Political tolerance is a core democratic value, yet a long-standing research agenda suggests that citizens are unwilling to put this value into practice when confronted by groups that they dislike. One of the most disliked groups, especially in recent times, are those promoting racist ideologies. Racist speech poses a challenge to the ideal of political tolerance because it challenges another core tenet of democratic politics – the value of equality. How do citizens deal with threats to equality when making decisions about what speech they believe should be allowed in their communities? In this article, we contribute to the rich literature on political tolerance, but focus on empathy as a key, and understudied, personality trait that should be central to how – and when – citizens reject certain types of speech. Empathy as a cognitive trait relates to one’s capacity to accurately perceive the feeling state of another person. Some people are more prone to worry and care about the feelings of other people, and such empathetic people should be most likely to reject speech that causes harm. Using a comparative online survey in Canada (n = 1,555) and the United States (n = 1627) conducted in 2017, we examine whether empathetic personalities - as measured by a modified version of the Toronto Empathy Scale - predict the tolerance of political activities by “least-liked” as well as prejudicially motivated groups. Using both a standard least-liked political tolerance battery, as well as a vignette experiment that manipulates group type, we test whether higher levels of trait empathy negatively correlate with tolerance of racist speech. Our findings show that empathy powerfully moderates the ways in which citizens react to different forms of objectionable speech.
We tested a novel method for studying human experience (thoughts and affect). We utilized Cognitive-Affective Maps (CAMs)–an approach to visually represent thoughts and their affective connotations as networks of concepts that individuals associate with a given event. Using an innovative software tool, we recruited a comparative sample of (n = 93) Canadians and (n = 100) Germans to draw a CAM of their experience (events, thoughts, feelings) with the Covid-19 pandemic. We treated these CAM networks as a series of directed graphs and examined the extent to which their structural properties (latent and emotional) are predictive for the perceived coronavirus threat (PCT). Across multiple models, we found consistent and significant relationships between these network variables and the PCT in both the Canadian and German sample. Our results provide unique insights into individuals' thinking and perceptions of the viral outbreak. Our results also demonstrate that a network analysis of CAMs' properties is a promising method to study the relationship between human thought and affective connotation. We suggest that CAMs can bridge several gaps between qualitative and quantitative methods. Unlike when using quantitative tools (e.g., questionnaires), participants' answers are not restricted by response items as participants are free to incorporate any thoughts and feelings on the given topic. Furthermore, as compared to traditional qualitative measures, such as structured interviews, the CAM technique may better enable researchers to objectively assess and integrate the substance of a shared experience for large samples of participants.
Political scientists recognize discriminatory attitudes as key to understanding a range of political preferences. Sexism is associated with both explicitly and non-explicitly gendered attitudes. But why do certain individuals display discriminatory attitudes, while others do not? Drawing from psychology, we examine the potential power of an underexplored set of personality traits—secure versus fragile self-esteem—in explaining gendered attitudes and preferences. With an online sample of (N = 487) U.S.-based participants, we find that fragile self-esteem is an important trait underlying individuals’ attitudes: individuals who display a discordant view of self—explicitly positive but implicitly negative—are more likely to hold hostile sexist attitudes and prefer men in leadership; these individuals are also more likely to support the Republican Party and former U.S. president Donald Trump. While present in only a fraction of the population, our results suggest that this trait may be important for understanding the development of discriminatory attitudes toward out-groups.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.