Racial stereotyping of gay men: Can a minority sexual orientation erase race? Christopher D. Petsko, Galen V. Bodenhausen. Journal of Experimental Social Psychology, Volume 83, July 2019, Pages 37-54, https://doi.org/10.1016/j.jesp.2019.03.002
Abstract: Decades of research indicate that the traits we ascribe to people often depend on their race. Yet, the bulk of this research has not considered how racial stereotypes might also depend on other aspects of targets' identities. To address this, researchers have begun to ask intersectional questions about racial stereotypes, such as whether they are applied in similar ways to men and women, or to children and adults. In the present studies, we examine whether men who are described as gay (vs. not) become de-racialized in the minds of perceivers. That is, we test whether gay (vs. non-gay) men are perceived as less stereotypic of their own racial or ethnic groups. Results consistently support the de-racialization hypothesis, regardless of whether targets are Black, White, Asian, or Hispanic. Moreover, when Black and Hispanic men are described as gay (vs. not), they become stereotypically “Whitened” in addition to seeming less stereotypic of their own racial groups. This “Whitening” effect is explained by Black and Hispanic men's seeming more affluent when described as gay (vs. when not), an effect that holds even when controlling for changes in these men's stereotypic femininity. Collectively, these findings underscore the point that race and sexual orientation are not orthogonal in the minds of perceivers. A minority sexual orientation can alter the racial characteristics ascribed to men, reducing the perceived presence of race-typical traits and, for low-SES men, increasing their perceived “Whiteness.”
Thursday, March 28, 2019
Leaders of gov't-favored firms are more likely to agree with sometimes contradictory ideas like markets should be generally free, but at present, the US market is too free, & competition is unfair
Matthew D. Mitchell, with Scott Eastman and Tamara Winter. “A Culture of Favoritism: Corporate Privilege and Beliefs about Markets and Government.” Mercatus Special Study, Mercatus Center at George Mason University, Arlington, VA, March 27 2019. https://www.mercatus.org/publications/corporate-welfare/culture-favoritism
Abstract: This paper discusses a national survey of business leaders that sought to determine how government favoritism toward particular firms correlates with attitudes about government, the market, and selectively favorable economic policy. Findings indicate that those individuals who believe they work for favored firms are more likely to approve of free markets in the abstract but also more likely to say the US market is currently too free. These individuals are more skeptical of competition and more inclined to approve of government intervention in markets. They also are more likely to approve of government favoritism and to believe that favoritism is compatible with a free market. Those who have direct experience with economic favoritism or are more attuned to such favoritism are more likely to have distorted perceptions of free- market capitalism and are more comfortable with further favoritism.
Keywords: favoritism, culture, corporate welfare, privilege, rent-seeking, cronyism, crony capitalism
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From the summary: Compared with other business leaders, the leaders of favored firms are more likely to agree with the following— sometimes contradictory—statements:
How Favored Firms Think about Markets
* Markets should be generally free (at least in the abstract), and a freer market serves the general public.
* But at present, the US market is too free, and competition is unfair to business.
How Favored Firms Think about Government
* Government should more heavily regulate markets.
* Regulations benefit consumers.
* Regulations benefit the economy.
* Competition is limited by government (they may view this as a good thing, given their belief that competition is unfair to business).
How Favored Firms Think about Favoritism
* Government should favor specific businesses and industries.
* Markets should be free, and government should favor particular firms (a contradictory set of beliefs).
* Government assistance has a positive effect on the economy.
* Customer focus and a unique business model are not the most important factors in business success.
* The most important factors in business success are either knowledge of influential policymakers or government assistance.
Consequences of Favoritism
In some quarters of the business world a culture exists that legitimizes government favoritism. It encourages business leaders to seek government privileges and policymakers to offer them. Not only is this culture of favoritism expensive to taxpayers and consumers, it may also undermine the public’s faith in markets and economic freedom. If such attitudes persist or expand, then free, open, and competitive markets may be in peril. We risk stunted economic growth, wasted resources, and higher levels of corruption as a result.
Abstract: This paper discusses a national survey of business leaders that sought to determine how government favoritism toward particular firms correlates with attitudes about government, the market, and selectively favorable economic policy. Findings indicate that those individuals who believe they work for favored firms are more likely to approve of free markets in the abstract but also more likely to say the US market is currently too free. These individuals are more skeptical of competition and more inclined to approve of government intervention in markets. They also are more likely to approve of government favoritism and to believe that favoritism is compatible with a free market. Those who have direct experience with economic favoritism or are more attuned to such favoritism are more likely to have distorted perceptions of free- market capitalism and are more comfortable with further favoritism.
Keywords: favoritism, culture, corporate welfare, privilege, rent-seeking, cronyism, crony capitalism
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From the summary: Compared with other business leaders, the leaders of favored firms are more likely to agree with the following— sometimes contradictory—statements:
How Favored Firms Think about Markets
* Markets should be generally free (at least in the abstract), and a freer market serves the general public.
* But at present, the US market is too free, and competition is unfair to business.
How Favored Firms Think about Government
* Government should more heavily regulate markets.
* Regulations benefit consumers.
* Regulations benefit the economy.
* Competition is limited by government (they may view this as a good thing, given their belief that competition is unfair to business).
How Favored Firms Think about Favoritism
* Government should favor specific businesses and industries.
* Markets should be free, and government should favor particular firms (a contradictory set of beliefs).
* Government assistance has a positive effect on the economy.
* Customer focus and a unique business model are not the most important factors in business success.
* The most important factors in business success are either knowledge of influential policymakers or government assistance.
Consequences of Favoritism
In some quarters of the business world a culture exists that legitimizes government favoritism. It encourages business leaders to seek government privileges and policymakers to offer them. Not only is this culture of favoritism expensive to taxpayers and consumers, it may also undermine the public’s faith in markets and economic freedom. If such attitudes persist or expand, then free, open, and competitive markets may be in peril. We risk stunted economic growth, wasted resources, and higher levels of corruption as a result.
Users are likely to argue over wide ideological divides, and are increasingly likely to engage with those who are different from themselves
Why Keep Arguing? Predicting Engagement in Political Conversations Online. Sarah Shugars, Nicholas Beauchamp. SAGE Open, March 27, 2019. https://doi.org/10.1177/2158244019828850
Abstract: Individuals acquire increasingly more of their political information from social media, and ever more of that online time is spent in interpersonal, peer-to-peer communication and conversation. Yet, many of these conversations can be either acrimoniously unpleasant or pleasantly uninformative. Why do we seek out and engage in these interactions? Who do people choose to argue with, and what brings them back to repeated exchanges? In short, why do people bother arguing online? We develop a model of argument engagement using a new dataset of Twitter conversations about President Trump. The model incorporates numerous user, tweet, and thread-level features to predict user participation in conversations with over 98% accuracy. We find that users are likely to argue over wide ideological divides, and are increasingly likely to engage with those who are different from themselves. In addition, we find that the emotional content of a tweet has important implications for user engagement, with negative and unpleasant tweets more likely to spark sustained participation. Although often negative, these extended discussions can bridge political differences and reduce information bubbles. This suggests a public appetite for engaging in prolonged political discussions that are more than just partisan potshots or trolling, and our results suggest a variety of strategies for extending and enriching these interactions.
Keywords: politics, social media, interpersonal communication, deliberation, polarization, natural language processing, topic models, sentiment
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Digital
communication plays a critical role in our political infrastructure.
Online platforms have expanded the reach of “kitchen table
conversations,” as people increasingly turn to social media as a primary
news source (Bakshy, Messing, & Adamic, 2015; Lee & Ma, 2012; O’Connor, Balasubramanyan, Routledge, & Smith, 2010) and elected officials use digital channels to communicate with their constituents (Farina, Epstein, Heidt, & Newhart, 2013; Kavanaugh et al., 2012). Such interactions are often modeled as one-shot games or as evidence of long-term links in a social network (Feng & Wang, 2013; Myers & Leskovec, 2014).
Yet, much online activity consists not of single-shot, unidirectional
interactions with elites, but repeated interactions among peers. These
iterated interactions—conversations—have important implications for
political theory: while conventional wisdom claims that brief social
media interactions have little effect on subsequent online behavior, a
number of recent experiments have shown modest but real effects of
single-shot interactions (Friggeri, Adamic, Eckles, & Cheng, 2014; Munger, 2017).
Deliberative theory suggests that repeated interpersonal interactions
where individuals engage in extended conversation may have even more
substantial effects (Axelrod, 1987; Bednar & Page, 2007; Habermas, 1984).
In this article, we focus not on persuasive outcomes but on the more fundamental question of what leads people to engage in extended online conversation and argument in the first place. Existing work in this area has generally had a more practical bent, focusing on tweet- or conversation-level recommendation and aiming to predict user interest in conversation threads to better curate and recommend targeted content. Such work has looked at user engagement in various forms of online conversation (Chen et al., 2012; He & Tan, 2015; Vosecky, Leung, & Ng, 2014; Yan, Lapata, & Li, 2012), as well as via retweeting (Feng & Wang, 2013; Hong, Doumith, & Davison, 2013) and re-entry back into existing conversations (Backstrom, Kleinberg, Lee, & Danescu-Niculescu-Mizil, 2013). Our work here is closest to the latter: We are more interested in the extended dynamics of conversation, particularly the decision to re-engage or exit, than in the initial decision to interact. We focus on users who have already made that initial participation, and seek to understand and predict whether and when they re-engage based on user, tweet, and thread-level features.
While ongoing deliberative conversation is the substantive focus here, this framing also turns an impossible problem—predicting initial responses to a tweet out of the entire pool of twitter users—into a practicable prediction task—predicting re-participation of users whom we know are already part of a conversation. This approach also conditions out the even harder problem of explaining the origins of an initial tweet or conversation, particularly given the immense variety of motivations behind those first moves. Instead, we focus on existing conversations—at least a first move followed by a response—and model the processes that lead to extended and branching conversations among existing participants. Twitter might seem less suited to such models than traditional online forums, but Twitter in fact produces immense quantities of impromptu extended, branching conversations, and by focusing only on re-entry by existing participants, we can study what causes individuals to continue an argument or drop out, bracketing the question of initial engagement.
By conditioning on existing user interaction, we aim to get more deeply at the question of why people bother arguing online. What brings them back to a repeated argument? What factors contribute to an individual returning to or abandoning an argument? While in face-to-face settings, social etiquette suggests that a comment will most likely be greeted with a response, there is no a priori reason to expect a response to the vast majority of online posts. While we expect to find many types of conversations occurring online, we might expect that more extreme content (positive or negative) will increase engagement, as trolls successfully incite arguments and partisan allies reinforce each other’s positions (Cheng, Danescu-Niculescu-Mizil, Leskovec, & Bernstein, 2017). Between the extremes lies a more productive and interesting mode of engagement: true deliberative argument, in which participants exchange content in a genuine attempt to persuade or inform. Such behavior is not as uncommon as skeptics might assume, and is prevalent in knowledge-sharing platforms such as StackOverflow, Yahoo! Answers, and other such forums, where users may be motivated to some degree out of a general sense of community (Adamic, Zhang, Bakshy, & Ackerman, 2008; Anderson, Huttenlocher, Kleinberg, & Leskovec, 2012; Oktay, Taylor, & Jensen, 2010) even as they argue over better or worse solutions to shared problems.
We find evidence for all of these behaviors in our data and, in particular, show that while many of these engagements are negative, conversations often cover a range of emotions and go on far longer than a single-shot attack or mutual trolling might suggest. While we leave for later the ultimate question of persuasive effect, we establish here that even a medium as apparently unpromising as Twitter is full of complex, extended political conversations, and that individuals’ decision to repeatedly re-engage in those conversations is surprisingly systematic.
Much
of the theoretical work around questions of conversational dynamics has
been done within the literatures of deliberation and persuasion. While
both these approaches focus their attention on back-and-forth
conversations, they vary in their characterization of those
conversations. The persuasion literature looks broadly at how people
convince others and “win” arguments, while the deliberative ideal
imagines thoughtful participants reasoning together to generate public
opinion centered on the common good (Cohen, 1989; Habermas, 1984). “Reasons” may constitute factual arguments or emotional appeals (Mansbridge, 2015), but ideal deliberation is often taken to be free of persuasion, coercion, or other forms of instrumental action (Habermas, 1984).
Contra persuasion models, ideal deliberators should engage in rational
speech acts—aiming to honestly express themselves and truly trying to
understand the other. Huckfeldt, Mendez, and Osborn (2004)
argue that ideal citizens “are those individuals who are able to occupy
the roles of tolerant gladiators—combatants with the capacity to
recognize and respect the rights and responsibilities of their political
adversaries” (p. 91) If political debate serves to sharpen our own
understanding and build our collective knowledge, then we owe it to our
interlocutors to press them on their positions, to find the holes in
their armor and encourage refinement of beliefs. The process of debate
makes us all better—thus allowing tolerant gladiators to walk away as
friends. Citizens who silence their discussants, seek to coerce others,
are easily persuaded by false beliefs, or who otherwise refuse to engage
in rational argument, therefore, do a disservice to themselves and to
their communities.
Experience tells us, however, that such a lofty deliberative ideal is rarely met in political conversation. Sunstein (2002) advances the “law of group polarization,” finding through numerous empirical studies that “deliberation tends to move groups, and the individuals who compose them, toward a more extreme point in the direction indicated by their own pre-deliberation judgments” (p. 175). Sunstein argues this polarization is the natural result of the social context, which serves as a significant driver of individual actions and opinions. Hearing friends express a view makes a person socially inclined to express the same view. In other words, deliberating groups tend toward extremism in the direction of the predeliberation median because nobody wants to take the social risk of expressing an unpopular view. Sanders (1997) similarly argues that the broader context of power dynamics frequently has a debilitating but under-recognized effect on deliberation, as marginalized individuals feel silenced and unable to share their true opinions. Importantly, the majority of participants may mistakenly assume that such power effects are negligible if “deliberation appears to be proceeding.”
Another line of work has tackled conversational dynamics from the perspective of the data-processing problem of platform curation, for example, trying to predict which posts will be popular for the purpose of highlighting those posts for users. Much of this work focuses on post-level engagement, predicting engagement as a function of topics (Hong et al., 2013) or social network structures (He & Tan, 2015; Pan, Cong, Chen, & Yu, 2013). Much of this work has considered “popularity” as a raw aggregate of engagement with an initial post, finding, perhaps unsurprisingly, that the popularity of a user’s past content is a strong predictor for the popularity of their future content (Artzi, Pantel, & Gamon, 2012). Backstrom et al. (2013) break the task into related subtasks: length prediction and re-entry prediction. Intuitively, these subtasks indicate distinctive types of threads: threads which are long because a high number of users chime in a small number of times—to offer congratulations or condolence, for example—while other threads are long because a small number of users contribute a large number of times in a back-and-forth conversation. Supporting this theory, Backstrom et al. (2013) find that the number of distinct users in long threads follows a bimodal distribution. Using data from Facebook and Wikipedia, Backstrom et al. (2013) find the identities of recent commenters is most predictive of conversation re-entry.
This lattermost line of work is largely atheoretical and not particularly concerned with normative issues. While the current study borrows many of their methods, we are also fundamentally interested in the dynamics of online conversation from a deliberative perspective. Thus, we are interested less in conversation recommendation or modeling engagement in conversations per se, and more focused on how individual speech acts (tweets) lead existing discussants to re-engage with each other or abandon a conversation. Regardless of the outcome of a conversation, it is important to understand what sustains conversations—particularly acrimonious ones—and keeps mutual opponents or supporters engaged with each other. As we will see, this engagement can take more or less productive forms, but simply understanding the deliberative dynamics is an important first step.
Abstract: Individuals acquire increasingly more of their political information from social media, and ever more of that online time is spent in interpersonal, peer-to-peer communication and conversation. Yet, many of these conversations can be either acrimoniously unpleasant or pleasantly uninformative. Why do we seek out and engage in these interactions? Who do people choose to argue with, and what brings them back to repeated exchanges? In short, why do people bother arguing online? We develop a model of argument engagement using a new dataset of Twitter conversations about President Trump. The model incorporates numerous user, tweet, and thread-level features to predict user participation in conversations with over 98% accuracy. We find that users are likely to argue over wide ideological divides, and are increasingly likely to engage with those who are different from themselves. In addition, we find that the emotional content of a tweet has important implications for user engagement, with negative and unpleasant tweets more likely to spark sustained participation. Although often negative, these extended discussions can bridge political differences and reduce information bubbles. This suggests a public appetite for engaging in prolonged political discussions that are more than just partisan potshots or trolling, and our results suggest a variety of strategies for extending and enriching these interactions.
Keywords: politics, social media, interpersonal communication, deliberation, polarization, natural language processing, topic models, sentiment
---
Introduction
In this article, we focus not on persuasive outcomes but on the more fundamental question of what leads people to engage in extended online conversation and argument in the first place. Existing work in this area has generally had a more practical bent, focusing on tweet- or conversation-level recommendation and aiming to predict user interest in conversation threads to better curate and recommend targeted content. Such work has looked at user engagement in various forms of online conversation (Chen et al., 2012; He & Tan, 2015; Vosecky, Leung, & Ng, 2014; Yan, Lapata, & Li, 2012), as well as via retweeting (Feng & Wang, 2013; Hong, Doumith, & Davison, 2013) and re-entry back into existing conversations (Backstrom, Kleinberg, Lee, & Danescu-Niculescu-Mizil, 2013). Our work here is closest to the latter: We are more interested in the extended dynamics of conversation, particularly the decision to re-engage or exit, than in the initial decision to interact. We focus on users who have already made that initial participation, and seek to understand and predict whether and when they re-engage based on user, tweet, and thread-level features.
While ongoing deliberative conversation is the substantive focus here, this framing also turns an impossible problem—predicting initial responses to a tweet out of the entire pool of twitter users—into a practicable prediction task—predicting re-participation of users whom we know are already part of a conversation. This approach also conditions out the even harder problem of explaining the origins of an initial tweet or conversation, particularly given the immense variety of motivations behind those first moves. Instead, we focus on existing conversations—at least a first move followed by a response—and model the processes that lead to extended and branching conversations among existing participants. Twitter might seem less suited to such models than traditional online forums, but Twitter in fact produces immense quantities of impromptu extended, branching conversations, and by focusing only on re-entry by existing participants, we can study what causes individuals to continue an argument or drop out, bracketing the question of initial engagement.
By conditioning on existing user interaction, we aim to get more deeply at the question of why people bother arguing online. What brings them back to a repeated argument? What factors contribute to an individual returning to or abandoning an argument? While in face-to-face settings, social etiquette suggests that a comment will most likely be greeted with a response, there is no a priori reason to expect a response to the vast majority of online posts. While we expect to find many types of conversations occurring online, we might expect that more extreme content (positive or negative) will increase engagement, as trolls successfully incite arguments and partisan allies reinforce each other’s positions (Cheng, Danescu-Niculescu-Mizil, Leskovec, & Bernstein, 2017). Between the extremes lies a more productive and interesting mode of engagement: true deliberative argument, in which participants exchange content in a genuine attempt to persuade or inform. Such behavior is not as uncommon as skeptics might assume, and is prevalent in knowledge-sharing platforms such as StackOverflow, Yahoo! Answers, and other such forums, where users may be motivated to some degree out of a general sense of community (Adamic, Zhang, Bakshy, & Ackerman, 2008; Anderson, Huttenlocher, Kleinberg, & Leskovec, 2012; Oktay, Taylor, & Jensen, 2010) even as they argue over better or worse solutions to shared problems.
We find evidence for all of these behaviors in our data and, in particular, show that while many of these engagements are negative, conversations often cover a range of emotions and go on far longer than a single-shot attack or mutual trolling might suggest. While we leave for later the ultimate question of persuasive effect, we establish here that even a medium as apparently unpromising as Twitter is full of complex, extended political conversations, and that individuals’ decision to repeatedly re-engage in those conversations is surprisingly systematic.
Related Work
Experience tells us, however, that such a lofty deliberative ideal is rarely met in political conversation. Sunstein (2002) advances the “law of group polarization,” finding through numerous empirical studies that “deliberation tends to move groups, and the individuals who compose them, toward a more extreme point in the direction indicated by their own pre-deliberation judgments” (p. 175). Sunstein argues this polarization is the natural result of the social context, which serves as a significant driver of individual actions and opinions. Hearing friends express a view makes a person socially inclined to express the same view. In other words, deliberating groups tend toward extremism in the direction of the predeliberation median because nobody wants to take the social risk of expressing an unpopular view. Sanders (1997) similarly argues that the broader context of power dynamics frequently has a debilitating but under-recognized effect on deliberation, as marginalized individuals feel silenced and unable to share their true opinions. Importantly, the majority of participants may mistakenly assume that such power effects are negligible if “deliberation appears to be proceeding.”
Another line of work has tackled conversational dynamics from the perspective of the data-processing problem of platform curation, for example, trying to predict which posts will be popular for the purpose of highlighting those posts for users. Much of this work focuses on post-level engagement, predicting engagement as a function of topics (Hong et al., 2013) or social network structures (He & Tan, 2015; Pan, Cong, Chen, & Yu, 2013). Much of this work has considered “popularity” as a raw aggregate of engagement with an initial post, finding, perhaps unsurprisingly, that the popularity of a user’s past content is a strong predictor for the popularity of their future content (Artzi, Pantel, & Gamon, 2012). Backstrom et al. (2013) break the task into related subtasks: length prediction and re-entry prediction. Intuitively, these subtasks indicate distinctive types of threads: threads which are long because a high number of users chime in a small number of times—to offer congratulations or condolence, for example—while other threads are long because a small number of users contribute a large number of times in a back-and-forth conversation. Supporting this theory, Backstrom et al. (2013) find that the number of distinct users in long threads follows a bimodal distribution. Using data from Facebook and Wikipedia, Backstrom et al. (2013) find the identities of recent commenters is most predictive of conversation re-entry.
This lattermost line of work is largely atheoretical and not particularly concerned with normative issues. While the current study borrows many of their methods, we are also fundamentally interested in the dynamics of online conversation from a deliberative perspective. Thus, we are interested less in conversation recommendation or modeling engagement in conversations per se, and more focused on how individual speech acts (tweets) lead existing discussants to re-engage with each other or abandon a conversation. Regardless of the outcome of a conversation, it is important to understand what sustains conversations—particularly acrimonious ones—and keeps mutual opponents or supporters engaged with each other. As we will see, this engagement can take more or less productive forms, but simply understanding the deliberative dynamics is an important first step.
Wednesday, March 27, 2019
A genetic mutation 60k to 130k years ago increased the capacity of general working memory or phonological storage, final piece in the evolution of human executive reasoning ability, language, & culture
Manoochehri, Majid. 2019. “The Evolution of Memory Span: A Review of the Existing Evidence.” PsyArXiv. March 27. doi:10.31234/osf.io/zdsya
Abstract: Memory span in humans has been intensely studied for more than a century. In spite of the critical role of memory span in our cognitive system, which intensifies the importance of fundamental determinants of its evolution, few studies have investigated it by taking an evolutionary approach. Overall, we know hardly anything about the evolution of memory components. In the current study, I reviewed the experimental studies of memory span in humans and non-human animals and the evolutionary hypotheses.
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Memory span refers to the ability of an individual to reproduce immediately, after one presentation, a series of discrete stimuli (e.g., digits, letters, and words) in their original order (Blankenship, 1938). Hermann Ebbinghaus (1850-1909) has been known as one of the first researchers of memory span. He studied the number of trials that it took him to memorize sequences of nonsense syllables (Ebbinghaus, 1885). He found that the number of trials needed increased with the length of the sequences. He then commented that: “The question can be asked: What number of syllables can be correctly recited after only one reading? For me the number is usually seven” (p. 36). In the years after that, several studies of memory span with verity of methods, tasks, and materials have been done by others (for review see Blankenship, 1938; Dempster, 1981). Surprisingly, some parts of results, such as the average memory span of adults were almost always the same. In 1956, Miller in his article discussed this issue. He stipulated that: “Everybody knows that there is a finite span of immediate memory and that for a lot of different kinds of test materials this span is about seven items in length” (p. 11). Today Miller’s suggestion has been known as the “magical number seven” of Miller, which refers to the memory span of young English adults. However, further findings from other nations were also in accordance with these results, suggesting that a memory span of about seven items is a universal characteristic of human beings. In addition to this feature, memory span scores have been discussed to be invariable and resistant to Flynn effects (Gignac, 2015; Wechsler, 1939). Moreover, memory span scores do not show considerable sex differences (Lynn & Irwing, 2008).The question that arises here is which selection pressures or evolutionary events caused the current memory span of humans and its particular characteristics.
The memory span of non-human animals
Firstly, it should be considered that because of the particular difficulties of studying cognitive functions in non-human animals, designed tasks in most of the available studies are somehow easier than classical memory span tests in humans. They usually include recognition of items instead of imitating the sequences, or several hours practice before the main test.
Chimps and other primates
Few studies have investigated memory span in non-human animals. Chimpanzees have been known as one of our nearest primate relatives and also one of the smartest non-human animals. Therefore, it may be expected to find the largest memory span of non-humans in them. The existing evidence shows that chimpanzees have a memory span of about 5 items (Inoue & Matsuzawa, 2007; Kawai & Matsuzawa, 2000). The results of other primates are very close to that of chimpanzees. Studies in baboons reveal a memory span of about 4 to 5 items (Fagot & De Lillo, 2011). On the other hand, the results of studying two rhesus monkeys by Swartz et al. (1991) suggest a memory span of about 4 objects.
Non-primates
Studies of non-primates do not exhibit better performances. Herman et al. (2013) have suggested a memory span of about 4 to 5 items for bottlenose dolphins. Lately, Toyoshima et al. (2018) have stipulated that rats are able to remember 5 objects at once. By contrast, a previous similar work by Sugita et al. (2015) has argued that rats’ memory span is approximately 4 items. A memory span of 4 items has also been suggested for pigeons. Terrace (1993) has discussed that the amount of time it takes a pigeon to learn a 4-item list (i.e., 3-4 months) suggests that 4 items may approach the limit of the pigeon's memory span.
Taking all these data together, one may conclude that there is an increasing trend of memory spans with a gentle slope from other animals to us. Moreover, it also seems reasonable to argue that while the memory span of most of the mentioned animals is about 4 to 5 items, humans’ memory span is about 7 items, which implies a sudden increase. This can be interpreted in favor of Coolidge and Wynn's (2005) hypothesis. They proposed that a mutation increased the length of memory span in the relatively recent human past. No need to emphasize that the idea of an increase with a gentle slope or a sudden increase is based on only a few experiments of memory span in some non-human animals. Surely, more studies are needed to provide the exact pattern. Experimental studies are also essential to measure the memory span of the current hunter-gatherers societies, such as Hadza of Tanzania. There are several reasons for the importance of their memory span results. Namely, because they are still foragers and their lifestyle is very close to that of our hunter-gatherer ancestors. Accordingly, their memory span might be similar, too. In addition, they are not literate or numerate and do not live in information-based societies. Therefore, they are not affected as broadly as other societies by some elements such as advanced educational programs. Moreover, another question is whether they apply memory’s strategies similar to people from other societies or not.
Evolutionary discussions and hypotheses
Until today, few studies have discussed memory span from an evolutionary perspective. There are also scant studies that discussed the evolution of working memory (e.g., Carruthers, 2013). It should be noticed that there are considerable differences between the functions of memory span and working memory. Therefore, there might be different selection pressures on them. In the present study the primary focus is on memory span.
Given the question of why memory span of humans has such a limited capacity, MacGregor (1987) based on a mathematical discussion emphasized the importance of an efficient retrieval. He suggested that: “… in a memory system evolved for efficient retrieval, there is an upper effective limit to short-term memory” (p. 107). From his point of view, there is an upper effective limit for the number of items in memory span, and this limitation guarantees an efficient retrieval.
The evolution of memory span has been also discussed by Coolidge and Wynn (2005). Although they mainly focused on working memory, the phonological lop which refers to memory span (or verbal memory span), has also been argued in their study. The core suggestion of their article is that a genetic mutation affected neural networks approximately 60,000 to 130,000 years ago and increased the capacity of general working memory or phonological storage. In case of memory span, they stipulated that:” A relatively simple mutation that increased the length of phonological storage would ultimately affect general working-memory capacity and language” (p. 14). They emphasized that an enhancement of capacities occurred in the relatively recent human past, most likely after the first appearance of anatomically modern humans, and this development was the final piece in the evolution of human executive reasoning ability, language, and culture. From their point of view, the larger capacity is a necessary precondition for symbolic thought, which selective pressures contributed to the growth of it. They noted that an increase in memory span of pre-modern Homo sapiens would have allowed greater articulatory rehearsal, consequently allowing for automatic long-term storage, and the beginnings of introspection, self-reflection, and consciousness. They, provided some evidence to support the assumption of a genetic mutation, such as the beginnings of composite tool-making about 300,000 years ago, or an explosion of culture which began approximately 50,000 years ago.
In another part of their article, Coolidge and Wynn (2005) have quoted from Alan Baddeley that: “the phonological store evolved principally for the demands and acquisition of language” (p. 9). In addition, they have proposed that, evolutionary, the visuospatial sketchpad which is a part of working memory and maintains visual and spatial information may be older than the phonological loop. It should be noticed that the visuospatial sketchpad refers to visual memory span.
Conclusions
In the first place, the present article draws attention to the gap of evolutionary studies of memory span. It also suggests an increasing trend of memory span from our ancestors to us, whether the trend includes a steady increase with a gentle slope or a sudden increase. In terms of evolutionary discussions, the few available studies which have argued the evolution of memory span concentrated on some particular issues such as the reasons of a limited-capacity construct, or the results of increasing the length on cognitive functions. Other aspects remain untouched.
Abstract: Memory span in humans has been intensely studied for more than a century. In spite of the critical role of memory span in our cognitive system, which intensifies the importance of fundamental determinants of its evolution, few studies have investigated it by taking an evolutionary approach. Overall, we know hardly anything about the evolution of memory components. In the current study, I reviewed the experimental studies of memory span in humans and non-human animals and the evolutionary hypotheses.
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Memory span refers to the ability of an individual to reproduce immediately, after one presentation, a series of discrete stimuli (e.g., digits, letters, and words) in their original order (Blankenship, 1938). Hermann Ebbinghaus (1850-1909) has been known as one of the first researchers of memory span. He studied the number of trials that it took him to memorize sequences of nonsense syllables (Ebbinghaus, 1885). He found that the number of trials needed increased with the length of the sequences. He then commented that: “The question can be asked: What number of syllables can be correctly recited after only one reading? For me the number is usually seven” (p. 36). In the years after that, several studies of memory span with verity of methods, tasks, and materials have been done by others (for review see Blankenship, 1938; Dempster, 1981). Surprisingly, some parts of results, such as the average memory span of adults were almost always the same. In 1956, Miller in his article discussed this issue. He stipulated that: “Everybody knows that there is a finite span of immediate memory and that for a lot of different kinds of test materials this span is about seven items in length” (p. 11). Today Miller’s suggestion has been known as the “magical number seven” of Miller, which refers to the memory span of young English adults. However, further findings from other nations were also in accordance with these results, suggesting that a memory span of about seven items is a universal characteristic of human beings. In addition to this feature, memory span scores have been discussed to be invariable and resistant to Flynn effects (Gignac, 2015; Wechsler, 1939). Moreover, memory span scores do not show considerable sex differences (Lynn & Irwing, 2008).The question that arises here is which selection pressures or evolutionary events caused the current memory span of humans and its particular characteristics.
The memory span of non-human animals
Firstly, it should be considered that because of the particular difficulties of studying cognitive functions in non-human animals, designed tasks in most of the available studies are somehow easier than classical memory span tests in humans. They usually include recognition of items instead of imitating the sequences, or several hours practice before the main test.
Chimps and other primates
Few studies have investigated memory span in non-human animals. Chimpanzees have been known as one of our nearest primate relatives and also one of the smartest non-human animals. Therefore, it may be expected to find the largest memory span of non-humans in them. The existing evidence shows that chimpanzees have a memory span of about 5 items (Inoue & Matsuzawa, 2007; Kawai & Matsuzawa, 2000). The results of other primates are very close to that of chimpanzees. Studies in baboons reveal a memory span of about 4 to 5 items (Fagot & De Lillo, 2011). On the other hand, the results of studying two rhesus monkeys by Swartz et al. (1991) suggest a memory span of about 4 objects.
Non-primates
Studies of non-primates do not exhibit better performances. Herman et al. (2013) have suggested a memory span of about 4 to 5 items for bottlenose dolphins. Lately, Toyoshima et al. (2018) have stipulated that rats are able to remember 5 objects at once. By contrast, a previous similar work by Sugita et al. (2015) has argued that rats’ memory span is approximately 4 items. A memory span of 4 items has also been suggested for pigeons. Terrace (1993) has discussed that the amount of time it takes a pigeon to learn a 4-item list (i.e., 3-4 months) suggests that 4 items may approach the limit of the pigeon's memory span.
Taking all these data together, one may conclude that there is an increasing trend of memory spans with a gentle slope from other animals to us. Moreover, it also seems reasonable to argue that while the memory span of most of the mentioned animals is about 4 to 5 items, humans’ memory span is about 7 items, which implies a sudden increase. This can be interpreted in favor of Coolidge and Wynn's (2005) hypothesis. They proposed that a mutation increased the length of memory span in the relatively recent human past. No need to emphasize that the idea of an increase with a gentle slope or a sudden increase is based on only a few experiments of memory span in some non-human animals. Surely, more studies are needed to provide the exact pattern. Experimental studies are also essential to measure the memory span of the current hunter-gatherers societies, such as Hadza of Tanzania. There are several reasons for the importance of their memory span results. Namely, because they are still foragers and their lifestyle is very close to that of our hunter-gatherer ancestors. Accordingly, their memory span might be similar, too. In addition, they are not literate or numerate and do not live in information-based societies. Therefore, they are not affected as broadly as other societies by some elements such as advanced educational programs. Moreover, another question is whether they apply memory’s strategies similar to people from other societies or not.
Evolutionary discussions and hypotheses
Until today, few studies have discussed memory span from an evolutionary perspective. There are also scant studies that discussed the evolution of working memory (e.g., Carruthers, 2013). It should be noticed that there are considerable differences between the functions of memory span and working memory. Therefore, there might be different selection pressures on them. In the present study the primary focus is on memory span.
Given the question of why memory span of humans has such a limited capacity, MacGregor (1987) based on a mathematical discussion emphasized the importance of an efficient retrieval. He suggested that: “… in a memory system evolved for efficient retrieval, there is an upper effective limit to short-term memory” (p. 107). From his point of view, there is an upper effective limit for the number of items in memory span, and this limitation guarantees an efficient retrieval.
The evolution of memory span has been also discussed by Coolidge and Wynn (2005). Although they mainly focused on working memory, the phonological lop which refers to memory span (or verbal memory span), has also been argued in their study. The core suggestion of their article is that a genetic mutation affected neural networks approximately 60,000 to 130,000 years ago and increased the capacity of general working memory or phonological storage. In case of memory span, they stipulated that:” A relatively simple mutation that increased the length of phonological storage would ultimately affect general working-memory capacity and language” (p. 14). They emphasized that an enhancement of capacities occurred in the relatively recent human past, most likely after the first appearance of anatomically modern humans, and this development was the final piece in the evolution of human executive reasoning ability, language, and culture. From their point of view, the larger capacity is a necessary precondition for symbolic thought, which selective pressures contributed to the growth of it. They noted that an increase in memory span of pre-modern Homo sapiens would have allowed greater articulatory rehearsal, consequently allowing for automatic long-term storage, and the beginnings of introspection, self-reflection, and consciousness. They, provided some evidence to support the assumption of a genetic mutation, such as the beginnings of composite tool-making about 300,000 years ago, or an explosion of culture which began approximately 50,000 years ago.
In another part of their article, Coolidge and Wynn (2005) have quoted from Alan Baddeley that: “the phonological store evolved principally for the demands and acquisition of language” (p. 9). In addition, they have proposed that, evolutionary, the visuospatial sketchpad which is a part of working memory and maintains visual and spatial information may be older than the phonological loop. It should be noticed that the visuospatial sketchpad refers to visual memory span.
Conclusions
In the first place, the present article draws attention to the gap of evolutionary studies of memory span. It also suggests an increasing trend of memory span from our ancestors to us, whether the trend includes a steady increase with a gentle slope or a sudden increase. In terms of evolutionary discussions, the few available studies which have argued the evolution of memory span concentrated on some particular issues such as the reasons of a limited-capacity construct, or the results of increasing the length on cognitive functions. Other aspects remain untouched.
Latent genetic traits account for, on average, 40.63% of variance in traditional and online political talk, discussion with agreement and disagreement, and political conflict avoidance: Results from two twin studies
Genetic influence on political discussion: Results from two twin studies. Chance York. Communication Monographs, Mar 26 2019. https://doi.org/10.1080/03637751.2019.1597274
ABSTRACT: Two twin studies are used to explore genetic influence on political discussion. Results from both studies demonstrate latent genetic traits account for, on average, 40.63% of variance in traditional and online political talk, discussion with agreement and disagreement, and political conflict avoidance. Taken together, the findings suggest a heritable genetic mechanism may partly explain why individuals vary across multiple dimensions of political discussion and differentially experience discussion effects. Implications for the political discussion effects literature and for reconceptualizing the etiology of political discussion are discussed.
KEYWORDS: Political discussion, individual differences, behavior genetics, twin study, genes
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Political discussion is an important and beneficial form of communication in representa-tive democracies. Citizens who frequently discuss politics become more knowledgeableabout current events and public affairs, engaged civically and politically, and confidentin their own ability to affect their national government and its institutions (Eveland &Hively,2009; Kenski & Stroud,2006; Shah et al.,2017). Yet, citizens differ widely in behav-ioral dimensions of political discussion and thus any potential benefits they may derivefrom talking about politics. For instance, some citizens routinely discuss politics whileothers only talk about politics during salient election periods (Hardy & Scheufele,2009)if they engage in political discussion at all. Some citizens prefer face-to-face talk whileothers prefer online conversation and some citizens seek political argument whileothers seek agreement.
What accounts for these individual differences in political discussion? In the past, indi-vidual differences in political discussion have been thought to emerge from, and be con-strained by, personality characteristics (Gerber, Huber, Doherty, & Dowling,2012;Hibbing, Ritchie, & Anderson,2011), parent and peer socialization (Hively & Eveland,2009; Klofstad,2009, 2010, 2015), and a wide array of psychological motivations as out-lined in the Uses and Gratifications (U&G) theory of communication behavior(Eveland, Morey, & Hutchens,2011; Gil de Zúñiga, Valenzuela, & Weeks,2016;Kearney,2017). However, it is also plausible that far more fundamental traits–genes–precede and delimit these more immediate influences on discussion. Because genes arecentral to neuroanatomical development and neurochemical responses to external stimuli (Hatemi, Byrne, & McDermott,2012; Knopik, Neiderhiser, DeFries, & Plomin,2016; Lockyer & Hatemi,2018), they may indirectly promote pathways to explicit behav-ioral patterns, including patterns of interpersonal political communication. In addition,genes have been shown to regulate personality characteristics amenable to political talk,such as extraversion (Bouchard & Loehlin,2001). This is perhaps why genetic traitshave already been shown to partially explain orientations to interpersonal discussion gen-erally (Kirzinger, Weber, & Johnson,2012) and frequency of political discussion specifi-cally (Funk et al.,2010), though it remains unclear whether genetic traits also influenceother critical dimensions of political talk, including online political talk and discussionwith disagreement.
The purpose of this article is to therefore explore genetic influence on previously unex-amined aspects of political discussion. In this article, a behavior genetics perspective andtwin study survey data were used to ascertain the amount of variance in several dimen-sions of political discussion that can be attributed to latent genetic traits and the socialenvironment. Building on previous research (Funk et al.,2010; Kirzinger et al.,2012),the results show that variation in multiple dimensions of political discussion is partlyexplained by genetics. Importantly, the results suggest genes may be an overlookedfactor motivating behavioral differences in political discussion and its effects. Moreover,the results imply a need to reconceptualize the etiology of political discussion as beingshaped by both social-environmental and biological forces.
Literature review
Talking about politics is associated with a number of desirable effects. For example, pol-itical discussion is related to enhanced knowledge about political candidates and issues(Eveland,2004; Eveland & Hively,2009), more frequent engagement in civic and electoralprocesses (Bakker & De Vreese,2011; Klofstad,2009, 2010, 2015) heightened confidenceone can make a difference politically (Kenski & Stroud,2006), and increased tolerance forindividuals with differing political opinions (Mutz,2002a). Political talk also acts as a keymediator of news media influence, altering selection and processing of news content(Anspach,2017) and augmenting positive effects of news exposure on civic and politicalparticipation by enabling citizens to make sense of mediated information (Cho et al.,2009;Shah et al.,2007, 2017; Shah, Cho, Eveland, & Kwak,2005). Although“cross-cutting”dis-cussion with un-likeminded partisans has been linked to reduced levels of participationwithin politically diverse social networks (Mutz,2002b, 2006), a considerable body of evi-dence has shown political discussion to be cognitively and behaviorally advantageous.
Individuals vary, however, in how they discuss politics and how frequently, and thusany informational and participatory benefits they may reap from discussion. Forexample, while some citizens are consistent political discussants regardless of external cir-cumstances, others might be characterized as“seasonal discussants”who are“uniformedand unengaged and usually do not participate in political discussions”unless they are“triggered by highly salient campaign coverage” (Hardy & Scheufele,2009, pp. 95–97).Still other citizens may avoid political talk altogether despite exposure to externalevents, such as national elections, and despite possessing a general interest in politics.Some citizens may prefer interactions that take place online while others seek out face-to-face conversation. Some may enjoy political discussion with disagreement whileothers abandon conflict in pursuit offinding common ground on the issues.
As with other forms of communication, several factors can motivate individual differences in political discussion. To date, in fact, the literature provides at least three sourcesof variation. First, political talk may arise from and be bounded by deeply ingrained personality characteristics such as extraversion. Extraversion, which can be defined as an“energetic approach to the social and material world”(Gerber, Huber, Doherty, &Dowling,2011, p. 267), has been linked to more frequent political discussion with friends, family, and distant social ties (Hibbing et al.,2011) as well as more frequent dis-cussions that involve disagreement (Gerber et al.,2012). Personality traits such as agree-ableness, conscientiousness, openness to experience, and emotional stability have alsobeen associated with political discussion frequency and discussion with disagreement(Gerber et al.,2012; Hibbing et al.,2011). From this perspective,“psychological predis-positions captured by individual personality traits play an important role in shaping thekinds of conversations citizens engage in, the setting for those conversations, and theinfluence discussion may or may not have on the individual”(Hibbing et al.,2011,p. 602).
Second, individual differences in political discussion may result from socialization viapolitical interactions with parents and peers that take place during childhood, adolescence,and young adulthood. Youth who belong to“concept-oriented”families that encouragekids to share their ideas, for instance, tend to engage in more frequent, more informedand“elaborative”talk with their families (Hively & Eveland,2009) that may, in turn,shape how they discuss politics in the future. Similarly, discussing politics with collegeroommates has been linked to increased short-term civic and political participation (Klof-stad,2009) and long-term discussion habits (Klofstad,2010; 2015). An individual’s earlyexposure to political talk, especially discussions with parents and peers, may thus play amajor role in discussion patterns over the life course.A third source of variation in political discussion comes from the U&G theory of com-munication behavior. Specifically, U&G suggests that individuals are active communica-tors who engage in interpersonal discussion in a manner that is“goal-directed,purposive, and motivated”by deliberate choices to satisfy immediate psychologicalneeds to communicate affection, promote feelings of social inclusion, escape from one’sday-to-day routines, and relax with close social ties (Rubin,2009a, p. 167; see Barbato,Graham, & Perse,1997, 2003; Graham, Barbato, & Perse,1993; Rubin,2009b; Rubin,Perse, & Barbato,1988).
Politically oriented discussions may likewise satisfy needs to per-suade politically, express political opinions, enhance issue learning (Eveland et al.,2011;Gil de Zúñiga et al.,2016; Yoo, Kim, & Gil de Zúñiga,2017), as well as maintain one’spolitical identity and feel emotionally engaged via political interaction (Kearney,2017;Valenzuela & Bachmann,2015). Accordingly, the U&G theoretical framework suggeststhat individual differences in political discussion occur because people perceive discussionto satisfy differing informational and social needs.
As Sherry (2001) has noted, however, it is likely that individual differences in U&G needs and the communication behaviors they inspire originate in biological factors. Forinstance, while it has been suggested that U&G needs for communication are governed by psychological“ predispositions [and] the environment”(Rubin,2009a, p. 167), such“predispositions”like those rooted in personality traits are known to have an even more fundamental genetic basis (e.g., Bouchard & Loehlin,2001; Plomin, DeFries, Knopik,& Neiderhiser,2016). Additionally, it is established that because genes form the basis of human neuroanatomical development and control neurochemical responses to external stimuli, they ultimately provide pathways to explicit cognitive and behavioral patterns(Hatemi et al.,2012; Lockyer & Hatemi, 2018), including neural pathways that, alongwith social contexts, prompt and structure communication behavior (Beatty, McCroskey, & Pence,2009; Weber, Sherry, & Mathiak, 2009). It is therefore possible, as decades of twin research in the behavior genetics paradigm has shown, “that many physical, psychological,and behavioral traits, however indirectly, are the ultimate result of a combination ofgenetic inheritance and the environment” (Medland & Hatemi,2009, p. 192).
A behavior genetics approach to communication behavior
Behavior genetics researchers rely on known degrees of biological relatedness among survey respondents–typically, identical and fraternal twins–to estimate the impactof genes on observable outcomes. These outcomes have included highly specializedpsychological orientations and behaviors, such as political ideology, political party affilia-tion, and voter turnout (Hatemi et al.,2014; Hatemi & McDermott,2012; Hatemi,Medland, Morley, Heath, & Martin,2007); social and economic attitudes (Hatemi,Smith, Alford, Martin, & Hibbing,2015); educational attainment (Cesarini & Visscher,2017); conservativism, authoritarianism, and religiousness (Ludeke, Johnson, & Bouchard,2013); fear of social and political out-groups (Hatemi, McDermott, Eaves,Kendler, & Neale,2013), risk-taking behavior (Kreek, Nielsen, Butelman, & LaForge, 2005); and social cooperation and trust (Cesarini et al.,2008). Twin studies have also shown that genes play a powerful role in shaping dimensions of mental health (Strachan,Duncan, Horn, & Turkheimer,2017), personality (Bouchard & Loehlin, 2001; Plominet al.,2016), and a variety of physical attributes such as height, weight, heart function,and facial structure (Polderman et al.,2015).1
In communication research, twin studies have demonstrated that genes partially explain differences in broad traits and orientations such as communicator style (Horvath,1995) and communicative adaptability (Beatty, Marshall, & Rudd,2001).
Twin studies have also been used to explore genetic influences on media consumptionand interpersonal communication behaviors. For example, one twin study demonstratedthat individual variation in mobile phone use, frequency of talking on mobile phones, andfrequency of texting were all indirectly influenced by genetic traits (Miller, Zhu, Wright,Hansell, & Martin,2012). Similar studies have shown that latent genetic traits influence frequency of using social media sites like Facebook to communicate with friends and family (York,2017), problematic internet use or PIU (Deryakulu & Ursavaş, 2014), and television viewing (Plomin, Corley, DeFries, & Fulker,1990).2
Across twin studies of communication, genetic traits have been shown to account forlarge proportions of individual variance in outcomes. For example, Kirzinger et al.(2012) showed genetic traits explained between 9% and 29% of the variance in orientationsto interpersonal discussion measured using two Likert-type items that tapped engagement in discussion and self-reported enjoyment in talking with“a lot of different people atparties”(p. 164). Funk et al. (2010, pp. 31–32) showed that up to a third of variance intwo Likert-type items measuring frequency of political discussion and conflict avoidance was explained by genes. These latter twin studies, combined with research that has foundthat genes provide brain–behavior pathways (Hatemi et al.,2012; Lockyer & Hatemi,2018) that activate patterns of communication (Beatty et al.,2009; Weber et al.,2009),suggest that additional dimensions of political talk may be partly explained by genetic traits. Thus, one could expect genetic traits to explain a nontrivial amount of variance in multiple dimensions of political talk, including traditional political discussion, online political discussion, political discussion with agreement and disagreement, and political conflict avoidance.In addition to examining whether genetic traits explain differences in dimensions of political discussion, it is also instructive in twin research to address the relative explana-tory contribution of genetic traits and the social environment shared by both twins (e.g.,being raised by the same parents) to the behaviors under investigation. Based on previousresearch, especially that of Kirzinger et al. (2012) and Funk et al. (2010), it may be the casethat both genetic and environmental factors shared by twins in a pair account for individ-ual differences in dimensions of political discussion, though it is uncertain which of thesefactors would make a more substantial contribution. Therefore, a research question is alsoposed:What is the relative explanatory contribution of genetic and environmental factors tovariance in multiple dimensions of political talk, including traditional political discussion,online political discussion, political discussion with agreement and disagreement, and pol-itical conflict avoidance?
ABSTRACT: Two twin studies are used to explore genetic influence on political discussion. Results from both studies demonstrate latent genetic traits account for, on average, 40.63% of variance in traditional and online political talk, discussion with agreement and disagreement, and political conflict avoidance. Taken together, the findings suggest a heritable genetic mechanism may partly explain why individuals vary across multiple dimensions of political discussion and differentially experience discussion effects. Implications for the political discussion effects literature and for reconceptualizing the etiology of political discussion are discussed.
KEYWORDS: Political discussion, individual differences, behavior genetics, twin study, genes
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Political discussion is an important and beneficial form of communication in representa-tive democracies. Citizens who frequently discuss politics become more knowledgeableabout current events and public affairs, engaged civically and politically, and confidentin their own ability to affect their national government and its institutions (Eveland &Hively,2009; Kenski & Stroud,2006; Shah et al.,2017). Yet, citizens differ widely in behav-ioral dimensions of political discussion and thus any potential benefits they may derivefrom talking about politics. For instance, some citizens routinely discuss politics whileothers only talk about politics during salient election periods (Hardy & Scheufele,2009)if they engage in political discussion at all. Some citizens prefer face-to-face talk whileothers prefer online conversation and some citizens seek political argument whileothers seek agreement.
What accounts for these individual differences in political discussion? In the past, indi-vidual differences in political discussion have been thought to emerge from, and be con-strained by, personality characteristics (Gerber, Huber, Doherty, & Dowling,2012;Hibbing, Ritchie, & Anderson,2011), parent and peer socialization (Hively & Eveland,2009; Klofstad,2009, 2010, 2015), and a wide array of psychological motivations as out-lined in the Uses and Gratifications (U&G) theory of communication behavior(Eveland, Morey, & Hutchens,2011; Gil de Zúñiga, Valenzuela, & Weeks,2016;Kearney,2017). However, it is also plausible that far more fundamental traits–genes–precede and delimit these more immediate influences on discussion. Because genes arecentral to neuroanatomical development and neurochemical responses to external stimuli (Hatemi, Byrne, & McDermott,2012; Knopik, Neiderhiser, DeFries, & Plomin,2016; Lockyer & Hatemi,2018), they may indirectly promote pathways to explicit behav-ioral patterns, including patterns of interpersonal political communication. In addition,genes have been shown to regulate personality characteristics amenable to political talk,such as extraversion (Bouchard & Loehlin,2001). This is perhaps why genetic traitshave already been shown to partially explain orientations to interpersonal discussion gen-erally (Kirzinger, Weber, & Johnson,2012) and frequency of political discussion specifi-cally (Funk et al.,2010), though it remains unclear whether genetic traits also influenceother critical dimensions of political talk, including online political talk and discussionwith disagreement.
The purpose of this article is to therefore explore genetic influence on previously unex-amined aspects of political discussion. In this article, a behavior genetics perspective andtwin study survey data were used to ascertain the amount of variance in several dimen-sions of political discussion that can be attributed to latent genetic traits and the socialenvironment. Building on previous research (Funk et al.,2010; Kirzinger et al.,2012),the results show that variation in multiple dimensions of political discussion is partlyexplained by genetics. Importantly, the results suggest genes may be an overlookedfactor motivating behavioral differences in political discussion and its effects. Moreover,the results imply a need to reconceptualize the etiology of political discussion as beingshaped by both social-environmental and biological forces.
Literature review
Talking about politics is associated with a number of desirable effects. For example, pol-itical discussion is related to enhanced knowledge about political candidates and issues(Eveland,2004; Eveland & Hively,2009), more frequent engagement in civic and electoralprocesses (Bakker & De Vreese,2011; Klofstad,2009, 2010, 2015) heightened confidenceone can make a difference politically (Kenski & Stroud,2006), and increased tolerance forindividuals with differing political opinions (Mutz,2002a). Political talk also acts as a keymediator of news media influence, altering selection and processing of news content(Anspach,2017) and augmenting positive effects of news exposure on civic and politicalparticipation by enabling citizens to make sense of mediated information (Cho et al.,2009;Shah et al.,2007, 2017; Shah, Cho, Eveland, & Kwak,2005). Although“cross-cutting”dis-cussion with un-likeminded partisans has been linked to reduced levels of participationwithin politically diverse social networks (Mutz,2002b, 2006), a considerable body of evi-dence has shown political discussion to be cognitively and behaviorally advantageous.
Individuals vary, however, in how they discuss politics and how frequently, and thusany informational and participatory benefits they may reap from discussion. Forexample, while some citizens are consistent political discussants regardless of external cir-cumstances, others might be characterized as“seasonal discussants”who are“uniformedand unengaged and usually do not participate in political discussions”unless they are“triggered by highly salient campaign coverage” (Hardy & Scheufele,2009, pp. 95–97).Still other citizens may avoid political talk altogether despite exposure to externalevents, such as national elections, and despite possessing a general interest in politics.Some citizens may prefer interactions that take place online while others seek out face-to-face conversation. Some may enjoy political discussion with disagreement whileothers abandon conflict in pursuit offinding common ground on the issues.
As with other forms of communication, several factors can motivate individual differences in political discussion. To date, in fact, the literature provides at least three sourcesof variation. First, political talk may arise from and be bounded by deeply ingrained personality characteristics such as extraversion. Extraversion, which can be defined as an“energetic approach to the social and material world”(Gerber, Huber, Doherty, &Dowling,2011, p. 267), has been linked to more frequent political discussion with friends, family, and distant social ties (Hibbing et al.,2011) as well as more frequent dis-cussions that involve disagreement (Gerber et al.,2012). Personality traits such as agree-ableness, conscientiousness, openness to experience, and emotional stability have alsobeen associated with political discussion frequency and discussion with disagreement(Gerber et al.,2012; Hibbing et al.,2011). From this perspective,“psychological predis-positions captured by individual personality traits play an important role in shaping thekinds of conversations citizens engage in, the setting for those conversations, and theinfluence discussion may or may not have on the individual”(Hibbing et al.,2011,p. 602).
Second, individual differences in political discussion may result from socialization viapolitical interactions with parents and peers that take place during childhood, adolescence,and young adulthood. Youth who belong to“concept-oriented”families that encouragekids to share their ideas, for instance, tend to engage in more frequent, more informedand“elaborative”talk with their families (Hively & Eveland,2009) that may, in turn,shape how they discuss politics in the future. Similarly, discussing politics with collegeroommates has been linked to increased short-term civic and political participation (Klof-stad,2009) and long-term discussion habits (Klofstad,2010; 2015). An individual’s earlyexposure to political talk, especially discussions with parents and peers, may thus play amajor role in discussion patterns over the life course.A third source of variation in political discussion comes from the U&G theory of com-munication behavior. Specifically, U&G suggests that individuals are active communica-tors who engage in interpersonal discussion in a manner that is“goal-directed,purposive, and motivated”by deliberate choices to satisfy immediate psychologicalneeds to communicate affection, promote feelings of social inclusion, escape from one’sday-to-day routines, and relax with close social ties (Rubin,2009a, p. 167; see Barbato,Graham, & Perse,1997, 2003; Graham, Barbato, & Perse,1993; Rubin,2009b; Rubin,Perse, & Barbato,1988).
Politically oriented discussions may likewise satisfy needs to per-suade politically, express political opinions, enhance issue learning (Eveland et al.,2011;Gil de Zúñiga et al.,2016; Yoo, Kim, & Gil de Zúñiga,2017), as well as maintain one’spolitical identity and feel emotionally engaged via political interaction (Kearney,2017;Valenzuela & Bachmann,2015). Accordingly, the U&G theoretical framework suggeststhat individual differences in political discussion occur because people perceive discussionto satisfy differing informational and social needs.
As Sherry (2001) has noted, however, it is likely that individual differences in U&G needs and the communication behaviors they inspire originate in biological factors. Forinstance, while it has been suggested that U&G needs for communication are governed by psychological“ predispositions [and] the environment”(Rubin,2009a, p. 167), such“predispositions”like those rooted in personality traits are known to have an even more fundamental genetic basis (e.g., Bouchard & Loehlin,2001; Plomin, DeFries, Knopik,& Neiderhiser,2016). Additionally, it is established that because genes form the basis of human neuroanatomical development and control neurochemical responses to external stimuli, they ultimately provide pathways to explicit cognitive and behavioral patterns(Hatemi et al.,2012; Lockyer & Hatemi, 2018), including neural pathways that, alongwith social contexts, prompt and structure communication behavior (Beatty, McCroskey, & Pence,2009; Weber, Sherry, & Mathiak, 2009). It is therefore possible, as decades of twin research in the behavior genetics paradigm has shown, “that many physical, psychological,and behavioral traits, however indirectly, are the ultimate result of a combination ofgenetic inheritance and the environment” (Medland & Hatemi,2009, p. 192).
A behavior genetics approach to communication behavior
Behavior genetics researchers rely on known degrees of biological relatedness among survey respondents–typically, identical and fraternal twins–to estimate the impactof genes on observable outcomes. These outcomes have included highly specializedpsychological orientations and behaviors, such as political ideology, political party affilia-tion, and voter turnout (Hatemi et al.,2014; Hatemi & McDermott,2012; Hatemi,Medland, Morley, Heath, & Martin,2007); social and economic attitudes (Hatemi,Smith, Alford, Martin, & Hibbing,2015); educational attainment (Cesarini & Visscher,2017); conservativism, authoritarianism, and religiousness (Ludeke, Johnson, & Bouchard,2013); fear of social and political out-groups (Hatemi, McDermott, Eaves,Kendler, & Neale,2013), risk-taking behavior (Kreek, Nielsen, Butelman, & LaForge, 2005); and social cooperation and trust (Cesarini et al.,2008). Twin studies have also shown that genes play a powerful role in shaping dimensions of mental health (Strachan,Duncan, Horn, & Turkheimer,2017), personality (Bouchard & Loehlin, 2001; Plominet al.,2016), and a variety of physical attributes such as height, weight, heart function,and facial structure (Polderman et al.,2015).1
In communication research, twin studies have demonstrated that genes partially explain differences in broad traits and orientations such as communicator style (Horvath,1995) and communicative adaptability (Beatty, Marshall, & Rudd,2001).
Twin studies have also been used to explore genetic influences on media consumptionand interpersonal communication behaviors. For example, one twin study demonstratedthat individual variation in mobile phone use, frequency of talking on mobile phones, andfrequency of texting were all indirectly influenced by genetic traits (Miller, Zhu, Wright,Hansell, & Martin,2012). Similar studies have shown that latent genetic traits influence frequency of using social media sites like Facebook to communicate with friends and family (York,2017), problematic internet use or PIU (Deryakulu & Ursavaş, 2014), and television viewing (Plomin, Corley, DeFries, & Fulker,1990).2
Across twin studies of communication, genetic traits have been shown to account forlarge proportions of individual variance in outcomes. For example, Kirzinger et al.(2012) showed genetic traits explained between 9% and 29% of the variance in orientationsto interpersonal discussion measured using two Likert-type items that tapped engagement in discussion and self-reported enjoyment in talking with“a lot of different people atparties”(p. 164). Funk et al. (2010, pp. 31–32) showed that up to a third of variance intwo Likert-type items measuring frequency of political discussion and conflict avoidance was explained by genes. These latter twin studies, combined with research that has foundthat genes provide brain–behavior pathways (Hatemi et al.,2012; Lockyer & Hatemi,2018) that activate patterns of communication (Beatty et al.,2009; Weber et al.,2009),suggest that additional dimensions of political talk may be partly explained by genetic traits. Thus, one could expect genetic traits to explain a nontrivial amount of variance in multiple dimensions of political talk, including traditional political discussion, online political discussion, political discussion with agreement and disagreement, and political conflict avoidance.In addition to examining whether genetic traits explain differences in dimensions of political discussion, it is also instructive in twin research to address the relative explana-tory contribution of genetic traits and the social environment shared by both twins (e.g.,being raised by the same parents) to the behaviors under investigation. Based on previousresearch, especially that of Kirzinger et al. (2012) and Funk et al. (2010), it may be the casethat both genetic and environmental factors shared by twins in a pair account for individ-ual differences in dimensions of political discussion, though it is uncertain which of thesefactors would make a more substantial contribution. Therefore, a research question is alsoposed:What is the relative explanatory contribution of genetic and environmental factors tovariance in multiple dimensions of political talk, including traditional political discussion,online political discussion, political discussion with agreement and disagreement, and pol-itical conflict avoidance?
Political journalists overwhelmingly interact with other journalists, particularly political ones, & their offline tendencies to form homogenous networks have transferred online
Exploring Political Journalism Homophily on Twitter: A Comparative Analysis of US and UK Elections in 2016 and 2017. Kelly Fincham. Media and Communication, Vol 7, No 1 (2019). March 21 2019. http://dx.doi.org/10.17645/mac.v7i1.1765
Abstract: The tendency of political journalists to form insular groups or packs, chasing the same angles and quoting the same sources, is a well-documented issue in journalism studies and has long been criticized for its role in groupthink and homogenous news coverage. This groupthink attracted renewed criticism after the unexpected victory of Republican candidate Donald Trump in the 2016 US presidential election as the campaign coverage had indicated a likely win by the Democratic candidate Hillary Clinton. This pattern was repeated in the 2017 UK election when the Conservative party lost their majority after a campaign in which the news coverage had pointed to an overall Tory victory. Such groupthink is often attributed to homophily, the tendency of individuals to interact with those most like them, and while homophily in the legacy media system is well-studied, there is little research around homophily in the hybrid media system, even as social media platforms like Twitter facilitate the development—and analysis—of virtual political journalism packs. This study, which compares Twitter interactions among US and UK political reporters in the 2016 and 2017 national elections, shows that political journalists are overwhelmingly more likely to use Twitter to interact with other journalists, particularly political journalists, and that their offline tendencies to form homogenous networks have transferred online. There are some exceptions around factors such as gender, news organizations and types of news organization—and important distinctions between types of interactions—but overall the study provides evidence of sustained homophily as journalists continue to normalize Twitter.
Keywords: elections; groupthink; homophily; political journalism; Twitter, UK; US
Check also Journalistic Homophily on Social Media: Exploring journalists’ interactions with each other on Twitter. Folker Hanusch & Daniel Nölleke. Digital Journalism, https://www.bipartisanalliance.com/2018/02/journalists-continue-to-live-in-bubbles.html
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The worst about this is not their constant sanctimoniousness when talking to the peasants, when they are bigger offenders and keep their membership in their echo chambers and sub-echo chambers in greater proportion that the great unwashed... It is that in journalism schools they are already told to be aware of their biases, and the very human need to be part of a pack (or herd?) and they forget it immediately after taking the exams.
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2. Literature Review
FromthetelegraphtotypewriterstotelevisiontoTwitter, successive technological innovations have transformed the norms and practice of journalism (Lasorsa, Lewis, & Holton, 2012) and each new technology has arrived amid much fanfare about its potential impact on political communication, particularly around election campaigns (Stromer-Galley, 2014). Ultimately however, the expectations and concerns about these potential utopias and dystopias have never been fully realized as the power structures of journalism and politics have instead normalized each new “new media” into their own practice (Singer, 2005). The potential power of digital media in election campaigns was first seen in the US in the 2004 Presidential campaign when it rocketed the relatively unknown candidate Howard Dean into the political and media stratosphere (Stromer-Galley, 2014) but as Margolis and Resnick had already argued in 2000, any of the digital advantages accruing to early adopters like Dean were soon eclipsed as the political and journalism elite folded these new technologies into existing practices when they recognized,a nd there by normalized, the “new” new media (Margolis & Resnick, 2000). Much of the research into Twitter journalism practice argues that journalists, seen as frequent, if not always skillful, Twitter users (Engesser & Humprecht, 2015) are well down the path of normalization, using Twitter in ways that conform to existing practice rather than using it to change journalism practice (see Lasorsa et al., 2012; Lawrence, Molyneux, Coddington, & Holton,2014; Lewis,2012; Molyneux & Mourão,2019; Nuernbergk,2016;Parmelee,2013). This is especially evidentinare as such as gatekeeping,wherejournalistshave long controlled whose voices make it through the editorial “gates” (Lasorsa et al., 2012; Singer, 2005), and Twitter gatekeeping can be seen in the “insider talk” and “regurgitation” of information flowing across Twitter (Lawrence et al., 2014; Parmelee, Roman, Beasley, & Perkins, 2019, p. 161) as journalists more frequently engage with other journalists or newsmakers—and even themselves—rather than interest groups, academics or citizens (Carlson, 2017; Molyneux & Mourão, 2019). While journalists can, and do, challenge normalization in other areas of journalism practice (see Broersma & Graham 2016; Molyneux & Mourão, 2019), this study’s sole concern is whether political journalists create homogenous packs on Twitter, thus supporting the idea of homophily, and by extension, normalization, even as the hybrid media system (Chadwick, 2013) theoretically presents alternatives to the pack model with a wider range of interaction partners and voices outside the bubbles. While some studies indicate more negotiation around normalization in newer affordances such as quote tweetsor areas such as monitoring, sourcing, publishing, promoting and branding (Broersma & Graham, 2016; Molyneux & Mourão, 2019; Tandoc & Vos, 2016), the research overwhelmingly indicates that journalists’ interactions are dominated by other journalists andthat these homogenous onlinenetworks resemblethosebuilt by journalists offline (Hanusch & Nölleke, 2018). However, despite the plethora of studies indicating that journalists’ Twitter networks are so homogenous as to suggest homophily there has been little research so far specifically into homophily in those interactions even as journalists themselves report low levels of citizen engagement. For example, Gulyas (2017) found journalist/ citizen interaction at 23 and 27 percent in the US and UK respectively, and Nuernbergk (2016) saw only rare interactions between German journalists and their Twitter followers, thus suggesting that political journalists still prefer to connect with each other in “journalism-centered bubbles” (Molyneux & Mourão, 2019; Mourão, 2015; Nuernbergk, 2016, p. 877). Additionally, researchers have noted evidence of bubbles within bubbles (Bentivegna & Marchetti, 2018) with political journalists seen as more likely to interact with other political journalists (Hanusch & Nölleke,2018); selfsegregating by gender (Artwick, 2013; Usheretal.,2018), and focusing on those inside their own news organization (Bentivegna & Marchetti, 2018; Larsson, Kalsnes, & Christensen, 2017) with Vergeer (2015) reporting that regional reporters were more likely to do this than national journalists. While these studies were broad in nature, Hanusch and Nölleke (2018) specifically considered thepotential impactofbeat, gender,organizational context and geographic proximity in an extensive inquiry into homophily among Australian reporters and found a high degree of homophily across those four sharedcharacteristics. Homophily, or the tendency of individuals to form groups with those most similar to themselves (McPhersonetal.,2001)wasintroduced as a concept in the 1950s when Lazarsfeld and Merton (1954) proposed that individuals were far more likely to build networks around shared values in areas like religion or sport or around shared status in areas such as race, ethnicity, sex, age, religion, education and occupation (Hanusch & Nölleke, 2018; McPherson et al., 2001). As an elite specialty within the wider occupational field of journalism, political journalists are perhaps more sensitive to the homophilous effects of these tight-knitgroups as they seek validation from “those to whom we compare ourselves, those whose opinions we attend to, and simply those whom weare aware of andwatchforsignals aboutwhat is happening in our environment” (McPherson et al., 2001, p. 428). The tendency for political reporters to focus on each other was first labelled as “pack journalism” during the 1972 US presidential election when Rolling Stone reporter Tim Crouse noted that the journalists’intentfocusoneacho therled to a shared groupthink about the day’s most important stories and created a pack dynamic so strong that “almost all the reporters will take the same approach to the story”, even though they were ostensibly competing against each other(Crouse,1973). As former Newsweek Bureau Chief Karl Fleming said: “Their (the reporters’) abiding interest is making sure that nobody else has got anything that they don’t have—not getting something that nobody else has”(Crouse,1973). While Crouse observed the political journalism network and the resulting groupthink from his physical seat on the campaign bus, researchers can now observe virtual political journalism networks from afar through the analysis of publicly-visible Twitter conversations and the use of affordances such as retweets, replies, mentions and followings. Retweet and mention networks (which include both replies and indirect mentions) are often seen as the strongest interaction markers (Hanusch & Nölleke, 2018) and several studies have reported differences in the way journalistsuseretweets and mentions with more homophily seen in mentions than retweets (Hanusch & Nölleke 2018; Molyneux & Mourão, 2019; Nuernbergk, 2016). However, indirect mentions can be also be used as a “shout out” (Usher et al., 2018) thus diluting their effectiveness as a distinct measure of interactive intent. Retweets, despite multiple Twitter disclaimers to the contrary (Hanusch & Nölleke, 2018), are most often viewed as an endorsement of content (Meraz & Papacharissi, 2013; Russell, Hendricks, Choi, & Stephens, 2015), but they also convey endorsement of the user and the link between the original and retweeting sender provides evidence of a pre-existing homophilous network of like-minded people (Bruns & Burgess, 2012; Hanusch & Nölleke, 2018). While some journalists use replies to thread longer posts together and circumvent Twitter’s 280-character count (Molyneux & Mourão, 2019, p. 257), specific replies (as against indirect mentions) are more typically interactive with some research indicating potential heterophily with studies showing “public/citizen” users receiving as high as 48 percent of the journalists’replies (Brems, Temmerman, Graham, & Broersma, 2017). However, these studies don’t mention if the accounts received more than one reply which would help us consider the nature and value of such interactions, a problem noted by Parmelee and Deeley in 2017, when they queried the use of simple counts arguing that such one-offs were inadequate ways to measure reciprocity. Such reciprocity is often absent in followings (Kiousis, 2002) and, as Ausserhoffer and Maireder reported in 2013, followings are not a reliable metricasthey can bepaid for or artificially enhanced by computer scripts. Subsequently, this study views the affordances of retweets and replies as more indicative of actual intent, highlighting the user’s value to the journalist (Conover et al.,2011; Molyneux, 2015). Frequency of interactions is also important. As McPherson et al .(2001) outlined, homophily can be seen in those whose “opinions we attend to” and given the concerns raised by Parmelee and Deeley (2017) around one-off replies, this study measures interactivity by focusing on the political journalists’ most-frequent discussion partners in replies and retweets to see which voices the journalists most frequently attend to. This research builds on the developing work into Twitter journalism homophily (see particularly Hanusch & Nölleke, 2018) and is important as it is the first to examine this issue in the context of social media election coverage, specifically on Twitter, and takes the analysis further by looking at media practice in two similar media systems. The importance of studies such as this, which examine these “new” types of interactions on social media, cannot be overstated as the work done by political journalists remains essential to a citizen’s ability to understand politics and election campaigns even in a digital and networked age (Harder, Paulussen, & VanAelst, 2016; Kuhn & Nielsen, 2014).
3.Research Questions
This study explores retweets and replies as two distinct affordances and explores them separately for the presence of homophily by asking the following two research questions:
RQ1: To what extent can homophily be identified in political journalists’ retweets on Twitterin an election campaign?
RQ2: To what extent can homophily be identified in political journalists’ replies on Twitter in an election campaign?
Drawing from the categories devised in Hanusch and Nölleke’s study (2018) the study then considers if organizational context, types of news organization or gender can be seen to play a role in homophily in political journalists’ retweets and replies, which leads to these research questions:
RQ3:Doshared characteristics such as news organizations; type of news organizations and gender play a role in homophily in retweets?
RQ4: Do shared characteristic ssuch as news organizations; type of news organizations and gender play a role in homophily in replies?
Abstract: The tendency of political journalists to form insular groups or packs, chasing the same angles and quoting the same sources, is a well-documented issue in journalism studies and has long been criticized for its role in groupthink and homogenous news coverage. This groupthink attracted renewed criticism after the unexpected victory of Republican candidate Donald Trump in the 2016 US presidential election as the campaign coverage had indicated a likely win by the Democratic candidate Hillary Clinton. This pattern was repeated in the 2017 UK election when the Conservative party lost their majority after a campaign in which the news coverage had pointed to an overall Tory victory. Such groupthink is often attributed to homophily, the tendency of individuals to interact with those most like them, and while homophily in the legacy media system is well-studied, there is little research around homophily in the hybrid media system, even as social media platforms like Twitter facilitate the development—and analysis—of virtual political journalism packs. This study, which compares Twitter interactions among US and UK political reporters in the 2016 and 2017 national elections, shows that political journalists are overwhelmingly more likely to use Twitter to interact with other journalists, particularly political journalists, and that their offline tendencies to form homogenous networks have transferred online. There are some exceptions around factors such as gender, news organizations and types of news organization—and important distinctions between types of interactions—but overall the study provides evidence of sustained homophily as journalists continue to normalize Twitter.
Keywords: elections; groupthink; homophily; political journalism; Twitter, UK; US
Check also Journalistic Homophily on Social Media: Exploring journalists’ interactions with each other on Twitter. Folker Hanusch & Daniel Nölleke. Digital Journalism, https://www.bipartisanalliance.com/2018/02/journalists-continue-to-live-in-bubbles.html
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The worst about this is not their constant sanctimoniousness when talking to the peasants, when they are bigger offenders and keep their membership in their echo chambers and sub-echo chambers in greater proportion that the great unwashed... It is that in journalism schools they are already told to be aware of their biases, and the very human need to be part of a pack (or herd?) and they forget it immediately after taking the exams.
---
2. Literature Review
FromthetelegraphtotypewriterstotelevisiontoTwitter, successive technological innovations have transformed the norms and practice of journalism (Lasorsa, Lewis, & Holton, 2012) and each new technology has arrived amid much fanfare about its potential impact on political communication, particularly around election campaigns (Stromer-Galley, 2014). Ultimately however, the expectations and concerns about these potential utopias and dystopias have never been fully realized as the power structures of journalism and politics have instead normalized each new “new media” into their own practice (Singer, 2005). The potential power of digital media in election campaigns was first seen in the US in the 2004 Presidential campaign when it rocketed the relatively unknown candidate Howard Dean into the political and media stratosphere (Stromer-Galley, 2014) but as Margolis and Resnick had already argued in 2000, any of the digital advantages accruing to early adopters like Dean were soon eclipsed as the political and journalism elite folded these new technologies into existing practices when they recognized,a nd there by normalized, the “new” new media (Margolis & Resnick, 2000). Much of the research into Twitter journalism practice argues that journalists, seen as frequent, if not always skillful, Twitter users (Engesser & Humprecht, 2015) are well down the path of normalization, using Twitter in ways that conform to existing practice rather than using it to change journalism practice (see Lasorsa et al., 2012; Lawrence, Molyneux, Coddington, & Holton,2014; Lewis,2012; Molyneux & Mourão,2019; Nuernbergk,2016;Parmelee,2013). This is especially evidentinare as such as gatekeeping,wherejournalistshave long controlled whose voices make it through the editorial “gates” (Lasorsa et al., 2012; Singer, 2005), and Twitter gatekeeping can be seen in the “insider talk” and “regurgitation” of information flowing across Twitter (Lawrence et al., 2014; Parmelee, Roman, Beasley, & Perkins, 2019, p. 161) as journalists more frequently engage with other journalists or newsmakers—and even themselves—rather than interest groups, academics or citizens (Carlson, 2017; Molyneux & Mourão, 2019). While journalists can, and do, challenge normalization in other areas of journalism practice (see Broersma & Graham 2016; Molyneux & Mourão, 2019), this study’s sole concern is whether political journalists create homogenous packs on Twitter, thus supporting the idea of homophily, and by extension, normalization, even as the hybrid media system (Chadwick, 2013) theoretically presents alternatives to the pack model with a wider range of interaction partners and voices outside the bubbles. While some studies indicate more negotiation around normalization in newer affordances such as quote tweetsor areas such as monitoring, sourcing, publishing, promoting and branding (Broersma & Graham, 2016; Molyneux & Mourão, 2019; Tandoc & Vos, 2016), the research overwhelmingly indicates that journalists’ interactions are dominated by other journalists andthat these homogenous onlinenetworks resemblethosebuilt by journalists offline (Hanusch & Nölleke, 2018). However, despite the plethora of studies indicating that journalists’ Twitter networks are so homogenous as to suggest homophily there has been little research so far specifically into homophily in those interactions even as journalists themselves report low levels of citizen engagement. For example, Gulyas (2017) found journalist/ citizen interaction at 23 and 27 percent in the US and UK respectively, and Nuernbergk (2016) saw only rare interactions between German journalists and their Twitter followers, thus suggesting that political journalists still prefer to connect with each other in “journalism-centered bubbles” (Molyneux & Mourão, 2019; Mourão, 2015; Nuernbergk, 2016, p. 877). Additionally, researchers have noted evidence of bubbles within bubbles (Bentivegna & Marchetti, 2018) with political journalists seen as more likely to interact with other political journalists (Hanusch & Nölleke,2018); selfsegregating by gender (Artwick, 2013; Usheretal.,2018), and focusing on those inside their own news organization (Bentivegna & Marchetti, 2018; Larsson, Kalsnes, & Christensen, 2017) with Vergeer (2015) reporting that regional reporters were more likely to do this than national journalists. While these studies were broad in nature, Hanusch and Nölleke (2018) specifically considered thepotential impactofbeat, gender,organizational context and geographic proximity in an extensive inquiry into homophily among Australian reporters and found a high degree of homophily across those four sharedcharacteristics. Homophily, or the tendency of individuals to form groups with those most similar to themselves (McPhersonetal.,2001)wasintroduced as a concept in the 1950s when Lazarsfeld and Merton (1954) proposed that individuals were far more likely to build networks around shared values in areas like religion or sport or around shared status in areas such as race, ethnicity, sex, age, religion, education and occupation (Hanusch & Nölleke, 2018; McPherson et al., 2001). As an elite specialty within the wider occupational field of journalism, political journalists are perhaps more sensitive to the homophilous effects of these tight-knitgroups as they seek validation from “those to whom we compare ourselves, those whose opinions we attend to, and simply those whom weare aware of andwatchforsignals aboutwhat is happening in our environment” (McPherson et al., 2001, p. 428). The tendency for political reporters to focus on each other was first labelled as “pack journalism” during the 1972 US presidential election when Rolling Stone reporter Tim Crouse noted that the journalists’intentfocusoneacho therled to a shared groupthink about the day’s most important stories and created a pack dynamic so strong that “almost all the reporters will take the same approach to the story”, even though they were ostensibly competing against each other(Crouse,1973). As former Newsweek Bureau Chief Karl Fleming said: “Their (the reporters’) abiding interest is making sure that nobody else has got anything that they don’t have—not getting something that nobody else has”(Crouse,1973). While Crouse observed the political journalism network and the resulting groupthink from his physical seat on the campaign bus, researchers can now observe virtual political journalism networks from afar through the analysis of publicly-visible Twitter conversations and the use of affordances such as retweets, replies, mentions and followings. Retweet and mention networks (which include both replies and indirect mentions) are often seen as the strongest interaction markers (Hanusch & Nölleke, 2018) and several studies have reported differences in the way journalistsuseretweets and mentions with more homophily seen in mentions than retweets (Hanusch & Nölleke 2018; Molyneux & Mourão, 2019; Nuernbergk, 2016). However, indirect mentions can be also be used as a “shout out” (Usher et al., 2018) thus diluting their effectiveness as a distinct measure of interactive intent. Retweets, despite multiple Twitter disclaimers to the contrary (Hanusch & Nölleke, 2018), are most often viewed as an endorsement of content (Meraz & Papacharissi, 2013; Russell, Hendricks, Choi, & Stephens, 2015), but they also convey endorsement of the user and the link between the original and retweeting sender provides evidence of a pre-existing homophilous network of like-minded people (Bruns & Burgess, 2012; Hanusch & Nölleke, 2018). While some journalists use replies to thread longer posts together and circumvent Twitter’s 280-character count (Molyneux & Mourão, 2019, p. 257), specific replies (as against indirect mentions) are more typically interactive with some research indicating potential heterophily with studies showing “public/citizen” users receiving as high as 48 percent of the journalists’replies (Brems, Temmerman, Graham, & Broersma, 2017). However, these studies don’t mention if the accounts received more than one reply which would help us consider the nature and value of such interactions, a problem noted by Parmelee and Deeley in 2017, when they queried the use of simple counts arguing that such one-offs were inadequate ways to measure reciprocity. Such reciprocity is often absent in followings (Kiousis, 2002) and, as Ausserhoffer and Maireder reported in 2013, followings are not a reliable metricasthey can bepaid for or artificially enhanced by computer scripts. Subsequently, this study views the affordances of retweets and replies as more indicative of actual intent, highlighting the user’s value to the journalist (Conover et al.,2011; Molyneux, 2015). Frequency of interactions is also important. As McPherson et al .(2001) outlined, homophily can be seen in those whose “opinions we attend to” and given the concerns raised by Parmelee and Deeley (2017) around one-off replies, this study measures interactivity by focusing on the political journalists’ most-frequent discussion partners in replies and retweets to see which voices the journalists most frequently attend to. This research builds on the developing work into Twitter journalism homophily (see particularly Hanusch & Nölleke, 2018) and is important as it is the first to examine this issue in the context of social media election coverage, specifically on Twitter, and takes the analysis further by looking at media practice in two similar media systems. The importance of studies such as this, which examine these “new” types of interactions on social media, cannot be overstated as the work done by political journalists remains essential to a citizen’s ability to understand politics and election campaigns even in a digital and networked age (Harder, Paulussen, & VanAelst, 2016; Kuhn & Nielsen, 2014).
3.Research Questions
This study explores retweets and replies as two distinct affordances and explores them separately for the presence of homophily by asking the following two research questions:
RQ1: To what extent can homophily be identified in political journalists’ retweets on Twitterin an election campaign?
RQ2: To what extent can homophily be identified in political journalists’ replies on Twitter in an election campaign?
Drawing from the categories devised in Hanusch and Nölleke’s study (2018) the study then considers if organizational context, types of news organization or gender can be seen to play a role in homophily in political journalists’ retweets and replies, which leads to these research questions:
RQ3:Doshared characteristics such as news organizations; type of news organizations and gender play a role in homophily in retweets?
RQ4: Do shared characteristic ssuch as news organizations; type of news organizations and gender play a role in homophily in replies?
While Democrats show stronger negative emotional response to moral violations than Republicans, partisans of both parties express significantly greater negativity when a politician of the other party violates a moral foundation
Voters’ Partisan Responses to Politicians’ Immoral Behavior. Annemarie S. Walter, David P. Redlawsk. Political Psychology, March 27 2019. https://doi.org/10.1111/pops.12582
Abstract: Politicians’ moral behaviors affect how voters evaluate them. But existing empirical research on the effects of politicians’ violations of moral standards pays little attention to the heterogeneous moral foundations of voters in assessing responses to violations. It also pays little attention to the ways partisan preferences shape responses. We examine voters’ heterogeneous evaluative and emotional responses to presumably immoral behaviors by politicians. We make use of moral foundation theory’s argument that people vary in the extent to which they endorse, value, and use the five universally available moral intuitions: care, fairness, loyalty, authority and sanctity. We report on a 5 × 3 between‐subjects experiment asking a random sample of 2,026 U.S. respondents to respond to politicians’ violations of different moral foundations. We randomly vary which of the five foundations is violated and the partisanship of the actor (Republican/ Democrat /Nonpartisan). Results suggest that partisanship rather than moral foundations drives most of U.S. voters’ responses to moral foundations violations by politicians. These foundations seem malleable when partisan actors are involved. While Democrats in this sample show stronger negative emotional response to moral violations than Republicans, partisans of both parties express significantly greater negativity when a politician of the other party violates a moral foundation.
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Immoral behavior by politicians is nothing new. The candidacy and subsequent election of Donald Trump to the U.S. presidency seems to suggest that in the current American political environment, moral violations may be more rule than exception. During his campaign, Trump was accused of sexual misconduct as a tape surfaced where he talked about “grabbing them by the pussy,” while a number of women came forward accusing Trump of inappropriate and sexually harassing behaviors that in other times would have doomed his candidacy. Trump routinely verbally violated a wide range of moral norms during his campaign, for example, mocking a reporter for his disabilities and referring to a former Miss Universe contestant campaigning for Hillary Clinton as “Miss Piggy.” Even after the election, Trump continued to violate basic moral positions that might have sunk other presidents. Recently, Stormy Daniels, a pornographic movie star, alleged that she had had an affair with Trump and he paid her to cover it up just before the November 2016 vote. Unlike John Edwards, the 2008 Democratic presidential candidate whose campaign was doomed when an affair came to light, Trump continues with little obvious impact on his favorability ratings.
Each of the above would be considered clear moral violations by moral foundation theorists, in particular, violations of the foundations of “care” and “sanctity” (Graham et al., 2011; Haidt & Graham, 2011). Among Trump’s most consistent supporters are religious conservative voters who generally perceive themselves as high in morality in everyday life, while identifying as strong Republicans when it comes to politics. This apparent conflict between moral values and partisan preferences suggests a need to examine the link between voters’ endorsements of moral foundations and their responses to moral transgressions of those foundations by politicians. If moral foundations are, in fact, innate and foundational, voter’s moral values should dominate when a foundation is violated. A voter who strongly cares about a particular moral foundation should react negatively to its violation, regardless of the party of the politician involved. And yet, as the Trump example makes clear, there is reason to question this belief. Over 90% of Republican voters supported Trump in 2016, despite his continual violations of moral foundations, and presumably in opposition to their own support of those same foundations.
We wish to examine the extent to which underlying moral values subscribed to by American voters condition responses to violations of moral foundations by politicians. We consider whether the extent to which people care about moral foundations like care, fairness, loyalty, authority, and sanctity influences their negative emotional responses to violations. Alternatively, given the partisan nature of American politics in the early twenty‐first century, it may be that partisan agreement is more important than moral foundations. We seek to answer the question of whether partisanship in America also extends to the point of overriding, or at least reducing, the effect of underlying moral values.
Partisanship is a core feature of the American political system. It acts as a perceptual screen (Campbell, Converse, Miller, & Stokes, 1960) coloring how partisans view all aspects of politics. More recent research on motivated reasoning (Lodge & Taber, 2013; Redlawsk, 2002; Taber & Lodge, 2006) provides a mechanism for this process, as existing affective evaluations—such as partisan preference—influence the cognitive processing of relevant information. As a result, in an era of increasing partisan and social sorting, partisan preference may provide a great deal of cover for politicians who violate moral foundations. Mason (2018) documents how American social and political identities have recently aligned so that previous crosscutting cleavages have all but disappeared. As a result, partisanship is now reinforced by other social identities, including religious identities. There may be good reason to think that moral foundations themselves can become subsumed within partisan identity, so that violations of foundations by the “other side” are much worse than violations by “our side.”
At the same time, studies have shown that exposure to scandals depresses voters’ candidate evaluations (Bhatti, Hansen, & Olsen, 2013; Carlson, Ganiel, & Hyde, 2000; Doherty et al., 2011) and reduces trust in political institutions and the political process (Bowler & Karp, 2004; Maier, 2011). Politicians’ moral transgressions are extensively covered by the media (Fogarty, 2013). This does not appear to have changed in recent years; the allegations against Trump were certainly front and center in media reports during the 2016 presidential campaign. Moreover, following Trump’s election, allegations of sexual harassment against other powerful men in and out of politics spurred the #metoo movement, as women recounted their experiences. Former Sen. Al Franken, thought to be in the mix for the presidential campaign in 2020, was forced to resign, while others have also lost positions of power. Yet the very same kinds of claims against Trump did not, in the end, derail his candidacy, nor so far, his presidency.
Emotions play an important role in moral foundations theory (Haidt, 2003) and are key factors in voters’ moral judgments about politicians and institutions (Ben‐Nun Bloom, 2014; Bowler & Karp, 2004). Emotions not only often guide moral judgments, but also shape voting behavior. Emotions have been found to underpin political campaigns generally (Marcus et al., 2000; Redlawsk, 2006) as voters both think and feel about politics. Negative emotions can be especially important. Among the many aspects of politics that might trigger emotional responses, we would expect violations of moral foundations by politicians to be central, with voters expressing negative emotions about violators, but only to the extent that the voters themselves care about any given foundation that has been violated.
Despite the prominent role of emotions in explaining political behavior and numerous studies examining effects of politicians’ violations of moral standards, little attention has been paid to the intersection of the two, that is, how voters respond emotionally to politicians’ moral violations (the notable exceptions are Halmburger, Rothmund, Schulte, & Baumert, 2012 and Jiang et al., 2011). In addition, to our knowledge, no study has examined how heterogeneous preferences for moral foundations condition how voters respond to politicians’ moral transgressions.
This study thus aims to answer three research questions: (1) How do American voters respond emotionally to violations of moral foundations by politicians? (2) Are voters’ emotional responses conditioned by their own moral values? and (3) Does partisanship influence the negative emotional responses voters have to violations of moral foundations? To examine these questions, we conducted a 5 × 3 between‐subjects experiment with an online random sample of about 2,000 U.S. voters. We manipulated the moral foundation violated by a politician (care, fairness, loyalty, authority, and sanctity) and the partisanship of the politician involved (Republican, Democrat and no partisan label).
We find voters express negative emotional responses to politicians’ moral transgressions, but the level of negativity is strongly conditioned by partisanship. Democratic voters have stronger negative emotional responses to many of these moral violations than do Republicans. At the same time, partisans of both parties express more negative emotions when a politician of the other party violates moral foundations, all else equal, while responding more similarly to a nonpartisan actor. Finally, while we anticipated that a voter who endorses the values of a particular foundation to a greater degree would be more negative when it is violated, this effect was and clearly less than the effects of party when partisan actors were involved.
The remainder of this article proceeds as follows. First, we discuss moral foundation theory and the role of emotions. Second, we summarize the literature explaining individual variance in response to politicians’ immoral behaviors and develop hypotheses from this literature. Third, the experimental design, analysis strategy, and operationalization of the variables are discussed. Finally, results are presented and conclusions are drawn.
Moral foundation theory (MFT) sees moral judgment as an intuitive process characterized by automatic affective reactions to stimuli (Clifford, Iyengar, Cabezzam, & Sinnott‐Armstrong, 2015). This is in line with the social intuitionism model of morality (Haidt, 2001) which argues that people know intuitively whether acts are right or wrong. They are capable of swift judgment of an (im)moral act, but they take considerably more time to come up with a rationale when asked to explain their judgment (Haidt & Hersh, 2001). Haidt and Hersh (2001) argue that intuitions and emotions most often precede and guide moral emotions.
MFT categorizes moral intuitions into five foundations: care, fairness, loyalty, authority, and sanctity (Haidt & Graham, 2011). Care refers to the dislike for the suffering of others; fairness to a commitment to fairness and justice. Loyalty is seen as a commitment to one’s own group. Authority refers to respect for authority and tradition, and sanctity refers to concerns with purity and contamination. People differ in the extent to which they endorse these five values, and thus MFT also provides an understanding of moral diversity (Graham et al., 2011). MFT extends most scales used in moral psychology as it does not limit the moral domain to concerns about individuals harming or unfairly treating other individuals (Graham et al., 2011). Moreover, MFT is meant to cover the full range of moral concerns, including those found in non‐Western cultures, in religious practices, and among political conservatives (Graham et al., 2011). Studies have found that political liberals and conservatives differ in the weight that they place on the various moral foundations (Graham et al., 2009; Haidt & Graham, 2007). Specifically, liberals have been found to rate considerations of care and fairness as significantly more important moral values than loyalty, authority, or purity. To liberals, acts are perceived as immoral primarily to the extent that they harm others or treat people unfairly.
There appear to be only two studies that have examined people’s emotional responses to moral transgressions by politicians (Halmburger et al., 2012; Jiang et al., 2011). Both studies report that exposure to a political scandal generates negative emotions towards the politician involved. Halmburger et al. (2012) incorporates specific moral emotions in their study, reporting higher levels of anger and shame when subjects are exposed to a news report including a politician’s moral transgression. They also find that negative moral emotions stimulate need for retribution versus need for restoration of the moral transgressing politician (Halmburger et al., 2012). But these studies are of limited generalizability since they do not effectively account for the role partisanship plays in conditioning responses when partisan actors are involved.
Although moral foundation theory is a prominent theory, it is not uncontroversial. Various scholars criticize the assumptions underlying MFT, such as the innateness and stability of moral foundations (Smith, Alford, Hibbing, Martin, & Hatemi, 2017), the existence of five or six distinct moral foundations underlying moral judgment (Schein & Gray, 2018), and the strength and direction of the relationship between moral foundations and political predispositions (Ciuk, 2018; Smith et al., 2017). Most recently, Connors (2019) reports that political values—like moral foundations thought by most scholars to be core beliefs—are readily influence by the social environment. Even with this, the theory is well enough established with key implications for politics that call for testing it in the political context we do here, following work by Clifford et al. (2015).
Numerous factors are mentioned as potential sources for this variance in voters’ responses. Voters may respond differently to different types of scandals (Bhatti et al., 2013; Carlson et al., 2000; Doherty et al., 2011; Fernández‐Vázquez et al., 2016). Thompson (2013) distinguishes three types of scandals, namely sex scandals, financial fraud scandals, and corruption scandals. Financial scandals are punished more severely than sex scandals (Brenton, 2011; Carlson et al., 2000, Funk, 1996), although Doherty et al. (2011) notes this holds only as long as the sex scandal does not involve abuse of power. The identity of the politician involved matters as does the politician’s response to the moral transgression (Lee, 2015; Tiedens, 2001). Gender appears related to voters’ judgments (Brenton, 2011), but probably in combination with the type of scandal (Carlson et al., 2000; Smith et al., 2015).
Other research has shown that trait impressions and prior affect for the politician influence voters’ responses (Fischle, 2000; Funk, 1996). In judging a politician’s moral transgression, Funk (1996) argues that perceived competence matters more than perceived warmth, but only for the more politically knowledgeable voters (Funk, 1996). Recently, Laustsen and Bor (2017) have shown in an electoral context that warmth is the most influential candidate trait on which people judge politicians, perhaps challenging Funk. It also matters how credible voters perceive the information about a scandal—especially when there are claims that the politician committed the transgression intentionally (Anduiza, Gallego, & Munoz, 2013; Lee, 2015). The relevance and importance of the transgression also influences voters’ responses (Anduiza et al., 2013; Lee, 2015). These perceptions are also affected by how their news sources and the media in general frame the scandal (Peterson & Vonnahme, 2014; Shah, Watts, Domke, & Fan, 2002).
Finally, and especially relevant for our study, political identity in the form of partisanship may influence voters’ perceptions of politicians’ immoral behavior (Anduiza et al., 2013; Bhatti et al., 2013; Blais et al., 2010; Fischle, 2000). Partisan preferences can engage motivated reasoning processes that lead voters to discount or otherwise accept behavior from politicians who share those preferences, that they would not for politicians from another party (Kunda, 1990; Redlawsk, 2002). People selectively process information in ways that enable them to arrive at conclusions congruent and congenial to their prior beliefs, including political beliefs (Fischle, 2000). This process can readily lead to partisans rejecting information about immoral behavior by a copartisan politician as not credible. Even when they acknowledge the moral transgression, partisan voters might still bear a less negative judgment about their party’s candidate. While partisanship may not affect perceptions of the facts of the scandal, it may still affect political judgment (Blais et al., 2010).
The usual assumption is that partisan bias works both ways, so partisans perceive their own party more positively and other parties more negatively. However, Blais, Gidengil, and Kilibarda (2017) argue that the partisan effect is asymmetrical, although they note there has been little systematic investigation of how symmetric (or asymmetric) it might be. They find that partisans view their own parties as less corrupt than do nonpartisans, but they do not necessarily view other parties as more corrupt. Anduiza et al. (2013) also find an asymmetrical effect, arguing that moral transgressions are judged differently by voters depending on whether the politician involved is a member of the respondent’s party, rival party, or of an unknown affiliation. However, not all studies find this partisan effect when it comes to how voters process politician’s moral violations (Halmburger et al., 2012). Some find that political sophistication interacts with this partisan bias, and the partisan bias is absent among the more politically sophisticated.
While we do not have a direct test of the mechanism by which partisanship conditions the effects of moral violations on emotional responses to politicians, a lengthy literature on partisanship in American politics makes clear that partisans see the political world through a very specific perceptual screen (Campbell et al., 1960). Motivated reasoning (Lodge & Taber, 2013; Redlawsk, 2002) likely becomes engaged when a voter sees a copartisan politician violating a moral foundation, leading to biased processing of the event, and the reduction of negativity about the event. But when the other party commits the violation, partisans are more than willing to express negative emotions about the event. Brain imaging studies reinforce the potential of this mechanism as distinct differences are seen between Democrats and Republicans in their processing of political information (Schreiber et al., 2013). Note that while we started this article with a brief discussion about moral violations by U.S. President Trump and his seeming imperviousness to them, it is worth recalling that it is generally only his Republican supporters who accept his behavior.
This study contributes to the literature in various ways. First of all, it is among a handful studies (Halmburger et al., 2012; Jiang et al., 2011) to study emotional responses to moral violations. A follow‐up study will examine the specific negative emotions to see whether these moral violations evoke specific discrete emotions, in particular so‐called moral emotions (Haidt, 2003). However, our main interest here is to see how partisanship and the importance of moral values for the voter affect emotional responses more generally.
Second, this study is the first to assess the role of voters’ moral values in their response to moral transgressions, as the results show they do matter. However, partisanship, more often than not, overrides the effects of moral values. This is a very interesting finding and suggests that moral foundations are maybe not as innate and foundational as might be supposed (see also, Connors [2019] on political values). The partisanship effect in this study is asymmetrical, showing that voters judge the opposing candidate more harshly for moral transgressions than their own candidate. This is in line with the trend of negative partisanship in American politics (Mason, 2018). Research has shown that while the feelings Democrats and Republicans have about their own party have not changed, their feelings about the opposing party have become much more negative (Abramowitz & Webster, 2016).
As with any research, this study is not without its shortcomings, one being the time frame in which it was conducted, namely following the 2016 presidential elections, which led to the election of a politician with frequent moral transgressions. It is not unthinkable that in a different time period we might find differences with respect to the strength of partisan responses to violations of moral foundations. Thus, we must consider that aspect of our results to be conditional, warranting further study in a different context.
Another limitation is that the vignettes used were specific. That is, the politician referred to in a vignette took a specific action. There is probably heterogeneity in people’s responses to these actions, and by the necessity of the research design, each study participant saw only one action representing one moral foundation. It is possible, for example, that a different vignette representing the same foundation might have a different impact on participants’ emotions. However, we are less interested here in the specific reactions to specific vignettes than we are in the larger story, that moral foundations appear to be readily ignored in the face of partisan actors. Across all of the vignettes we use, partisan voters were far less negative about a same‐party actor violating a foundation than they were an opposite‐party actor. At the same time, although extensively pretested, the authority vignette had the lowest homogeneity coefficient and resulted in the weakest findings. Apparently American voters did not find that specific example to be compelling.
Finally, as described in Footnote 2, new research by Montgomery et al. (2018) suggests that appropriate care must be taken in measuring moderating variables in an experimental context. We were concerned that measuring our moderators—partisanship and moral values—before the experimental treatment would prime participants as to the purpose of our study and thus influence their responses to the treatment. Thus, we measured them at the end of the study. While the very small shared variance we report between the moderators and treatment provides some confidence that our results are not biased, future studies should consider ways to separate these measures, such as the use of multiple waves. If the work by Montgomery et al. (2018) is sustained through additional research, experimentalists in general will need to consider whether the potential costs of such strategies outweigh the risks of biasing results by measuring moderators after an experimental treatment.
While recognizing the potential bias suggested by Montgomery et al. (2018) may be present in our analyses, notwithstanding the very small shared variance between our measures, any such bias would matter more if we were making inferences about the direct effects of specific coefficients in our models. But, instead, we are more interested in the patterns that we see in the data when different moral foundations are engaged across partisan voters. To the extent that these patterns of differential response by partisan voters and those who more or less adopt the moral values of the foundation are biased, we would not expect the bias to eliminate the differences we see across groups. Thus, while the effects of any given treatment may be more or less than we find here, we expect any bias would be unidirectional across the treatments, and thus the patterns we find would remain.
Notwithstanding these limitations, this study makes a significant contribution to the moral foundations literature. For the first time, we examine the intersection of partisanship and moral foundations and find that, as with so many other things in American politics in the early twenty‐first century, responses to moral violations by politicians are subject to partisan preferences. This holds even when voters themselves feel strongly about a given moral foundation. Put simply, when the effects of partisanship and strength of support for moral values are tested against each other in predicting emotional responses to violations of moral foundations, partisanship usually comes out the winner. This provides new insight into the role of moral violations in politics and helps us understand perhaps why some American politicians are able to continue to receive strong support from their own party voters even after violating what are thought to be basic moral values.
Abstract: Politicians’ moral behaviors affect how voters evaluate them. But existing empirical research on the effects of politicians’ violations of moral standards pays little attention to the heterogeneous moral foundations of voters in assessing responses to violations. It also pays little attention to the ways partisan preferences shape responses. We examine voters’ heterogeneous evaluative and emotional responses to presumably immoral behaviors by politicians. We make use of moral foundation theory’s argument that people vary in the extent to which they endorse, value, and use the five universally available moral intuitions: care, fairness, loyalty, authority and sanctity. We report on a 5 × 3 between‐subjects experiment asking a random sample of 2,026 U.S. respondents to respond to politicians’ violations of different moral foundations. We randomly vary which of the five foundations is violated and the partisanship of the actor (Republican/ Democrat /Nonpartisan). Results suggest that partisanship rather than moral foundations drives most of U.S. voters’ responses to moral foundations violations by politicians. These foundations seem malleable when partisan actors are involved. While Democrats in this sample show stronger negative emotional response to moral violations than Republicans, partisans of both parties express significantly greater negativity when a politician of the other party violates a moral foundation.
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Immoral behavior by politicians is nothing new. The candidacy and subsequent election of Donald Trump to the U.S. presidency seems to suggest that in the current American political environment, moral violations may be more rule than exception. During his campaign, Trump was accused of sexual misconduct as a tape surfaced where he talked about “grabbing them by the pussy,” while a number of women came forward accusing Trump of inappropriate and sexually harassing behaviors that in other times would have doomed his candidacy. Trump routinely verbally violated a wide range of moral norms during his campaign, for example, mocking a reporter for his disabilities and referring to a former Miss Universe contestant campaigning for Hillary Clinton as “Miss Piggy.” Even after the election, Trump continued to violate basic moral positions that might have sunk other presidents. Recently, Stormy Daniels, a pornographic movie star, alleged that she had had an affair with Trump and he paid her to cover it up just before the November 2016 vote. Unlike John Edwards, the 2008 Democratic presidential candidate whose campaign was doomed when an affair came to light, Trump continues with little obvious impact on his favorability ratings.
Each of the above would be considered clear moral violations by moral foundation theorists, in particular, violations of the foundations of “care” and “sanctity” (Graham et al., 2011; Haidt & Graham, 2011). Among Trump’s most consistent supporters are religious conservative voters who generally perceive themselves as high in morality in everyday life, while identifying as strong Republicans when it comes to politics. This apparent conflict between moral values and partisan preferences suggests a need to examine the link between voters’ endorsements of moral foundations and their responses to moral transgressions of those foundations by politicians. If moral foundations are, in fact, innate and foundational, voter’s moral values should dominate when a foundation is violated. A voter who strongly cares about a particular moral foundation should react negatively to its violation, regardless of the party of the politician involved. And yet, as the Trump example makes clear, there is reason to question this belief. Over 90% of Republican voters supported Trump in 2016, despite his continual violations of moral foundations, and presumably in opposition to their own support of those same foundations.
We wish to examine the extent to which underlying moral values subscribed to by American voters condition responses to violations of moral foundations by politicians. We consider whether the extent to which people care about moral foundations like care, fairness, loyalty, authority, and sanctity influences their negative emotional responses to violations. Alternatively, given the partisan nature of American politics in the early twenty‐first century, it may be that partisan agreement is more important than moral foundations. We seek to answer the question of whether partisanship in America also extends to the point of overriding, or at least reducing, the effect of underlying moral values.
Partisanship is a core feature of the American political system. It acts as a perceptual screen (Campbell, Converse, Miller, & Stokes, 1960) coloring how partisans view all aspects of politics. More recent research on motivated reasoning (Lodge & Taber, 2013; Redlawsk, 2002; Taber & Lodge, 2006) provides a mechanism for this process, as existing affective evaluations—such as partisan preference—influence the cognitive processing of relevant information. As a result, in an era of increasing partisan and social sorting, partisan preference may provide a great deal of cover for politicians who violate moral foundations. Mason (2018) documents how American social and political identities have recently aligned so that previous crosscutting cleavages have all but disappeared. As a result, partisanship is now reinforced by other social identities, including religious identities. There may be good reason to think that moral foundations themselves can become subsumed within partisan identity, so that violations of foundations by the “other side” are much worse than violations by “our side.”
At the same time, studies have shown that exposure to scandals depresses voters’ candidate evaluations (Bhatti, Hansen, & Olsen, 2013; Carlson, Ganiel, & Hyde, 2000; Doherty et al., 2011) and reduces trust in political institutions and the political process (Bowler & Karp, 2004; Maier, 2011). Politicians’ moral transgressions are extensively covered by the media (Fogarty, 2013). This does not appear to have changed in recent years; the allegations against Trump were certainly front and center in media reports during the 2016 presidential campaign. Moreover, following Trump’s election, allegations of sexual harassment against other powerful men in and out of politics spurred the #metoo movement, as women recounted their experiences. Former Sen. Al Franken, thought to be in the mix for the presidential campaign in 2020, was forced to resign, while others have also lost positions of power. Yet the very same kinds of claims against Trump did not, in the end, derail his candidacy, nor so far, his presidency.
Emotions play an important role in moral foundations theory (Haidt, 2003) and are key factors in voters’ moral judgments about politicians and institutions (Ben‐Nun Bloom, 2014; Bowler & Karp, 2004). Emotions not only often guide moral judgments, but also shape voting behavior. Emotions have been found to underpin political campaigns generally (Marcus et al., 2000; Redlawsk, 2006) as voters both think and feel about politics. Negative emotions can be especially important. Among the many aspects of politics that might trigger emotional responses, we would expect violations of moral foundations by politicians to be central, with voters expressing negative emotions about violators, but only to the extent that the voters themselves care about any given foundation that has been violated.
Despite the prominent role of emotions in explaining political behavior and numerous studies examining effects of politicians’ violations of moral standards, little attention has been paid to the intersection of the two, that is, how voters respond emotionally to politicians’ moral violations (the notable exceptions are Halmburger, Rothmund, Schulte, & Baumert, 2012 and Jiang et al., 2011). In addition, to our knowledge, no study has examined how heterogeneous preferences for moral foundations condition how voters respond to politicians’ moral transgressions.
This study thus aims to answer three research questions: (1) How do American voters respond emotionally to violations of moral foundations by politicians? (2) Are voters’ emotional responses conditioned by their own moral values? and (3) Does partisanship influence the negative emotional responses voters have to violations of moral foundations? To examine these questions, we conducted a 5 × 3 between‐subjects experiment with an online random sample of about 2,000 U.S. voters. We manipulated the moral foundation violated by a politician (care, fairness, loyalty, authority, and sanctity) and the partisanship of the politician involved (Republican, Democrat and no partisan label).
We find voters express negative emotional responses to politicians’ moral transgressions, but the level of negativity is strongly conditioned by partisanship. Democratic voters have stronger negative emotional responses to many of these moral violations than do Republicans. At the same time, partisans of both parties express more negative emotions when a politician of the other party violates moral foundations, all else equal, while responding more similarly to a nonpartisan actor. Finally, while we anticipated that a voter who endorses the values of a particular foundation to a greater degree would be more negative when it is violated, this effect was and clearly less than the effects of party when partisan actors were involved.
The remainder of this article proceeds as follows. First, we discuss moral foundation theory and the role of emotions. Second, we summarize the literature explaining individual variance in response to politicians’ immoral behaviors and develop hypotheses from this literature. Third, the experimental design, analysis strategy, and operationalization of the variables are discussed. Finally, results are presented and conclusions are drawn.
Moral Violations and Emotions
We build on two strands of literature: the scandal literature from political science and literature on (moral) emotions and moral political judgements from social psychology. Moral judgment is the evaluation of an act as morally wrong or right (Ben‐Nun Bloom, 2014). Moral transgressions, that is, harm to others’ welfare, are thought to be inherently wrong since they have an intrinsic effect on the well‐being of others (Ben‐Nun Bloom, 2014). Moral transgressions by politicians can become scandals, although the word “scandal” itself does not refer to the moral transgression, but to the communicative event surrounding the moral transgression becoming public (Lee, 2015).Moral foundation theory (MFT) sees moral judgment as an intuitive process characterized by automatic affective reactions to stimuli (Clifford, Iyengar, Cabezzam, & Sinnott‐Armstrong, 2015). This is in line with the social intuitionism model of morality (Haidt, 2001) which argues that people know intuitively whether acts are right or wrong. They are capable of swift judgment of an (im)moral act, but they take considerably more time to come up with a rationale when asked to explain their judgment (Haidt & Hersh, 2001). Haidt and Hersh (2001) argue that intuitions and emotions most often precede and guide moral emotions.
MFT categorizes moral intuitions into five foundations: care, fairness, loyalty, authority, and sanctity (Haidt & Graham, 2011). Care refers to the dislike for the suffering of others; fairness to a commitment to fairness and justice. Loyalty is seen as a commitment to one’s own group. Authority refers to respect for authority and tradition, and sanctity refers to concerns with purity and contamination. People differ in the extent to which they endorse these five values, and thus MFT also provides an understanding of moral diversity (Graham et al., 2011). MFT extends most scales used in moral psychology as it does not limit the moral domain to concerns about individuals harming or unfairly treating other individuals (Graham et al., 2011). Moreover, MFT is meant to cover the full range of moral concerns, including those found in non‐Western cultures, in religious practices, and among political conservatives (Graham et al., 2011). Studies have found that political liberals and conservatives differ in the weight that they place on the various moral foundations (Graham et al., 2009; Haidt & Graham, 2007). Specifically, liberals have been found to rate considerations of care and fairness as significantly more important moral values than loyalty, authority, or purity. To liberals, acts are perceived as immoral primarily to the extent that they harm others or treat people unfairly.
There appear to be only two studies that have examined people’s emotional responses to moral transgressions by politicians (Halmburger et al., 2012; Jiang et al., 2011). Both studies report that exposure to a political scandal generates negative emotions towards the politician involved. Halmburger et al. (2012) incorporates specific moral emotions in their study, reporting higher levels of anger and shame when subjects are exposed to a news report including a politician’s moral transgression. They also find that negative moral emotions stimulate need for retribution versus need for restoration of the moral transgressing politician (Halmburger et al., 2012). But these studies are of limited generalizability since they do not effectively account for the role partisanship plays in conditioning responses when partisan actors are involved.
Although moral foundation theory is a prominent theory, it is not uncontroversial. Various scholars criticize the assumptions underlying MFT, such as the innateness and stability of moral foundations (Smith, Alford, Hibbing, Martin, & Hatemi, 2017), the existence of five or six distinct moral foundations underlying moral judgment (Schein & Gray, 2018), and the strength and direction of the relationship between moral foundations and political predispositions (Ciuk, 2018; Smith et al., 2017). Most recently, Connors (2019) reports that political values—like moral foundations thought by most scholars to be core beliefs—are readily influence by the social environment. Even with this, the theory is well enough established with key implications for politics that call for testing it in the political context we do here, following work by Clifford et al. (2015).
Heterogeneous Responses to Politicians’ Moral Transgressions
Moral transgressions by a politician should signal to voters that he or she is an immoral candidate, which should negatively affect the candidate’s electoral prospects. If it were that simple, we would have little to examine here: Voters would simply punish those who violate moral standards, with those feeling more strongly about a given moral foundation responding more negatively. However, politicians embroiled in scandals are not always electorally punished for their moral transgressions, and individual voters’ responses to such transgressions differ in strength (Fernández‐Vázquez, Barberá, & Rivero, 2016). This has puzzled scholars and stimulated research trying to understand the psychology of the public’s heterogeneous reactions to scandals (e.g., Fischle, 2000; Halmburger et al., 2012; Lee, 2015).Numerous factors are mentioned as potential sources for this variance in voters’ responses. Voters may respond differently to different types of scandals (Bhatti et al., 2013; Carlson et al., 2000; Doherty et al., 2011; Fernández‐Vázquez et al., 2016). Thompson (2013) distinguishes three types of scandals, namely sex scandals, financial fraud scandals, and corruption scandals. Financial scandals are punished more severely than sex scandals (Brenton, 2011; Carlson et al., 2000, Funk, 1996), although Doherty et al. (2011) notes this holds only as long as the sex scandal does not involve abuse of power. The identity of the politician involved matters as does the politician’s response to the moral transgression (Lee, 2015; Tiedens, 2001). Gender appears related to voters’ judgments (Brenton, 2011), but probably in combination with the type of scandal (Carlson et al., 2000; Smith et al., 2015).
Other research has shown that trait impressions and prior affect for the politician influence voters’ responses (Fischle, 2000; Funk, 1996). In judging a politician’s moral transgression, Funk (1996) argues that perceived competence matters more than perceived warmth, but only for the more politically knowledgeable voters (Funk, 1996). Recently, Laustsen and Bor (2017) have shown in an electoral context that warmth is the most influential candidate trait on which people judge politicians, perhaps challenging Funk. It also matters how credible voters perceive the information about a scandal—especially when there are claims that the politician committed the transgression intentionally (Anduiza, Gallego, & Munoz, 2013; Lee, 2015). The relevance and importance of the transgression also influences voters’ responses (Anduiza et al., 2013; Lee, 2015). These perceptions are also affected by how their news sources and the media in general frame the scandal (Peterson & Vonnahme, 2014; Shah, Watts, Domke, & Fan, 2002).
Finally, and especially relevant for our study, political identity in the form of partisanship may influence voters’ perceptions of politicians’ immoral behavior (Anduiza et al., 2013; Bhatti et al., 2013; Blais et al., 2010; Fischle, 2000). Partisan preferences can engage motivated reasoning processes that lead voters to discount or otherwise accept behavior from politicians who share those preferences, that they would not for politicians from another party (Kunda, 1990; Redlawsk, 2002). People selectively process information in ways that enable them to arrive at conclusions congruent and congenial to their prior beliefs, including political beliefs (Fischle, 2000). This process can readily lead to partisans rejecting information about immoral behavior by a copartisan politician as not credible. Even when they acknowledge the moral transgression, partisan voters might still bear a less negative judgment about their party’s candidate. While partisanship may not affect perceptions of the facts of the scandal, it may still affect political judgment (Blais et al., 2010).
The usual assumption is that partisan bias works both ways, so partisans perceive their own party more positively and other parties more negatively. However, Blais, Gidengil, and Kilibarda (2017) argue that the partisan effect is asymmetrical, although they note there has been little systematic investigation of how symmetric (or asymmetric) it might be. They find that partisans view their own parties as less corrupt than do nonpartisans, but they do not necessarily view other parties as more corrupt. Anduiza et al. (2013) also find an asymmetrical effect, arguing that moral transgressions are judged differently by voters depending on whether the politician involved is a member of the respondent’s party, rival party, or of an unknown affiliation. However, not all studies find this partisan effect when it comes to how voters process politician’s moral violations (Halmburger et al., 2012). Some find that political sophistication interacts with this partisan bias, and the partisan bias is absent among the more politically sophisticated.
Hypotheses
Considering the prominence that MFT has gained in social psychology, it seems surprising that political scientists have not used it yet to try to explain voters’ responses to moral violations by politicians. Certainly, moral violations occur, and voters historically have seemed to care about them, even if responses might be tempered for one’s own party. While there is evidence that partisans on different sides of the aisle see different moral foundations as salient (Haidt & Graham, 2011), examining all five foundations should let us get a better understanding of how voters respond to their violations and in particular, the extent of negative emotions generated by violations. Thus, the literature we have reviewed above leads us to propose the following four hypotheses:H1 (Partisanship and Negative Emotions Hypothesis): Across parties, respondents will have negative emotional responses to politicians committing moral violations, all else equal. But based on work by Haidt and Graham (2011), Democrats (typically liberals) will show stronger negative emotions in response to violations of care and fairness specifically, compared to Republicans. Given no prior evidence of partisan effects, we do not have specific expectations about partisan responses to the other three foundations: loyalty, authority, and sanctity.This leads to a testable hypothesis: Respondents will express a lower level of negativity toward co‐partisans violating a given foundation, compared to a nonpartisan or other party actor, at all levels of moral values strength. That is, even though voters with stronger moral values should be more negative to violations of the corresponding moral foundation (H2), partisan‐motivated reasoning should moderate these effects. However, for a nonpartisan actor, respondents who more strongly support a given moral value will be more negative about its violation than those for whom the value is less important.
H2 (Moral Values Hypothesis): Negative emotional responses to violations of moral foundations by politicians will be conditioned on voters’ own endorsements of particular moral values. The more that respondents endorse a particular moral value, the stronger their negative emotional response will be when a politician violates that particular moral foundation.
H3 (Partisanship Interaction Hypothesis): Partisan respondents will be less negative about violations of moral foundations by politicians of their own party, compared to violations by out‐party and nonpartisan politicians committing the same violation.
H4 (Moral Values by Partisanship Interaction Hypothesis): Moral foundations are thought to be based on innate, evolutionarily developed intuitive ethics, where “moral judgment is caused by quick moral intuitions” (Haidt, 2001, p. 817). At the same time, in politics, we know that partisanship acts in many ways as a perceptual screen (Campbell et al., 1960), conditioning how voters respond to partisan information. Thus, when partisanship is not invoked in a moral foundation violation, we expect the strength of a given moral value to drive emotional response to it. However, when the actor is a partisan and so is the voter, we expect that partisan preference will moderate these effects.
Discussion and Conclusions
This study set out to answer three questions, namely (1) How do American voters respond emotionally to violations of moral foundations by politicians? (2) Are voters’ emotional responses conditioned by their own moral values? and (3) Does partisanship minimize the effects of violations of moral foundations by politicians of the voter’s own party compared to the other party? We find that in general voters respond with negative emotions to politicians’ moral violations. However, not all voters respond in the same manner; we find that Democrats tend to respond more negatively to this set of moral violations than do Republicans. We might speculate that the political environment in which our study was done could have played a role in this unexpected result. As we detailed at the beginning of the article, there have been many accusations of moral violations by President Trump, none of which seem to shake his core Republican supporters. One impact of this may have been to lessen Republican voters’ sensitivity to moral violations by politicians more generally. Unfortunately, we have no way to test this speculation. We do find that voters’ responses to these moral violations can be sometimes conditioned by their own moral values, but they are more so by their partisanship when partisan actors are involved. Partisans of both parties express more negative emotions when a politician of the other party violates moral foundations.While we do not have a direct test of the mechanism by which partisanship conditions the effects of moral violations on emotional responses to politicians, a lengthy literature on partisanship in American politics makes clear that partisans see the political world through a very specific perceptual screen (Campbell et al., 1960). Motivated reasoning (Lodge & Taber, 2013; Redlawsk, 2002) likely becomes engaged when a voter sees a copartisan politician violating a moral foundation, leading to biased processing of the event, and the reduction of negativity about the event. But when the other party commits the violation, partisans are more than willing to express negative emotions about the event. Brain imaging studies reinforce the potential of this mechanism as distinct differences are seen between Democrats and Republicans in their processing of political information (Schreiber et al., 2013). Note that while we started this article with a brief discussion about moral violations by U.S. President Trump and his seeming imperviousness to them, it is worth recalling that it is generally only his Republican supporters who accept his behavior.
This study contributes to the literature in various ways. First of all, it is among a handful studies (Halmburger et al., 2012; Jiang et al., 2011) to study emotional responses to moral violations. A follow‐up study will examine the specific negative emotions to see whether these moral violations evoke specific discrete emotions, in particular so‐called moral emotions (Haidt, 2003). However, our main interest here is to see how partisanship and the importance of moral values for the voter affect emotional responses more generally.
Second, this study is the first to assess the role of voters’ moral values in their response to moral transgressions, as the results show they do matter. However, partisanship, more often than not, overrides the effects of moral values. This is a very interesting finding and suggests that moral foundations are maybe not as innate and foundational as might be supposed (see also, Connors [2019] on political values). The partisanship effect in this study is asymmetrical, showing that voters judge the opposing candidate more harshly for moral transgressions than their own candidate. This is in line with the trend of negative partisanship in American politics (Mason, 2018). Research has shown that while the feelings Democrats and Republicans have about their own party have not changed, their feelings about the opposing party have become much more negative (Abramowitz & Webster, 2016).
As with any research, this study is not without its shortcomings, one being the time frame in which it was conducted, namely following the 2016 presidential elections, which led to the election of a politician with frequent moral transgressions. It is not unthinkable that in a different time period we might find differences with respect to the strength of partisan responses to violations of moral foundations. Thus, we must consider that aspect of our results to be conditional, warranting further study in a different context.
Another limitation is that the vignettes used were specific. That is, the politician referred to in a vignette took a specific action. There is probably heterogeneity in people’s responses to these actions, and by the necessity of the research design, each study participant saw only one action representing one moral foundation. It is possible, for example, that a different vignette representing the same foundation might have a different impact on participants’ emotions. However, we are less interested here in the specific reactions to specific vignettes than we are in the larger story, that moral foundations appear to be readily ignored in the face of partisan actors. Across all of the vignettes we use, partisan voters were far less negative about a same‐party actor violating a foundation than they were an opposite‐party actor. At the same time, although extensively pretested, the authority vignette had the lowest homogeneity coefficient and resulted in the weakest findings. Apparently American voters did not find that specific example to be compelling.
Finally, as described in Footnote 2, new research by Montgomery et al. (2018) suggests that appropriate care must be taken in measuring moderating variables in an experimental context. We were concerned that measuring our moderators—partisanship and moral values—before the experimental treatment would prime participants as to the purpose of our study and thus influence their responses to the treatment. Thus, we measured them at the end of the study. While the very small shared variance we report between the moderators and treatment provides some confidence that our results are not biased, future studies should consider ways to separate these measures, such as the use of multiple waves. If the work by Montgomery et al. (2018) is sustained through additional research, experimentalists in general will need to consider whether the potential costs of such strategies outweigh the risks of biasing results by measuring moderators after an experimental treatment.
While recognizing the potential bias suggested by Montgomery et al. (2018) may be present in our analyses, notwithstanding the very small shared variance between our measures, any such bias would matter more if we were making inferences about the direct effects of specific coefficients in our models. But, instead, we are more interested in the patterns that we see in the data when different moral foundations are engaged across partisan voters. To the extent that these patterns of differential response by partisan voters and those who more or less adopt the moral values of the foundation are biased, we would not expect the bias to eliminate the differences we see across groups. Thus, while the effects of any given treatment may be more or less than we find here, we expect any bias would be unidirectional across the treatments, and thus the patterns we find would remain.
Notwithstanding these limitations, this study makes a significant contribution to the moral foundations literature. For the first time, we examine the intersection of partisanship and moral foundations and find that, as with so many other things in American politics in the early twenty‐first century, responses to moral violations by politicians are subject to partisan preferences. This holds even when voters themselves feel strongly about a given moral foundation. Put simply, when the effects of partisanship and strength of support for moral values are tested against each other in predicting emotional responses to violations of moral foundations, partisanship usually comes out the winner. This provides new insight into the role of moral violations in politics and helps us understand perhaps why some American politicians are able to continue to receive strong support from their own party voters even after violating what are thought to be basic moral values.
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