COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 1

1 Responses to the COVID-19 Pandemic Reflect the Dual Evolutionary Foundations of

2 Political Ideology

1 2, 3 1, 4 3 Kyle Fischer* , Ananish Chaudhuri , & Quentin D. Atkinson*

1 4 School of Psychology, University of Auckland, Auckland, New Zealand

2 5 Department of Economics, University of Auckland, Auckland, New Zealand

3 6 CESifo, Munich, Germany

4 7 Max Planck Institute for the Science of Human History, Jena, Germany

8 This working paper is still under peer review.

9 *Correspondence concerning this article should be addressed to:

10 Quentin D. Atkinson (e-mail: [email protected]) or Kyle Fischer (e-mail:

11 [email protected]), Floor 3, Building 302, 23 Symonds Street, Auckland, 1010, New

12 Zealand.

13 Data, Code, and Materials are available here:

14 https://osf.io/mv2j6/?view_only=2c24869169934b5993841c1eb4058bbf

15 This study is pre-registered, details of which can be found here:

16 https://aspredicted.org/blind.php?x=xs6jm8

17 We have no known conflict of interest to disclose.

18 No data used in this study have been used in any previous publications. COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 2

19 ABSTRACT

20 Opposition to COVID-19 response measures from many conservatives is puzzling given the

21 well-established link between conservatism and threat-sensitivity and strong pandemic

22 responses from many conservative nations. We argue a resolution is provided by the ‘dual

23 evolutionary foundations’ theory of political ideology, which holds that ideology varies along

24 two dimensions, reflecting trade-offs between: threat-driven conformity vs. individualism, and

25 empathy-driven co-operation vs. competition. We test predictions derived from this theory

26 using longitudinal data from a UK sample on widely-used measures of the two dimensions –

27 ‘right-wing authoritarianism’ (RWA) and ‘social dominance orientation’ (SDO), respectively.

28 Consistent with the theory, RWA but not SDO significantly increased following the pandemic,

29 and worry about COVID-19 predicts this effect. Moreover, consistent with the theory, higher

30 RWA predicts more worried and conformist/norm-enforcing responses, while lower SDO

31 predicts more cooperative/empathic responses. These findings help explain paradoxical prior

32 results and highlight divergent motives across the ideological landscape that may be useful for

33 managing pandemic responses.

34 Keywords: COVID-19 pandemic, political ideology, longitudinal, authoritarianism, social

35 dominance orientation, threat, co-operation

36 Word count: abstract = 154; main text = 8,454 (excl. ref. list); figure/table captions = 371.

37 INTRODUCTION

38 In the wake of the COVID-19 pandemic, a popular view has gained ground that liberals are

39 in favour of lockdowns to prevent the spread of the virus while conservatives are focused on

40 resuming activities to prevent an economic downturn. This is supported by studies showing an

41 association between conservative political ideology and reduced support for and compliance

42 with pandemic prevention measures, at both the individual level (Allcott et al. 2020; Van Bavel

43 et al. 2020; Calvillo et al. 2020; Christensen et al. 2020; Clements 2020; Conway III et al. 2020; COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 3

44 Everett et al. 2020; Gadarian, Goodman, and Pepinsky 2021; Makridis and Rothwell 2020;

45 Pennycook et al. 2021; Raihani and de Wit 2020; Rothgerber et al. 2020) and population level

46 (Barrios and Hochberg 2020; Frey, Chen, and Presidente 2020; Gollwitzer et al. 2020; Painter

47 and Qiu 2021). However, such a conclusion appears inconsistent with the well-known link

48 between conservatism and increased threat-sensitivity, including pathogen aversion (Hibbing,

49 Smith, and Alford 2014; Shaffer and Duckitt 2013). Moreover, it remains unclear what

50 psychological mechanisms underlie these observed differences in responses to COVID-19, or

51 why some apparently conservative or “tight” populations (e.g., Saudi Arabia, India, and South

52 Korea) have in fact responded to the pandemic by implementing strict mitigating measures

53 relatively swiftly (Frey, Chen, and Presidente 2020; Gelfand et al. 2021). One potential solution

54 to this apparent paradox comes from research in social and political psychology indicating that

55 a unidimensional view of politics as fundamentally ‘conservative’ versus ‘liberal’ misses

56 important features of the political landscape (Claessens et al. 2020; Duckitt and Sibley 2009).

57 As highlighted in a recent review article, a unidimensional view of political ideology is, if

58 not incorrect, then certainly incomplete (Claessens et al. 2020). Unidimensional scales often

59 have low external validity and produce more than one latent variable in factor analyses (Duckitt

60 and Sibley 2009; Treier and Hillygus 2009). In contrast, over the last few decades scholars

61 using a diverse range of methodologies and theoretical frameworks have found consistent

62 support for two distinct dimensions underlying variation in political ideology. The first

63 dimension, linked to measures like ‘social dominance orientation’ (SDO) (Duckitt and Sibley

64 2009), ‘hierarchy vs. egalitarianism’ (Trompenaars and Hampden-Turner 1998), and ‘vertical

65 vs. horizontal values’ (Triandis and Gelfand 1998), predicts views on issues such as inequality,

66 taxation, and social welfare – people high in SDO, for example, tend to be on the political right,

67 and hold views that are more economically conservative (Duriez and Van Hiel 2002; Lönnqvist

68 and Kivikangas 2019; Perry and Sibley 2013; Pratto et al. 1994). The second dimension, linked COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 4

69 to measures like ‘right-wing authoritarianism’ (RWA) (Duckitt and Sibley 2009), cultural

70 ‘tightness vs. looseness’ (Jackson, Gelfand, and Ember 2020), and ‘collectivism vs.

71 individualism’, predicts views on issues like same-sex marriage, abortion, and other traditional

72 or religious values – people high in RWA, for example, are also part of the political right, and

73 hold views that are more socially conservative than those low in RWA (Cizmar et al. 2014;

74 Duckitt et al. 2010; Duriez and Van Hiel 2002; Passini 2020).

75 Claessens et al. (2020) argue these dimensions can be understood as the product of two basic

76 tensions inherent to the evolution of human group living (Tomasello et al. 2012). SDO and

77 related constructs concern the trade-off between co-operation for the common good versus

78 individual self-interest and competition. RWA and related constructs concern the trade-off

79 between group conformity and social control versus individual autonomy and openness to

80 change. Strategic responses to these dual challenges of group living are argued to give rise to

81 contemporary variation in political attitudes, values, and policy preferences. This variation

82 within populations is maintained by a combination of fluctuating selection on heritable

83 biological predispositions, social learning, and evolved species-typical responses to

84 environmental and social triggers – known as ‘behavioural plasticity’. The importance of each

85 of these mechanisms is supported by work in behavioural genetics showing that both

86 dimensions of ideology are partly heritable and partly socially influenced (Batrićević and

87 Littvay 2017; Hatemi et al. 2014; Kandler, Bell, and Riemann 2016; Kandler, Bleidorn, and

88 Riemann 2012; Kandler, Gottschling, and Spinath 2016; Lewis and Bates 2014; Oskarsson et

89 al. 2015), and work in political and moral psychology showing that they are differentially

90 sensitive to certain situational factors, e.g., a range of measures of conformist attitudes and

91 values (such as RWA, cultural tightness, religiosity, and social conservatism) are sensitive to

92 threat (Asbrock and Fritsche 2013; Fincher and Thornhill 2012; Gelfand et al. 2011; Henrich

93 et al. 2019; Jackson, Gelfand, and Ember 2020; Van Leeuwen et al. 2012; Murray, Schaller, COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 5

94 and Suedfeld 2013; Napier et al. 2018; Oxley et al. 2008; Shaffer and Duckitt 2013; Shook,

95 Ford, and Boggs 2017; Tybur et al. 2016; Zmigrod et al. 2020).

96 These dual evolutionary foundations of political ideology provide a natural framework for

97 making predictions regarding the specific attitudes and behaviours associated with the two

98 dimensions of ideology, and their distinct socio-ecological triggers. Here, we focus our

99 predictions on variation in RWA (as an indicator of conformist/individualist preferences) and

100 SDO (as an indicator of cooperative/competitive preferences). We chose these scales because

101 they are among the most widely used two-dimensional measures of political ideology (Duckitt

102 and Sibley 2009, 2017; Johnston and Ollerenshaw 2020), they show a clear conceptual

103 mapping to the proposed dual evolutionary foundations (Claessens et al. 2020), and have been

104 shown to powerfully predict behaviour and policy preferences in other domains (Asbrock,

105 Sibley, and Duckitt 2010; Duckitt and Sibley 2016, 2017; Milojev et al. 2014; Perry and Sibley

106 2013).

107 Under the dual foundations framework, RWA can be explained as underpinned by a threat-

108 driven concern for group viability that motivates conformity, norm enforcement, and other

109 forms of social control. Consistent with this, people high (vs. low) in RWA tend to be more

110 uncertainty-averse and conformist (scoring highly on ‘Need for Closure’ and ‘Social

111 Conformity’ scales), obedient to authority, and prejudiced against and punitive of norm-

112 violators or people with foreign norms (Bilewicz et al. 2017; Cizmar et al. 2014; Dambrun and

113 Vatiné 2010; Duckitt and Sibley 2017; Feldman 2003; Van Hiel, Pandelaere, and Duriez 2004;

114 Hunsberger 1996; McKee and Feather 2008; Passini 2020), as well as more threat- and disgust-

115 sensitive and likely to see the world as dangerous (Duckitt and Sibley 2009, 2017; Feldman

116 2013; Liuzza et al. 2018; Oxley et al. 2008; Shaffer and Duckitt 2013; Shook, Ford, and Boggs

117 2017; Smith et al. 2011; Terrizzi, Shook, and Ventis 2010). As a result, high RWA individuals

118 are more likely to hold views that promote and enforce in-group conformity and protect the in- COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 6

119 group, such as religious fundamentalism (Hunsberger 1996) and support for capital punishment

120 and increased defence spending (Cizmar et al. 2014; McKee and Feather 2008). In addition,

121 perceived threat and uncertainty in the environment is expected to act as a trigger, increasing

122 norm-enforcing conformityand, in turn, RWA (Aoki and Feldman 2014; Claessens et al. 2020).

123 This is consistent with evidence showing (1) increased conformity (Murray and Schaller 2012;

124 Wu and Chang 2012), norm enforcement (Littman et al. 2020; Sääksvuori, Mappes, and

125 Puurtinen 2011), and RWA (Asbrock and Fritsche 2013; Duckitt and Fisher 2003) in response

126 to increased experimentally induced or real threat (e.g., of group conflict or disease), as well as

127 (2) population-level correlations between levels of threat (e.g., warfare or disease) and RWA

128 and related variables (Fincher and Thornhill 2012; Gelfand et al. 2011; Gneezy and Fessler

129 2012; Henrich et al. 2019; Van Leeuwen et al. 2012; Lindén, Björklund, and Bäckström 2018;

130 Murray, Schaller, and Suedfeld 2013; Terrizzi, Shook, and McDaniel 2013; Tybur et al. 2016;

131 Zmigrod et al. 2020).

132 In contrast, the dual foundations framework conceptualizes SDO as underpinned by a

133 competitive, self-interested motivation for dominance driven by a view of the world as a

134 ‘competitive jungle’ vs. a more cooperative, other-regarding orientation motivated by empathic

135 and egalitarian preferences. Consistent with this, people low in SDO and similar measures

136 show greater empathic concern (Chiao et al. 2009; Sidanius et al. 2013) and cooperative

137 behaviour in economic games (Fischer, Atkinson, and Chaudhuri 2021), whilst those high in

138 SDO score higher on personality traits such as Machiavellianism, and lower in agreeableness

139 and see the world as a competitive zero sum game (Duckitt and Sibley 2009; Jones and

140 Figueredo 2013). As a result, low SDO individuals tend to support policies that foster public

141 goods (especially for those in need) at individual expense (especially of the privileged), like

142 redistributive taxation, social welfare, and environmental protection, while high SDO

143 individuals tend to oppose such policies and support free-market capitalism. COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 7

144 This dual evolutionary foundations of political ideology framework makes clear predictions

145 about the relationship between political ideology and individuals’ responses to a pandemic like

146 COVID-19, as well as the effect of the pandemic on people’s political ideology. First, the

147 framework predicts that SDO and RWA will differentially predict attitudinal responses to the

148 pandemic related to co-operation and conformity, respectively. Prediction 1: Low SDO

149 individuals will display cooperative, empathic attitudes and policy preferences regarding

150 COVID-19; high RWA individuals will display conformist, norm-enforcing attitudes and policy

151 preferences regarding COVID-19. Recent studies taking a unidimensional view of ideology

152 have found that the political left displayed more empathy-related (Oosterhoff and Palmer 2020;

153 Pfattheicher et al. 2020) attitudes and behaviours like physical distancing (Allcott et al. 2020;

154 Van Bavel et al. 2020; Clements 2020; Conway III et al. 2020; Everett et al. 2020; Gadarian,

155 Goodman, and Pepinsky 2021; Gollwitzer et al. 2020; Makridis and Rothwell 2020; Pennycook

156 et al. 2021; Raihani and de Wit 2020; Rothgerber et al. 2020), but it is an open question whether

157 low SDO or low RWA individuals are driving this. Studies looking at unidimensional ideology

158 also found that the political left has been more compliant with prevention measures and more

159 in favour of strict policy to deal with the pandemic (Allcott et al. 2020; Van Bavel et al. 2020;

160 Clements 2020; Conway III et al. 2020; Everett et al. 2020; Gadarian, Goodman, and Pepinsky

161 2021; Makridis and Rothwell 2020; Pennycook et al. 2021; Raihani and de Wit 2020;

162 Rothgerber et al. 2020), although the political right may favour stricter border control

163 (Gadarian, Goodman, and Pepinsky 2021; Lindholt et al. 2021). However, studies comparing

164 country-level data around the globe have found a positive relationship between concerted

165 COVID-19 response and several measures typically associated with political conservatism –

166 autocratic (vs. democratic) countries introduced stricter lockdowns, collectivistic (vs.

167 individualistic) countries were more successful at reducing mobility, and culturally ‘tight’ (vs.

168 ‘loose’) countries were some of the most effective at limiting infection rates (Frey, Chen, and COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 8

169 Presidente 2020; Gelfand et al. 2021). The reason for these apparently inconsistent results is

170 unclear but the dual dimensions of ideology offer a potential explanation. Conservatives who

171 are high in SDO may be slow, and conservatives high in RWA quick, to embrace stringent

172 measures to deal with the pandemic because the former are more focused on maintaining

173 normal economic activity while the latter want greater social control and restrictions to tackle

174 pandemic threats. Conversely, people on the political left who are low in SDO may be quick,

175 and those low in RWA slow, to adopt some stringent measures because the former are driven

176 by empathy while the latter are opposed to social control.

177 Second, the dual foundations of ideology make predictions about how the socio-ecological

178 context of COVID-19 will influence ideology. Prediction 2: RWA but not SDO will increase

179 in response to both real and perceived threats posed by COVID-19. Ideally, longitudinal data

180 are required to show such effects but are difficult to acquire because pandemics are rare and

181 unexpected. As a result, few prior longitudinal studies have looked at the effects of a pandemic

182 on political ideology, with even fewer considering multidimensional ideology. Studies on the

183 Ebola outbreak in the US found an increase in inclinations to vote for conservative candidates

184 (Beall, Hofer, and Schaller 2016), but no strong or consistent increase in prejudice against gay

185 men and lesbians (Inbar et al. 2016). During the current pandemic, no change was observed in

186 unidimensional ideology in a US sample, but there was an increase in support for conformity

187 to traditional gender roles (Rosenfeld and Tomiyama 2021). In France, county-level data

188 showed that perceived threat (looking up coronavirus-related words on the internet) but not

189 real threat (number of diagnosed cases) before an election predicted increased voting for

190 conservatives in the election (Adam-Troian et al. 2020).. While there are few longitudinal

191 studies on the dual dimensions of ideology, there is still some evidence supporting our

192 prediction. One study found that, conditional on perceived COVID-19 threat, higher RWA

193 correlates with higher nationalism and anti-immigration sentiments in the UK (Hartman et al. COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 9

194 2021). Another study found that priming COVID-19 salience in Polish and US samples

195 elevated anxiety, indirectly increasing social conservatism and support for conservative

196 candidates (Karwowski et al. 2020). The only longitudinal study examining both dimensions

197 of ideology found that scores on the RWA (but not SDO) scale increased following the

198 outbreak of COVID-19 (Golec de Zavala et al. 2020), but the study was conducted in Poland

199 and did not include measures of perceived threat or exposure to real pandemic threats, therefore

200 the mechanism involved, and the generalizability of the finding, remain unclear.

201 Third, the widespread swift and stringent response to the pandemic among political liberals

202 demonstrates that they are at least as worried about it as conservatives are. Under the dual

203 foundations framework, pandemic concern across the political spectrum is expected to reflect

204 two distinct ideological drivers – a threat-based drive for conformity and social control (greater

205 among people high in RWA) and an empathy-based drive for co-operation to protect others

206 (greater among people low in SDO). Prediction 3: RWA will predict greater threat-sensitivity

207 and hence more worry about the pandemic across all our worry measures. SDO is expected to

208 show a very different pattern, with people low in SDO predicted to worry more than those high

209 in SDO, but specifically about aspects of the pandemic that prime empathic concern (i.e., the

210 pandemic in general and the health of both familiar and unfamiliar others). Almost all the

211 recent studies on worry about the pandemic have used unidimensional measures of ideology

212 and found that political liberals are more worried in most but not all countries (Allcott et al.

213 2020; Barrios and Hochberg 2020; Calvillo et al. 2020; Conway III et al. 2020; Dryhurst et al.

214 2020; Gadarian, Goodman, and Pepinsky 2021; Makridis and Rothwell 2020; Pennycook et al.

215 2021; Raihani and de Wit 2020; Rothgerber et al. 2020). However, unidimensional measures

216 of ideology may be obscuring the previously well-established link between high RWA or social

217 conservatism and threat-sensitivity. Moreover, these studies did not differentiate between

218 different pandemic-related threats to self (including economic threats) and threats to others, COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 10

219 triggering empathic concern. It therefore remains unclear whether the reported relationship

220 between liberalism and worry about COVID-19 masks a relationship between both low SDO

221 and worry due to empathic concern, and high RWA and worry due to threat-sensitivity.

222 Here, we test these predictions using a longitudinal online survey of a large UK sample,

223 measuring the two primary dimensions of political ideology (SDO and RWA), Empathic

224 Concern, and a broad array of worried, cooperative, conformist, and norm-enforcing attitudes

225 and policy preferences regarding COVID-19. We also controlled for likely covariates (age, sex,

226 race, and socioeconomic status), as well as left-right political affiliation because it has been

227 argued that political polarization and partisanship explains the stronger response on the

228 political left compared to the political right (Allcott et al. 2020; Barrios and Hochberg 2020;

229 Clinton et al. 2021; Conway III et al. 2020; Cornelson and Miloucheva 2020; Gadarian,

230 Goodman, and Pepinsky 2021; Gollwitzer et al. 2020; Makridis and Rothwell 2020; Painter

231 and Qiu 2021; Pennycook et al. 2021; Rothgerber et al. 2020).

232 METHODS

233 Open Science Statement

234 We sampled participants in the UK in three waves using Prolific (https://www.prolific.co/).

235 First, between 8 October and 7 November 2019 (approximately 3 months before the pandemic)

236 for another study (unpublished), where we measured RWA and SDO. Second, between the 18

237 and 28 April 2020 (during the pandemic; the first confirmed coronavirus case in the UK was

238 on the 31 January 2020), where we measured RWA and SDO again, as well as a broad array

239 of experiences of and responses to the pandemic. Third, between 15 and 28 June 2020 where

240 we measured Empathic Concern.

241 All data and analysis code, as well as procedural details for this study are available online

242 (https://osf.io/mv2j6/?view_only=2c24869169934b5993841c1eb4058bbf). We pre-registered

243 our predictions and analyses while the second wave of data collection was running on Prolific COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 11

244 but before the authors accessed the data (https://aspredicted.org/blind.php?x=xs6jm8). We pre-

245 registered Predictions 1 and 2 mentioned in the introduction. Prediction 3 was derived on the

246 basis of support for prediction 1 and 2 as we began to analyse the data and is therefore presented

247 as an exploratory analysis. Our principal components analysis of conformist/norm-enforcing

248 attitudes and policy preferences was an exploratory follow-up to Prediction 1. Regarding

249 statistical analyses, we pre-registered that we would (1) use paired-samples t-tests to determine

250 whether RWA or SDO increased following the onset of the pandemic, (2) use structural

251 equation modelling (SEM) or (if SEM models do not converge) regression analyses to examine

252 RWA’s and SDO’s (both measured before the onset of the pandemic) effects on conformist,

253 norm-enforcing, and cooperative, other-regarding responses to COVID-19 (we specified the

254 items we would use to create these two outcome variables), controlling for COVID-19

255 experiences/exposure, age, sex, race, socioeconomic status, and political affiliation, and (3)

256 exclude data from participants who completed the study too quickly/slowly, failed attention

257 checks, and had the same response to more than two thirds of Likert scale questions (see the

258 pre-registration for details). We report results from regression analyses rather than SEM

259 because it did not produce a good fit for RWA measured before the onset of the pandemic

260 (RMSEA = 0.12, SRMR = 0.10).

261 Participants

262 We recruited 553 participants (the survey was open to all Prolific participants who were

263 over 18 and lived in the UK). This serves as the first wave of data collection for the present

264 study. For the second wave, we approached these same participants. After excluding

265 participants who did not meet our pre-registered exclusion criteria or who, in the first wave,

266 took under 8 or over 90 minutes to complete the session, gave the same response to more than

267 two thirds of Likert scale items, or incorrectly answered at least one of two attention checks,

268 we were left with 433 participants (age: 18–72, mean 37; 285 female; race: 44 non-white). For COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 12

269 analyses that used political affiliation as a covariate, there were 15 participants who did not

270 provide this information on Prolific. Excluding them left us with 418 participants (age: 18–72,

271 mean 38; 273 female; 43 non-white; political affiliation: left = 229, centre = 57, right = 100,

272 other = 32). For analyses involving items answered on a sliding scale (Items B12.1.1–4 and

273 D.1–6 below), eight of the above 433 participants did not answer these questions, leaving 425

274 participants (age: 18–72, mean 37; 279 female; 42 non-white; political affiliation: left = 226,

275 centre = 57, right = 97, other = 31). For the third wave of data collection, we were able to

276 recruit 368 of the same participants from the second wave, of whom five were excluded due to

277 the exclusion criteria from the first two waves, and a further six whose completion time was

278 outside of three standard deviations of the mean completion time for the third wave, leaving

279 357 participants for analyses involving Empathic Concern (age: 18–72, mean 38; 235 female;

280 41 non-white; political affiliation: left = 191, centre = 46, right = 80, other = 28). This relatively

281 large, diverse sample was deemed sufficient given that G*Power reveals that 175 participants

282 are required to detect a correlation effect size of r = 0.21, typically found in social psychology

283 (Richard, Bond, and Stokes-Zoota 2003), with statistical power of 0.8, or 289 participants with

284 statistical power of 0.95. Ethical approval was granted for this study by The University of

285 Auckland Human Participants Ethics Committee (ref: 023639).

286 Procedure

287 In all waves of data collection, participants were directed from Prolific to a Qualtrics survey

288 where they provided informed consent. In the first wave, participants completed SDO and

289 RWA scales as well as other items and tasks not related to the current study. In the second

290 wave, participants completed the same SDO and RWA scales as well as items on COVID-19

291 (COVID-19 items were separated into different blocks based on method of response, with

292 block order randomized). In both waves, the SDO and RWA items were randomized in the

293 same block and this block appeared in a random order with other blocks. In the third and final COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 13

294 wave of data collection, participants answered several scales (blocks and items within each

295 block were randomized), of which we used only Empathic Concern here.

296 Materials

297 Unless stated otherwise all below items were answered on Likert scales from 1 (strongly

298 disagree) to 7 (strongly agree).

299 Political ideology and Empathic Concern: We measured SDO with the 16-item SDO7

300 Scale (Ho et al. 2015), and RWA with the 36-item Authoritarianism-Conservatism-

301 Traditionalism Scale (Duckitt et al. 2010). We also measured Empathic Concern with the items

302 (answered on a Likert scale, 1 = does not describe me well, 5 = describes me very well) related

303 to this in the Interpersonal Reactivity Index (Davis 1983). Cronbach’s alpha reliability was

304 0.93 for SDO, 0.96 for RWA, and 0.86 for Empathic Concern.

305 (A) Cooperative, other-regarding responses to COVID-19: As per our pre-registration,

306 we used the mean of the following items for cooperative, other-regarding responses to COVID-

307 19: (A.1) “The government should waive all insurance costs and hospital fees for testing and

308 treating COVID-19”, (A.2) “Paid leave should be granted to anyone diagnosed with

309 coronavirus COVID-19”, and (A.3) “I am very concerned about those most vulnerable to

310 COVID-19” (Pfattheicher et al. 2020). The wording of Item A.1 was a combination of two

311 items from a recent study (Gadarian, Goodman, and Pepinsky 2021): “The government should

312 waive insurance costs and hospital fees for treating COVID-19”, and “Make all testing for

313 COVID-19 free for all Americans”.

314 (B) Conformist, norm-enforcing responses to COVID-19: As per our pre-registration,

315 we used the mean of all of the following items in our main analysis. (B.1) “It is important to

316 follow the UK government's rules regarding COVID-19”, (B.2) “Because of COVID-19, it is

317 very important that others take physical distancing very seriously and limit all social contact”,

318 (B.3) “I support government measures to restrict the movement of UK citizens to limit the COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 14

319 spread of COVID-19” (Conway III, Woodward, and Zubrod 2020), (B.4) “It makes me angry

320 that the government would tell me where I can go and what I can do, even when there is a crisis

321 such as COVID-19” [reverse coded] (Conway III, Woodward, and Zubrod 2020), (B.5) “I am

322 upset at the thought that my government would force people to stay home against their will”

323 [reverse coded] (Conway III, Woodward, and Zubrod 2020), (B.6) “It is vital right now that

324 the government strongly enforces social distancing measures”, a reworded version of “It is

325 vital right now that the Federal government strongly punishes people who do not engage in

326 social distancing measures” (Conway III, Woodward, and Zubrod 2020), (B.7) “All citizens of

327 China should be banned from entering the UK while the COVID-19 pandemic is ongoing”,

328 (B.8) “All citizens of the USA should be banned from entering the UK while the COVID-19

329 pandemic is ongoing”, (B.9) “Strict entry restrictions should be imposed at all borders while

330 the COVID-19 pandemic is ongoing”, (B.10) “I want my government to severely punish those

331 who violate orders to stay home” (Conway III, Woodward, and Zubrod 2020), (B.11) “The

332 army should be mobilized to enforce quarantines and rules regarding COVID-19”, and (B.12)

333 “Imagine a person, called K, who does not feel sick and so ignores the rules and goes out

334 without a facemask and does not try at all to keep a safe two-meter distance from other people.

335 To what extent does K’s behaviour make you feel…” (B.12.1) “anger?” (B.12.2) “disgust?”

336 (B.12.3) “contempt?” (B.12.4) “outrage?” (B.12.5) “Finally, how do you think K should be

337 treated?” [answered on a Likert scale: 1 = very leniently, 7 = very harshly]. For Items B.12.1–

338 4, we followed a study (Stamkou et al. 2019), unrelated to COVID-19, wherein participants

339 read vignettes about the behaviour (during an office meeting) of a hypothetical person called

340 K and moral emotions were measured in the same way as we did.

341 (C) Experiences of and exposure to COVID-19 threats: To measure exposure to threats

342 related to the pandemic, we asked participants the following questions which we then put in a

343 composite measure (set to 1 if participants responded “Yes” to one or more items, and 0 COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 15

344 otherwise): (C.1) “Has anyone you personally know tested positive for COVID-19?” [Yes, No,

345 Not sure] (Everett et al. 2020). (C.2) “Were you diagnosed with COVID-19?” [Yes, No]. (C.3)

346 “If you were not diagnosed with COVID-19, did you ever suspect that you had it?” [Yes, No].

347 (C.4) “Have you had necessary medical treatment such as surgery or cancer screening

348 delayed?” [Yes, No]. (C.5) “Do you know of anyone who has had necessary medical treatment

349 such as surgery or cancer screening delayed?” [Yes, No]. (C.6) “Has COVID-19 impacted you

350 negatively from a financial point of view?” [Yes, No, Not sure] – a reworded version of “The

351 Coronavirus (COVID-19) has impacted me negatively from a financial point of view” (Conway

352 III, Woodward, and Zubrod 2020). We also asked participants the following but did not include

353 this item in our analyses because almost everyone said yes: “Are there currently any cases of

354 COVID-19 infections in the city or town where you live?” [Yes, No, Not sure] (Everett et al.

355 2020).

356 (D) Perceived threat of COVID-19: We measured different domains of threat-sensitivity

357 by asking participants: “How worried are you about…” (D.1) “…the COVID-19 pandemic?”

358 (D.2) “…that you will get sick from COVID-19?” (D.3) “…that your family members and

359 friends will get sick from COVID-19?” (D.4) “…that people you don't personally know will get

360 sick from COVID-19?” (D.5) “…that the COVID-19 pandemic will negatively impact the

361 economy?” (D.6) “…that the COVID-19 pandemic will negatively impact you from a financial

362 point of view?” These items were answered on a sliding scale from 1 (“not at all worried”) to

363 7 (“extremely worried”).

364 Participants completed some additional items on COVID-19 that we do not report here.

365 Statistical analyses

366 We performed all analyses in R Statistical Software version 3.6.1. (R Core Team, 2019).

367 We performed paired sample t-tests to compare mean RWA (one-tailed) and mean SDO (two-

368 tailed) measured before the pandemic to mean RWA and mean SDO measured during the COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 16

369 pandemic. We used regression analyses to examine whether the changes in RWA and SDO

370 were predicted by real COVID-19 threat exposure (a composite of Items C.1–6 above), or

371 perceived COVID-19 threat (Item D.1 above, measuring general worry about the pandemic).

372 We ran regressions with SDO and RWA measured before COVID-19 as the predictors of the

373 different responses to the pandemic (e.g., our pre-registered composite measure of conformist,

374 norm-enforcing responses). We centred the RWA and SDO scores around the mean value of

375 RWA and SDO for all participants, respectively. All regressions reported here were linear,.

376 However, we also calculated ordinal logistic regressions for outcome variables that were

377 answered on a Likert scale as this accounts for the discrete yet ordered nature of such data.

378 Given that the linear and ordinal regression results were nearly identical, for presentation

379 purposes we report only the former here (see the supplemental material for the latter).

380 We incorporated pre-registered covariates in the above regression models using data

381 provided by Prolific for age, sex, race (white vs. non-white), socioeconomic status (indicated

382 on a ladder from 1 = lowest, to 10 = highest), and political affiliation (a composite that we

383 created of political left-right self-placement and voting for left- or right-wing parties). For the

384 COVID-19 experiences covariate, we used the composite (of items C.1–6) variable defined

385 above. For each regression, to find the model that fitted the data best we used the all-subsets

386 method (that evaluates every possible combination of variables) with the “dredge” function

387 from the MuMIn Package (Bartoń 2019), and chose the best fitting model that included our

388 variables of interest (i.e., both SDO and RWA). We included both SDO and RWA

389 simultaneously in the models because they are correlated in our sample and the importance of

390 controlling for shared variance between the two dimensions of ideology has recently been

391 independently demonstrated (Costello and Lilienfeld 2020). We used standardized beta

392 estimates to measure effect sizes. Assumption checks revealed no significant problems with

393 multicollinearity, non-linearity, heteroscedasticity, outliers, or non-independence of errors. COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 17

394 However, most error distributions showed some departure from normality. To account for this,

395 we report bootstrapped confidence intervals (standardized). We also repeated relevant analyses

396 using ordinal logistic regression, which produced results consistent with the linear models

397 reported in the main text (see Section 3 in the supplemental material).

398 As a follow-up to examine the unexpected relationship between SDO and the mean of

399 conformist/norm-enforcement items (Items B.1–12), we also conducted a principal

400 components analysis with oblique rotation (Oblimin) on all the conformist/norm-enforcement

401 items. The Kaiser–Meyer–Olkin measure verified the sampling adequacy for the analysis KMO

402 = .889, considered “great” (Hutcheson and Sofroniou 1999), and all KMO values for individual

403 items were > .719 (well above the acceptable limit of .5). Bartlett’s test of sphericity, χ² (120)

404 = 4613, p < .001, indicated that correlations between items were sufficiently large for principal

405 component analysis.

406 RESULTS

407 We report only the results for our variables of interest (e.g., SDO and RWA) predicting our

408 pre-registered and other important outcome variables. In the supplemental material, we provide

409 correlations between all relevant variables and more detailed regression results, including

410 covariate effects.

411 (1) Cooperative, other-regarding and conformist, norm-enforcing responses to COVID-

412 19

413 (1a) Did SDO negatively predict cooperative, other-regarding responses? Yes (see

414 Table 1 and Figure 1). In line with our pre-registered prediction, SDO was a significant

415 negative predictor of the mean of all pre-registered cooperative, other-regarding items – RWA

416 was unrelated to this.

417 (1b) Did RWA positively predict conformist, norm-enforcing responses to COVID-19?

418 Yes (see Table 1 and Figure 1). As expected, RWA was a significant positive predictor of the COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 18

419 mean of all pre-registered conformist, norm-enforcing responses to COVID-19. While we did

420 not pre-register a prediction for SDO, we found that SDO was also a significant negative

421 predictor of this (see Table 1 and Figure1).

422 In order to better understand these relationships, we ran a principal components analysis on

423 the set of conformist, norm-enforcing items (B.1-B.12; see Methods). Four components had

424 eigenvalues over Kaiser’s criterion of 1 (Kaiser 1960) and in combination explained 75% of

425 the variance, with high internal reliabilities (Table 2). Interpretation of the factor loadings in

426 Table 2 suggest that PC1 captures support for lockdown rules, PC2 captures moral emotions

427 towards rule-breakers, PC3 captures support for strict border control, and PC4 captures support

428 for more severe government and military enforcement of lockdown rules. Table 1 shows

429 regression analyses examining whether RWA and SDO predicted these four principal

430 components. We found that, while RWA was a significant positive predictor of all of them,

431 SDO significantly negatively predicted only PC1 and PC2 (Table 1; Figure 1).

432 To investigate whether the putatively conformist, norm-enforcing responses of those low in

433 SDO might be a result of other-regarding preferences, we examined which of the conformist,

434 norm-enforcing responses were predicted by the centred mean of our measure of Empathic

435 Concern (controlling for RWA and the same covariates that were included in the relevant

436 models in Table 1). We found that Empathic Concern shows the same pattern as low SDO,

437 predicting the mean of all conformist, norm-enforcing responses, and specifically PC1 and PC2

438 (Table 3). In addition, analysis using the ‘Lavaan’ package in R showed that, in each case this

439 relationship was mediated by SDO, suggesting Empathic Concern and SDO explain common

440 variance in the three outcome measures (see Figure S1 in the supplemental materials).

COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 19

Table 1. Multiple regression analyses with centred means of RWA and SDO predicting the means of cooperative/other- regarding and conformist/norm-enforcing responses to COVID-19, including different types of conformist/norm-enforcing responses revealed by principal components analysis (PC1–4 = Principal Component 1–4). All pre-registered covariates were included in initial models. Only results for RWA and SDO for best fitting models are shown here (see the supplemental material for results for covariates included in these models).

Bootstrapped 95% Predictors B (unstd.) β (std.) SE (std.) t p CI (std.)

Cooperative, other-regarding responses to COVID-19:

Model 1. Mean cooperative/other-regarding R2 = 0.14, F(5, 427) = 13.40, p < .001 RWA 0.03 0.04 0.06 0.66 .508 [-0.06, 0.13] SDO -0.27 -0.36 0.06 -6.44 <.001* [-0.49, -0.25]

Conformist, norm-enforcing responses to COVID-19:

Model 2. Mean conformist/norm-enforcing R2 = 0.1, F(3, 421) = 15.58, p < .001 RWA 0.31 0.39 0.06 6.68 <.001* [0.26, 0.50] SDO -0.18 -0.21 0.06 -3.62 <.001* [-0.35, -0.08]

Model 3. Support lockdown rules (PC1) R2 = 0.06, F(3, 429) = 9.08, p < .001 RWA 0.14 0.18 0.06 3.05 .002* [0.05, 0.29] SDO -0.26 -0.30 0.06 -5.09 <.001* [-0.44, -0.15]

Model 4. Moral emotions towards rule breaker (PC2) R2 = 0.05, F(3, 421) = 6.73, p < .001 RWA 0.27 0.24 0.06 4.07 <.001* [0.13, 0.36] SDO -0.18 -0.14 0.06 -2.42 .016* [-0.28, -0.02]

Model 5. Support strict border control (PC3) R2 = 0.13, F(2, 430) = 33.09, p < .001 RWA 0.45 0.40 0.06 7.11 <.001* [0.30, 0.50] SDO -0.08 -0.06 0.06 -1.09 .275 [-0.16, 0.03]

Model 6. Support severe enforcement (PC4) R2 = 0.18, F(2, 430) = 48.1, p < .001 RWA 0.69 0.47 0.05 8.73 <.001* [0.35, 0.59] SDO -0.14 -0.09 0.05 -1.63 .104 [-0.21, 0.04] * = significant at p < .05

Figure 1. Standardized beta estimates with bootstrapped 95% confidence intervals (std.) for linear regressions with centred means of RWA and SDO predicting the means of cooperative/other-regarding responses, conformist/norm-enforcing responses, and different types of conformist/norm-enforcing responses revealed by principal components analysis (PC1–4 = Principal Component 1–4). All pre-registered covariates were included in initial models. Only results for RWA and SDO for best fitting models are shown here (see the supplemental material for results for covariates included in these models).

COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 20

Table 2. Summary of principal components analysis results for the conformist/norm-enforcement items (n=425) including pattern matrix, eigenvalues, percentage of variance, and Cronbach’s alpha for each principal component. Factor loadings over .40 appear in bold. Oblimin rotated factor loadings (Pattern matrix) PC1: PC2: Moral PC3: PC4: Support emotions Support Support

lockdown towards rule strict border severe rules breakers control enforcement (B.1) “It is important to follow the UK government's rules 0.85 0.04 0.08 -0.15 regarding COVID-19” (B.2) “Because of COVID-19, it is very important that others take physical distancing very seriously and limit all social 0.81 0.18 0.06 -0.25 contact” (B.3) “I support government measures to restrict the 0.87 0.00 0.06 0.03 movement of UK citizens to limit the spread of COVID-19” (B.4) “It makes me angry that the government would tell me where I can go and what I can do, even when there is a crisis 0.85 -0.05 -0.12 0.15 such as COVID-19” [reverse coded] (B.5) “I am upset at the thought that my government would 0.75 -0.07 -0.08 0.32 force people to stay home against their will” [reverse coded] (B.6) “It is vital right now that the government strongly 0.73 0.06 0.05 0.19 enforces social distancing measures” (B.7) “All citizens of China should be banned from entering -0.14 -0.01 0.92 0.07 the UK while the COVID-19 pandemic is ongoing” (B.8) “All citizens of the USA should be banned from 0.01 0.00 0.88 0.06 entering the UK while the COVID-19 pandemic is ongoing” (B.9) “Strict entry restrictions should be imposed at all 0.26 -0.02 0.74 -0.12 borders while the COVID-19 pandemic is ongoing” (B.10) “I want my government to severely punish those who 0.14 0.22 0.17 0.67 violate orders to stay home” (B.11) “The army should be mobilized to enforce quarantines 0.19 0.09 0.18 0.67 and rules regarding COVID-19” (B.12) “To what extent does K’s behaviour make you feel…” 0.04 0.89 0.00 0.02 (B.12.1) “… anger?” (B.12.2) “… disgust?” -0.03 0.88 0.00 0.05 (B.12.3) “… contempt?” 0.10 0.77 -0.02 -0.25 (B.12.4) “… outrage?” -0.03 0.91 -0.01 0.08 (B.12.5) “Finally, how do you think K should be treated?” 0.01 0.55 0.05 0.45 Eigenvalues 6.93 2.07 1.94 1.04 % of variance 0.43 0.13 0.12 0.07 α 0.89 0.89 0.81 0.77

Table 3. Multiple regression analyses with the centred mean of Empathic Concern, controlling for RWA and all relevant covariates (i.e., those included in relevant models in Table 1) predicting mean conformist/norm-enforcing responses to COVID-19 and different types of these responses as revealed by principal components analysis (PC1–4 = Principal Component 1–4). Only the results for Empathic Concern are shown here (see the supplemental material for results for all predictors).

IV: Mean Empathic Concern (centred) Model B β SE Bootstrapped DV t p R2 F df p (unstd.) (std.) (std.) 95% CI (std.) Mean conformist/norm-enforcing 0.17 0.15 0.05 2.80 .005* [0.04, 0.28] 0.10 12.43 (3, 358) <.001 Support lockdown rules (PC1) 0.18 0.15 0.05 2.86 .004* [0.04, 0.28] 0.03 3.10 (3, 353) .027 Moral emotions towards rule breaker (PC2) 0.27 0.16 0.05 3.09 .002* [0.05, 0.28] 0.06 7.76 (3, 348) <.001 Support strict border control (PC3) 0.10 0.06 0.05 1.19 .236 [-0.04, 0.16] 0.14 28.13 (2, 354) <.001 Support severe enforcement (PC4) 0.08 0.04 0.05 0.79 .433 [-0.07, 0.15] 0.18 39.56 (2, 354) <.001 * = significant at p < .05

441 (2) Change in ideology because of COVID-19 threats

442 (2a) Was there an increase in RWA, but not SDO, in response to COVID-19? Yes. In

443 line with our pre-registered prediction, there was a significant increase in mean RWA measured COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 21

444 during the pandemic (M = 3.576, SE = 0.057) compared to before the pandemic with a small

2 445 effect size (M = 3.517, SE = 0.054; t(432) = 2.837, p = .002, r = .018) while SDO remained

446 unchanged (before: M = 2.471, SE = 0.049; during: M = 2.480, SE = 0.053; t(432) = 0.311, p

2 447 = .756, r = 0).

448 (2b) Was the increase in RWA predicted by perceived and real pandemic-related

449 threats? Partly. Supporting our prediction, perceived threat – worrying about the pandemic –

450 had a significant positive effect on the change in RWA [B (unstd.) = 0.06, β (std.) = 0.17, SE

451 (std.) = 0.05; t = 3.59, p < .001, bootstrapped 95% CI: [0.08, 0.28]; model: F(5, 405) = 4.68, p

2 452 < .001, R = 0.05)]. However, against our prediction, proxies of actual exposure to COVID-19

453 threats did not significantly predict the change in RWA [B (unstd.) = 0.00, β (std.) = -0.01, SE

454 (std.) = 0.12; t = -0.06, p = .953; bootstrapped 95% CI: [-0.22, 0.22]; model: F(3, 429) = 2.67,

2 455 p = .047, R = 0.02].

456 (3) Perceived threat of COVID-19

457 (3a) Did RWA predict general threat-sensitivity? Mostly (see Table 4 and Figure 2). In

458 line with our predictions, RWA was a significant positive predictor of worrying about the

459 pandemic, getting sick, familiar others (family and friends) getting sick, personal finances, and

460 the economy. RWA also showed a positive relationship with worrying about unfamiliar others

461 getting sick, although this was not significant at the .05 level.

462 (3b) Did SDO only negatively predict sensitivity to threats conceptually related to

463 concern for others? Yes (see Table 4 and Figure 2). As expected, SDO significantly

464 negatively predicted worrying about the pandemic in general, and specifically about familiar

465 (family and friends) and unfamiliar others getting sick.

466 For three of the above regressions – predicting change in RWA from worry about the

467 pandemic (2b), and predicting worry about the pandemic from RWA (3a) and SDO (3b), the

468 best fitting models included participants’ ideological position on a unidimensional left-right COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 22

469 spectrum. In order to test whether our interpretation of these analyses is contingent on the

470 inclusion of this measure, we repeated the three regressions with the unidimensional measure

471 excluded. We found no appreciable change in the parameters of interest (Tables S5 and S8),

472 although the 95% confidence interval for the effect of RWA on worry about the pandemic

473 shifted slightly to include zero (from [0.03, 0.28] to [-0.01, 0.23]; Table S8).

Table 4. Multiple regression analyses with centred means of RWA and SDO predicting worried/threat-sensitive responses to COVID-19. All pre-registered covariates were included in initial models, but only results for RWA and SDO for best fitting models are shown here (see the supplemental material for results for covariates included in these models).

Bootstrapped 95% Predictors B (unstd.) β (std.) SE (std.) t p CI (std.)

Model 1. Worry about pandemic R2 = 0.11, F(9, 401) = 5.55, p < .001 RWA 0.19 0.16 0.06 2.48 .014* [0.05, 0.27] SDO -0.18 -0.14 0.06 -2.33 .020* [-0.28, -0.01]

Model 2. Worry about getting sick R2 = 0.12, F(5, 419) = 11.09, p < .001 RWA 0.29 0.19 0.06 3.14 .002* [0.06, 0.30] SDO -0.15 -0.09 0.06 -1.58 .114 [-0.20, 0.03]

Model 3. Worry about familiar others getting sick R2 = 0.05, F(4, 420) = 6.05, p < .001 RWA 0.19 0.16 0.06 2.57 .011* [0.04, 0.28] SDO -0.24 -0.17 0.06 -2.91 .004* [-0.31, -0.04]

Model 4. Worry about unfamiliar others getting sick R2 = 0.09, F(5, 419) = 8, p < .001 RWA 0.14 0.10 0.06 1.63 .104 [-0.01, 0.21] SDO -0.33 -0.22 0.06 -3.7 <.001* [-0.34, -0.10]

Model 5. Worry about personal finances R2 = 0.08, F(3, 421) = 12.43, p < .001 RWA 0.26 0.18 0.06 2.99 .003* [0.06, 0.29] SDO -0.04 -0.03 0.06 -0.43 .664 [-0.15, 0.10]

Model 6. Worry about economy R2 = 0.11, F(4, 420) = 12.91, p < .001 RWA 0.25 0.23 0.06 3.91 <.001* [0.12, 0.36] SDO -0.01 -0.01 0.06 -0.13 .898 [-0.13, 0.12] * = significant at p < .05

Figure 2. Standardized beta estimates, with bootstrapped 95% confidence intervals (std.), for linear regressions with centred means of RWA and SDO predicting worried, threat-sensitive responses to COVID-19. All pre-registered covariates were included in initial models. Only results for RWA and SDO for best fitting models are shown here (see the supplemental material for results for covariates included in these best fitting models). COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 23

474 DISCUSSION

475 We found support for each of the three basic predictions derived from the dual evolutionary

476 foundations of political ideology: (1) SDO negatively predicted cooperative, other-regarding

477 responses to the pandemic, while RWA positively predicted all of the conformist, norm-

478 enforcing responses that we measured; (2) RWA (and not SDO) increased following the

479 outbreak of the pandemic and the magnitude of this effect was predicted by perceived pandemic

480 threat (worry about the pandemic); and (3) RWA positively predicted worry across different

481 domains of pandemic threats, while SDO negatively predicted worry specifically about others.

482 These effects persist when accounting for age, sex, race, socioeconomic status, and left-right

483 political affiliation, suggesting that the dual dimensions of political ideology uniquely explain

484 responses to the COVID-19 pandemic. Below, we discuss each of our results in turn.

485 (1) Cooperative, other-regarding and conformist, norm-enforcing responses to

486 COVID-19. As expected, people low in SDO were more likely to display cooperative, other-

487 regarding attitudes and policy preferences, while RWA was unrelated to these measures. Also

488 consistent with the dual foundations model, RWA positively predicted support for conformity

489 and norm enforcement responses, generally. This relationship held across all types of

490 conformist, norm-enforcing responses to the pandemic, including responses that relate most

491 obviously to the social control and group viability concerns theorized to underlie RWA (and

492 conformist ideology generally) – i.e., support for severe government and military enforcement

493 of lockdown rules and strict border control. Thus, people high in RWA seem to be motivated

494 by a desire for social control to stop the spread of the virus. We also found that people low in

495 SDO were likely to show conformist, norm-enforcing responses. Whilst this was not what we

496 initially predicted, our follow-up analyses revealed that this related to moral emotions towards

497 rule breakers and support for lockdown rules, but not the other dimensions of conformity/norm-

498 enforcement more obviously connected to social control and group viability. We suspected that COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 24

499 this was because the relationship between low SDO and conformity/norm-enforcement is

500 motivated by empathic concern, rather than social control. Consistent with this explanation, a

501 separate measure of empathic concern showed the same relationships with our measures of

502 norm-enforcing conformity as did low SDO. Moreover, mediation analyses indicated that SDO

503 and empathic concern explained common variance in the same three outcome measures:

504 support for lockdown rules, moral emotions towards rule breakers, and the mean of all

505 conformist, norm-enforcing responses. Taken together, these results suggest that, just as worry

506 about the pandemic among those low in SDO is related specifically to empathy and other-

507 regarding concerns, so their preferences for conformity and norm enforcement also relate to

508 empathic concerns. While the causal path tested in our mediation analyses is consistent with

509 trait level empathic concern predicting the above pandemic responses via a reduction in SDO,

510 our data and analysis cannot rule out alternative possible pathways – e.g., that SDO predicts

511 these conformist responses via empathic concern or that both variables reflect a more general

512 underlying predisposition.

513 (2) Change in ideology as a result of COVID-19 threats. Previous studies using

514 longitudinal data have found mixed results regarding the effect of pandemics on ideology

515 (Beall, Hofer, and Schaller 2016; Golec de Zavala et al. 2020; Inbar et al. 2016; Rosenfeld and

516 Tomiyama 2021). Our results add to evidence for a shift specifically towards authoritarian and

517 socially conservative views (Golec de Zavala et al. 2020), and show this effect generalizes to

518 the UK. Whilst we cannot prove the shift was caused by the pandemic, because we were not

519 able to compare populations with and without COVID-19 exposure, our results match our

520 theory-based predictions and are also in line with experimental evidence for a link between

521 COVID-19 threat and social conservatism (Karwowski et al. 2020). In addition, our finding

522 that perception of threat (worry about the pandemic) predicted the magnitude of participants’

523 change in RWA strongly suggests perceived threat posed by the pandemic was causally linked COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 25

524 to the increase in RWA. Further, the fact that exposure to real pandemic-related threats (e.g.,

525 knowing people diagnosed with the virus) did not predict change in RWA but perceived threat

526 (worrying about the pandemic) did, suggests that perceived threat is the psychological

527 mechanism driving the increase in RWA. In retrospect, the primacy of perceived threat is not

528 surprising because threat perceptions must be the final determinants of responses to real threats,

529 while various social factors (such as signalling commitment to a political in-group,

530 misinformation from trusted in-group leaders, and lack of trust in science or mainstream media)

531 can distort how even very real threats are perceived (Bursztyn et al. 2020; Calvillo et al. 2020;

532 Hall Jamieson and Albarracín 2020; Pennycook et al. 2021; Rodriguez et al. 2020; Rothgerber

533 et al. 2020; Samore et al. 2021).

534 (3) Perceived threat of COVID-19. Our findings regarding threat-sensitivity are also

535 generally in accordance with the dual evolutionary foundations model, confirming an

536 association between RWA and threat-sensitivity: RWA predicted increased worry about all the

537 threats that we measured, although this relationship was not statistically significant for worry

538 about unfamiliar others getting sick. This exception is itself interesting because such a worry,

539 more than any other, reflects empathic concern for others, rather than a threat to oneself or

540 one’s immediate group. More generally, our results support our prediction that people high in

541 RWA should display threat-sensitivity. While some prior research has emphasized that RWA

542 may be related to specific domains of threat such as violence or dangerous out-groups (Brandt

543 et al. 2021; Duckitt and Fisher 2003; Sinn 2019) or non-zoonotic disease threats (Murray and

544 Schaller 2012; Terrizzi, Shook, and McDaniel 2013; Zmigrod et al. 2020), our results suggest

545 that RWA may be related to more domain-general threat-sensitivity. However, this should be

546 interpreted with caution since all the threats we measured are at least indirectly pandemic-

547 related. The dual evolutionary foundations model predicts that the SDO dimension of ideology

548 should be unrelated to most threats, but in contrast to people high in RWA, the greater empathic COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 26

549 concern of people low in SDO should make them specifically sensitive to threats to others.

550 Indeed, we found that people low in SDO were worried about the pandemic in general but were

551 specifically worried about the health of others, both familiar and unfamiliar, rather than threats

552 to their own health and finances or the economy. This suggests that prior work linking political

553 liberals to worry about the pandemic (Allcott et al. 2020; Barrios and Hochberg 2020; Calvillo

554 et al. 2020; Conway III et al. 2020; Dryhurst et al. 2020; Gadarian, Goodman, and Pepinsky

555 2021; Makridis and Rothwell 2020; Pennycook et al. 2021; Raihani and de Wit 2020;

556 Rothgerber et al. 2020) likely reflects mostly empathic concern for others (more than threat-

557 sensitivity) among people low in SDO in particular.

558 General discussion. Taken together, our results support the dual evolutionary foundations

559 model of political ideology (Claessens et al. 2020) and help to explain prior findings and

560 resolve apparent contradictions in the literature. Our findings reveal striking concordance

561 between low SDO and high RWA, showing that both are associated with worry about the

562 pandemic, and support of strong responses to it. This alignment between low SDO and high

563 RWA chimes with prior work showing economic progressives (who tend to score lower on

564 SDO) and social conservatives (who tend to score higher on RWA) are both concerned with

565 protection as opposed to freedom (Federico and Malka 2018; Malka et al. 2014; Malka, Lelkes,

566 and Soto 2019) – nevertheless we show that support for protection, at least in the context of

567 COVID-19, appears to reflect different psychological motives in the two groups. Our

568 theoretical model and results indicate that while low SDO responses to the pandemic are driven

569 by empathy, high RWA responses are driven by threat-sensitivity and a desire for conformity,

570 norm-enforcement (i.e., social control) and protection of the in-group. We can therefore explain

571 prior work linking liberal/progressive ideology (on a unidimensional spectrum) to increased

572 support for a strong COVID-19 response (Allcott et al. 2020; Barrios and Hochberg 2020; Van

573 Bavel et al. 2020; Clements 2020; Conway III et al. 2020; Everett et al. 2020; Gadarian, COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 27

574 Goodman, and Pepinsky 2021; Makridis and Rothwell 2020; Pennycook et al. 2021; Raihani

575 and de Wit 2020; Rothgerber et al. 2020) as due to the association between low SDO in

576 particular and empathy-driven concern for others. Conversely, by lumping together

577 conservatives high in RWA with conservatives high in SDO (who are more reluctant to make

578 personal sacrifices and behavioural changes that they see as only benefiting others and

579 negatively impacting the economy), studies on unidimensional ideology have likely masked

580 threat-sensitive, pro-lockdown responses among conservatives high in RWA.

581 Although these studies on unidimensional ideology seem to have mostly picked up the

582 effects of the co-operation/competition dimension (SDO) and missed the effects of the

583 conformity/individualism dimension (RWA), it is worth noting that the dual foundations model

584 does not predict that this will always be the case. On the contrary, unidimensional measures of

585 ideology may very well pick up the effects of the conformity/individualism dimension (RWA)

586 and not the co-operation/competition dimension (SDO) in some populations, or they may not

587 reveal any differences between political liberals and conservatives. Indeed, most studies on

588 unidimensional ideology that find less concern among conservatives than liberals were

589 conducted in the US, with its unique political climate (e.g., particularly strong polarization and

590 Donald Trump who downplayed the threat), but other studies on unidimensional ideology find

591 that conservatives in Mexico and South Korea are more concerned than liberals (Dryhurst et

592 al. 2020), and some but not all unidimensional studies find no differences between liberals and

593 conservatives in concern about COVID-19 in the UK (Dryhurst et al. 2020; Pennycook et al.

594 2021; Raihani and de Wit 2020).

595 Our findings are also consistent with prior work linking conservatism to general threat-

596 sensitivity (Feldman 2013; Hibbing, Smith, and Alford 2014; Shaffer and Duckitt 2013) and

597 the observed COVID-19 response efficacy among right-leaning countries like Saudi Arabia

598 (Frey, Chen, and Presidente 2020; Gelfand et al. 2021). We find that RWA has increased in the COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 28

599 UK following the outbreak of COVID-19, and that support for government COVID-19

600 responses among conservatives is linked to a focus on conformity and norm-enforcement

601 among those high in RWA in particular. Similarly, national-level studies have tended to focus

602 on measures of the conformist dimension of ideology, such as collectivism and cultural

603 ‘tightness’ (Frey, Chen, and Presidente 2020; Gelfand et al. 2021). The inherently groupish

604 focus of conformist ideology may also make it a particularly important predictor of response

605 strategy at the national level.

606 Whilst the size of the ideological effects we observe is at least as large as other demographic

607 predictors of responses to the pandemic, it is worth noting that a considerable portion of the

608 variance in responses remains unexplained in our models. Other factors, such as partisan

609 politics and the fact that conservatives and progressives follow different leaders and sources of

610 information undoubtedly also play a role (Allcott et al. 2020; Barrios and Hochberg 2020;

611 Bursztyn et al. 2020; Calvillo et al. 2020; Clinton et al. 2021; Conway III et al. 2020; Cornelson

612 and Miloucheva 2020; Gadarian, Goodman, and Pepinsky 2021; Gollwitzer et al. 2020; Hall

613 Jamieson and Albarracín 2020; Makridis and Rothwell 2020; Painter and Qiu 2021; Pennycook

614 et al. 2021; Rodriguez et al. 2020; Rothgerber et al. 2020; Samore et al. 2021). For example, a

615 recent US-based study shows that higher trust in Trump, lower trust in

616 liberal/moderate/scientific information, and higher economic conservatism are driving the lack

617 of precautionary behaviours found among socially conservative Republicans and Independents

618 (Samore et al. 2021). Crucially, however, when controlling for these factors, conformist

619 socially conservative views significantly predict greater precautionary behaviours among

620 Republicans and Independents. Future work on the relationship between the dual foundations

621 and other pandemic responses may be able to include measures of these variables.

622 The results we report are based on a sample of participants from across the general

623 population of the UK, spanning a range of demographic groups and political affiliations. COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 29

624 However, the psychological mechanisms underlying the dual evolutionary foundations of

625 political ideology are expected to apply to human group living generally. Consistent with this,

626 cross-country data show that pandemic responses are stronger in authoritarian and culturally

627 tight nations (Frey, Chen, and Presidente 2020; Gelfand et al. 2021) and longitudinal and

628 experimental data show a link between COVID-19 threat and a shift towards conformist

629 ideology in particular (e.g., increased RWA but not SDO) in both the US and Poland (Golec

630 de Zavala et al. 2020; Karwowski et al. 2020). Moreover, as we note above, even in the US

631 where President Donald Trump and the more conservative Republican party has tended to

632 minimize the risk of COVID-19 and eschew strong government response, socially conservative

633 views among Republicans and Independents remain positively related to precautionary

634 behaviours (Samore et al. 2021) after controlling for Trump support and a range other factors.

635 Even without controlling for these variables, there is evidence that, in the USA, people high in

636 RWA (and left-wing authoritarianism) respond to the pandemic in a strict norm-enforcing

637 manner (Manson 2020), and people high in ‘binding’ moral foundations (in-group loyalty,

638 purity, and authority; similar to high RWA) and ‘individualizing’ moral foundations (care and

639 fairness; similar to low SDO) show more concern about the pandemic (Sloan et al. 2021). We

640 also expect the patterns we find to apply outside the context of modern nation states – for

641 example, in small-scale societies responding to more local disease threats – however, testing

642 this would require the development of survey instruments that can be tailored to the local socio-

643 political and economic context.

644 Beyond their implications for understanding political ideology, our findings are also likely

645 to be of interest to politicians, policymakers, and communicators seeking to manage the

646 response to pandemics like COVID-19. It is clear that effective collective response requires

647 broad political support and can be undermined if responses to the pandemic become politically

648 polarized. Our findings indicate that support for a strong response to the pandemic can come COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 30

649 from the political left and right, but that it rests on two very different psychological drives that

650 we all possess to some degree – a desire for co-operation motivated by empathic concern for

651 others (including unknown others) that is stronger among those low in SDO (who tend to be

652 on the political left), and a desire for strict social control to mitigate threats to the self and the

653 nation that is stronger among those high in RWA (who tend to be on the political right).

654 Communicators seeking to generate bi-partisan support need to acknowledge and appeal to

655 both sets of concerns. It may also be wise to appeal to values held by people high in SDO or

656 low in RWA to encourage compliance from these otherwise resistant groups (e.g., by

657 mentioning that more co-operation and compliance with rules may lead to a quicker return to

658 normal economic life and personal freedoms). Moreover, our finding that RWA increases in

659 response to the pandemic suggests that social control may become more important to people

660 as the pandemic progresses.

st 661 Whilst a global pandemic like COVID-19 is unprecedented in the 21 century, the basic

662 human drives inherent to the way we respond have deep evolutionary roots – a trade-off

663 between co-operation for the common good and self-interested competition, and a trade-off

664 between conformity and enforcement to protect the group and individual freedom. The dual

665 evolutionary foundations of political ideology provide a principled framework with which to

666 connect these basic social drives to the modern political landscape and individual responses to

667 the COVID-19 pandemic, connections which we hope can help us unite in tackling the

668 challenges it presents.

COVID-19 PANDEMIC AND POLITICAL IDEOLOGY 31

669 Supplementary Material

670 Supplementary material for this article is available at

671 https://osf.io/mv2j6/?view_only=2c24869169934b5993841c1eb4058bbf

672 Data Availability Statement

673 The data, replication instructions, and the data’s codebook can be found at

674 https://osf.io/mv2j6/?view_only=2c24869169934b5993841c1eb4058bbf

675 Author Contributions Statement

676 KF designed the study with input from QDA and AC. KF collected the data and ran all

677 analyses. All authors contributed to writing the manuscript.

678 Competing Interests

679 We declare that none of the authors have competing financial or non-financial interests.

680 Acknowledgments

681 We wish to thank Scott Claessens for checking the code and helpful suggestions regarding

682 some of the statistical analyses.

683 Funding

684 This work was supported by a Royal Society of New Zealand Marsden Fund grant (#17-

685 UOA-074) and a Rutherford Discovery Fellowship (#11-UOA-019) to QDA. The funders had

686 no role in the preparation of the manuscript or the decision to publish.

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