 [-0.32, -0.02] -2.24 310 .026
Party idIndependent 0.27 [0.01, 0.52] 2.08 310 .039
Party idRepublican 0.20 [-0.16, 0.56] 1.08 310 .282
Income num -0.09 [-0.13, -0.04] -3.87 310 < .001
Edu num -0.06 [-0.15, 0.03] -1.28 310 .203
Raceblack 0.00 [-0.48, 0.47] -0.01 310 .992
Racehispanic 0.46 [-0.11, 1.04] 1.60 310 .110
Racemultiracial 0.35 [-0.19, 0.90] 1.28 310 .203
Racewhite 0.14 [-0.26, 0.55] 0.70 310 .486
Genderwoman 0.02 [-0.19, 0.22] 0.18 310 .861
Age 0.00 [-0.01, 0.01] -0.07 310 .947
County gini -0.66 [-3.88, 2.56] -0.40 310 .688
County density 0.00 [0.00, 0.00] 0.35 310 .727
County medianincome 0.00 [0.00, 0.00] -1.49 310 .137

National Pride

(#tab:unnamed-chunk-94)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scalenationalpride -0.30 [-0.39, -0.20] -6.21 398 < .001
(#tab:unnamed-chunk-95)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.82 [-0.96, 2.60] 0.91 310 .365
Scalenationalpride -0.21 [-0.31, -0.10] -3.74 310 < .001
Scaleideo con -0.18 [-0.34, -0.03] -2.32 310 .021
Party idIndependent 0.23 [-0.04, 0.49] 1.68 310 .095
Party idRepublican 0.17 [-0.21, 0.54] 0.89 310 .376
Income num -0.08 [-0.13, -0.04] -3.52 310 < .001
Edu num -0.05 [-0.15, 0.05] -1.05 310 .293
Raceblack 0.10 [-0.39, 0.60] 0.41 310 .679
Racehispanic 0.40 [-0.19, 0.99] 1.34 310 .182
Racemultiracial 0.36 [-0.20, 0.93] 1.27 310 .206
Racewhite 0.19 [-0.23, 0.61] 0.88 310 .379
Genderwoman 0.02 [-0.19, 0.23] 0.21 310 .832
Age 0.00 [-0.01, 0.01] -0.36 310 .716
County gini -0.74 [-4.07, 2.59] -0.44 310 .664
County density 0.00 [0.00, 0.00] 0.44 310 .660
County medianincome 0.00 [0.00, 0.00] -1.02 310 .308

Progress

(#tab:unnamed-chunk-96)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.09, 0.09] 0.00 398 > .999
Scaleprogress -0.26 [-0.36, -0.17] -5.47 398 < .001
(#tab:unnamed-chunk-97)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.48 [-1.30, 2.26] 0.53 310 .599
Scaleprogress -0.22 [-0.33, -0.12] -4.18 310 < .001
Scaleideo con -0.19 [-0.34, -0.04] -2.46 310 .014
Party idIndependent 0.21 [-0.05, 0.48] 1.60 310 .111
Party idRepublican 0.07 [-0.31, 0.44] 0.34 310 .731
Income num -0.09 [-0.14, -0.04] -3.91 310 < .001
Edu num -0.07 [-0.16, 0.03] -1.41 310 .159
Raceblack 0.13 [-0.36, 0.63] 0.53 310 .595
Racehispanic 0.51 [-0.08, 1.10] 1.70 310 .091
Racemultiracial 0.45 [-0.12, 1.01] 1.56 310 .120
Racewhite 0.27 [-0.15, 0.69] 1.27 310 .205
Genderwoman 0.00 [-0.21, 0.21] -0.02 310 .984
Age 0.00 [-0.01, 0.01] -0.20 310 .840
County gini -0.18 [-3.51, 3.15] -0.11 310 .915
County density 0.00 [0.00, 0.00] 0.47 310 .636
County medianincome 0.00 [0.00, 0.00] -0.61 310 .546

Security

(#tab:unnamed-chunk-98)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.00 [-0.10, 0.10] 0.00 398 > .999
Scalesecurity -0.21 [-0.30, -0.11] -4.22 398 < .001
(#tab:unnamed-chunk-99)
Predictor \(b\) 95% CI \(t\) \(\mathit{df}\) \(p\)
Intercept 0.79 [-1.01, 2.58] 0.86 310 .391
Scalesecurity -0.15 [-0.27, -0.04] -2.67 310 .008
Scaleideo con -0.21 [-0.37, -0.06] -2.67 310 .008
Party idIndependent 0.28 [0.01, 0.54] 2.07 310 .040
Party idRepublican 0.15 [-0.23, 0.53] 0.78 310 .435
Income num -0.09 [-0.14, -0.05] -3.99 310 < .001
Edu num -0.08 [-0.17, 0.02] -1.52 310 .129
Raceblack 0.06 [-0.44, 0.57] 0.25 310 .802
Racehispanic 0.45 [-0.14, 1.05] 1.49 310 .137
Racemultiracial 0.38 [-0.19, 0.96] 1.31 310 .191
Racewhite 0.23 [-0.20, 0.66] 1.06 310 .292
Genderwoman -0.01 [-0.23, 0.20] -0.13 310 .893
Age 0.00 [-0.01, 0.01] 0.05 310 .958
County gini -0.79 [-4.16, 2.57] -0.46 310 .643
County density 0.00 [0.00, 0.00] 0.82 310 .410
County medianincome 0.00 [0.00, 0.00] -0.76 310 .449