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The spatial grounding of politics

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Abstract

In three studies, we advance the research on the association between abstract concepts and spatial dimensions by examining the spatial anchoring of political categories in three different paradigms (spatial placement, memory, and classification) and using non-linguistic stimuli (i.e., photos of politicians). The general hypothesis that politicians of a conservative or socialist party are grounded spatially was confirmed across the studies. In Study 1, photos of politicians were spontaneously placed to the left or right of an unanchored horizontal line depending on their socialist-conservative party affiliation. In Study 2, the political orientation of members of parliament systematically distorted the recall of the spatial positions in which they were originally presented. Finally, Study 3 revealed that classification was more accurate and faster when the politicians were presented in spatially congruent positions (e.g., socialist politician presented on the left side of the monitor) rather than incongruent ones (e.g., socialist on the right side). Additionally, we examined whether participants’ political orientation and awareness moderated these effects and showed that spatial anchoring seems independent of political preference but increases with political awareness.

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Availability of data, material, and code

All data and analysis scripts are openly available at the website of the Open Science Framework (https://osf.io/st7h4/?view_only=7c71d87c136249d184855617179482ce).

Notes

  1. The photos of politicians used were taken from the following parliamentary website: https://www.parlamento.pt/DeputadoGP/Paginas/Deputados.aspx. However, the parliament changes at least every 4 years, so it is possible that not all the photos of politicians we have used are still available.

  2. As we were assigned a larger subject pool than expected, participants in Experiment 1 exceeded the sample size suggested by the power analysis. To ensure that the effect holds up to empirical scrutiny with a sample size suggested by power analysis, we removed the 40 last-run participants from Experiment 1, and thus equated the number of participants per experiment. In short, the analyses run on the data from 50 participants showed an almost identical pattern of results as the analyses run on the data from 90 participants. Specifically, the results showed that politician’s party membership was not a significant predictor (estimate =  − 0.28, SE = 0.22, t =  − 1.29, p = .23, 95% CI [− 0.71, 0.15]) of participants’ responses. However, introducing participants’ political orientation and political awareness to the model as additional predictors revealed a significant interaction between the politicians’ party membership and participants’ political awareness (estimate =  − 0.30, SE = 0.09, t =  − 3.30, p = .001, 95% CI [− 0.48, − 0.12]).

  3. We excluded this participant’s data as the accuracy of only 10% would lead to the removal of 90% of observations during the analysis of response times, where only correct responses were considered. The analysis done on the accuracy data including this participant revealed an almost identical pattern of results. Specifically, there was a significant interaction between politicians’ party membership and screen side (estimate = 0.16, SE = 0.05, z = 3.44, p = .001, 95% CI [0.07, 0.25]), reflecting the fact that participants classified socialist politicians more accurately when they appeared on the left side (estimate = 0.15, SE = 0.06, z = 2.35, p = .019, 95% CI [0.02, 0.28]); and conservative politicians when they appeared on the right side (estimate =  − 0.16, SE = 0.06, z =  − 2.53, p = .012, 95% CI [− 0.29, − 0.04]).

  4. Notably, truly right-wing participants made up only about 14% of the sample (see “Appendix 1”), and therefore these results should be interpreted with caution. Further statistical analyses regarding the moderating role of political orientation and awareness in spatial-grounding effects are provided in “Appendix 2”.

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Funding

The research reported here was supported by the Fundação para a Ciência e Tecnologia, Portugal, with Grants awarded to the third (SFRH/BPD/115533/2016) and fourth (FCT-UID/04810/2020) authors.

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Correspondence to Margarida V. Garrido.

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Appendices

Appendix 1

Participants’ distribution (in proportions) according to their levels of political orientation and awareness in Experiments 1–3.

Experiment

Orientation

Awareness

Left (%)

Center (%)

Right (%)

Low (%)

Average (%)

High (%)

Exp. 1

36

30

34

21

2

77

Exp. 2

54

29

17

52

4

44

Exp. 3

55

31

14

55

4

41

Participants’ levels of political orientation and awareness were assessed with 7-point scales (political orientation: 1 = left and 7 = right; political awareness: 1 = very low; 7 = very high). Therefore, participants with average scores below 4 were considered left-oriented and with low political awareness; and with average scores above 4 were considered right-oriented and with high political awareness. Participants with mean scores of 4 were considered as being at the center of the political spectrum and having an average political awareness.

Appendix 2

Exploratory analyses

In Experiment 3, we found a significant interaction between participants’ political orientation, screen side, and politicians’ party membership for response time data. However, right-wing participants made up only about 14% of the sample, and it is, therefore, difficult to determine the strength of this moderation effect. To quantify the amount of evidence in favor of an effect of political orientation on participants’ responses, we performed likelihood ratio comparisons using the anova function in R.

First, we checked whether a three-way interaction between the side, political position, and political awareness contributes to increased predictive accuracy. To this end, we compared the model that includes all possible main effects, two-way interactions, and a three-way interaction (R syntax of fixed effects: scaled.RT ~ side * position * zscore.awareness) with the model that includes all possible main effects and two-way interactions (scaled.RT ~ side * position + position * zscore.awareness + side * zscore.awareness). As shown in Table 1 (model 1 vs. model 2), the estimates of prediction accuracy favored model 2 that includes a three-way interaction.

Second, we checked whether a three-way interaction between the side, political position, and political orientation contributes to increased predictive accuracy. To this end, we compared the model that includes all possible main effects, two-way interactions, and a three-way interaction (scaled.RT ~ side * position * zscore.orientation) with the model that includes all possible main effects and two-way interactions (scaled.RT ~ side * position + position * zscore.orientation + side * zscore.orientation). As shown in Table 1 (model 3 vs. model 4), the estimates of prediction accuracy favored model 4 that includes a three-way interaction.

Third, we checked whether a three-way interaction between the side, political position, and political awareness together with a three-way interaction between the side, political position, and political orientation contribute to increased predictive accuracy, compared to when only a three-way interaction between the side, political position, and political awareness is considered. To this end, we compared the model that includes all possible main effects, two-way interactions, and two three-way interactions (scaled.RT ~ side * position * (zscore.orientation + zscore.awareness)) with the model that includes all possible main effects, two-way interactions, and only one three-way interaction (scaled.RT ~ position * zscore.orientation + side * zscore.orientation + side * position * zscore.awareness). As shown in Table 1 (model 5 vs. model 6), the Akaike information criterion (AIC) favored model 6 that includes two three-way interactions. At the same time, the Bayesian information criterion (BIC) favored model 5 that includes only one three-way interaction. Thus, the result of political orientation for representation of the political space needs to be interpreted with caution.

Table 1 The performance indices of the models used in Experiment 3

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Garrido, M.V., Farias, A.R., Horchak, O.V. et al. The spatial grounding of politics. Psychological Research 87, 84–95 (2023). https://doi.org/10.1007/s00426-022-01654-2

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