Educating the Public on Evidence-based methods for improving inter-group civility.

How to Make Real Progress Against Trump’s Incivility

I haven’t written much about Trump, who has taken “incivility” to new heights this election season, in part because there is no trumpevidence that telling large groups of people to be more civil has any value.  There is both anecdotal evidence and research that suggests forcefully telling people to be more civil will backfire.  Incivility and conflict involving large groups of people tends to be a function of a situational dynamic – two groups competing for a goal or a scarce resource like victory in a game or an election – that trumps any direct commandment to be more civil.  The rise of Trump as a political force is an opportunity for us to practice what we preach at Civil Politics and try to understand the dynamics that give rise to the conflict we see, in the hopes of cutting it off at its source.  As has been written in other places, Trump is a symptom, not a cause, and we are likely to see others follow in his footsteps whether he is elected or not.  If we really want a better political dialogue, we need to understand the root causes of Trump’s appeal.

It helps to start with the empirical fact that there are very few truly evil people in the world.  Human beings are uniquely social creatures who survived and thrived by being able to cooperate with hundreds of thousands of others, such that only ~1% of us are “psychopaths” who actually don’t care about others.  A human being who doesn’t care about others is akin to a bee that doesn’t care about his hive.  It’s rare.  The rest of us really do care about others beyond ourselves and try to do what we think is right, even if we sometimes do what others would think of as “evil” as a result.  That definition of “right” may include violence, theft, and incivility in the name of a moral cause (see research on idealistic evilthe dark side of moral conviction or terrorism and sacred values), but there is a moral cause behind most people’s actions, even when we disagree with those actions.

Trump supporters have many moral motivations that many who disagree with him would recognize and value.

– They worry about the lack of jobs for hard-working, but under educated Americans.
– They fear that the system of lobbyists and special interests is stacked against them.
– They think that politicians cannot be trusted to fight for everyday Americans, due to their reliance on donors who line their pockets.
– They feel that their identity and their ability to express their opinions is under attack.

Indeed, many of these positions are emphasized by Bernie Sanders, which is why you sometimes see people who support Trump and Sanders both.  Calling Trump supporters racist, stupid or naive is not only a misleading caricature, but also a recipe for only exacerbating the coarsening conflict that we are trying to avoid, as it drives each side into its corner.  If we want things to get better, research suggests that we have to start from a place of common goals and develop a positive relationship with Trump fans rather than having convincing them why they are wrong as our ultimate goal.  Staging violent protests at Trump’s rallys is the opposite of this.  How can we instead reduce the divisions, rather than inflame them?

Let us acknowledge that we need to do something to help people who want to work hard but are being left behind by an increasingly global and technological economy.  Let us acknowledge that lobbyists and donors have undue influence and work to curb that influence, whether it be through campaign finance or a simpler government with fewer rules to be gamed.  Let us all accept that we want a society where no identity, American or immigrant, religious or atheist, urban or rural, feels threatened and unable to express their opinions freely, and work to make relationships across these divides.  And let us accept that whatever we think of Donald Trump as a person, his supporters are generally ordinary Americans who care deeply about their kids and their communities.  Let’s help them with their concerns as it makes no sense to be someone who cares deeply about poor Americans who simultaneously denigrates many in that group, who happen to support a candidate they disagree with.

To be clear, I do not support Trump or his rhetoric which is deeply uncivil and divisive.  But those who are demonizing Trump’s supporters and disrupting his events are only exacerbating the problem.  As Martin Luther King Jr. once said, “Hate cannot drive out hate: only love can do that” and there is ample research that suggests that forging positive empathic relationships across divisions is indeed the only way to truly heal a great moral divide.

– Ravi Iyer

Ravi Iyer has a Ph.D in psychology from the University of Southern California and has published dozens of articles on political and moral attitudes.  He works as a data scientist at Ranker and is also the Executive Director of Civil Politics, a non-profit that promotes evidence based methods for healing inter-group divisions.
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Love thy neighbor: Ingroups, outgroups and collaboration possibilities

Context: Research on intergroup conflict is well supported and grounded in implementing collaboration. However, despite this data, conflict continues to grow and develop. In the present research, Waytz, Young, and Ginges (2014) provide context as to why individuals and their respective group associations may fail to respect peace-promoting findings through an analysis of “motive attribution asymmetry.” Motive attribution symmetry is an assumption-based pattern that involves ingroup vs. outgroup tendencies to respond with either biased ingroup-love or outgroup-hate assumptions.
Waytz et al. (2014) hypothesize that people will “attribute ingroup engagement in conflict to love more than hate…. but [also] attribute outgroup engagement in conflict to hate more than love” (p. 15687) Within five separate studies, Waytz et al. (2014) utilize several distinct intergroup conflicts, violent and non-violent, aiming to understand individuals’ innate sense of ingroup and outgroup motives and subsequent intergroup assumptions.

 Study 2 and Study 3 outline continuing information found in study one: individuals tend to support the motive attribution asymmetry pattern and generally form internal biases that follow outgorup-hate assumptions and ingroup-love assessments.

 

Study 5: Incentivizing Accuracy
1. What They Did – Intervention Summary:
The motive attribution symmetry pattern is not only negative (i.e. hate assumptions) but also inhibiting compromise. Waytz et al. wanted to see what may curb its effect and thus improve likelihood of cooperation.
In this study, 331 American democrat and republican residents participated by completing an online study similar to study 1. Those who answered with a secure political ideology were then asked if they felt their party was motivated by various items. Items ranged from love (empathy for others in your own party) to hate (dislike of opposing party members). Participants were then randomly placed into either an incentive experimental group or a control group. Both were told to guess the motivations of the opposing political party, however those in the incentive group were given the notion of earning 12 extra dollars if they estimated correctly. The questions asked were the same asked prior, but now about the opposing party, be it republican or democrat. Lastly, each condition rated how much the would be willing to negotiated with an opposing party.

 2. What They Found – Results:
Researchers were excited to find that when provided incentive, the experimental group diminished motivational attributions of hate and increased the motivational attribution of love for outrgroups. Thus, the pattern seen through the motive attribution symmetry in the previous four studies is derailed and actually reversed when individuals are presented incentives. Incentive was found to increase optimism in terms of the conflict, and thus could open doors towards future agreements and compromises.
However, despite this exciting discovery, Waytz et al. suggest that these findings were in a context less violent and volatile than those in other intergroup contexts.

Screen Shot 2014-12-02 at 10.30.01 PM
Green – Attribution of hate to opposing party
Blue – Attribution of love to opposing party

 

 3. Who Was Studied – Sample:
331 American democrats and republicans; 223 male, 106 female, 2 unreported

4. Study Name:
Waytz et al., 2014, Study 5

 5. Citation:
Waytz, A., Young, L. L., & Ginges, J. (2014). Motive attribution asymmetry for love vs. hate drives        intractable conflict. Proceedings of the National Academy of Sciences, 111(44), 15687-15692.     doi:10.1073/pnas.1414146111

6. Link:
http://www.pnas.org/content/111/44/15687.abstract

7. Intervention categories:
Intergroup Conflict, Ingroup love, Outgroup hate, Attribution, Cognitive bias, Political ideology, Politics, Republican, Democrat, 2014

8. Sample size:
331

9. Central Reported Statistic:
“Most importantly, a significant condition × target × motive interaction [F(1, 329) = 42.05, P = 0.001, η2P = 0.11] (all other effects, P > 0.39)”

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Political Partisanship Without the Politics

Polarization of American partisans continues to increase.  Liberals and conservatives alike have obvious contempt for opposing partisans — this is universally demonstrated by implicit, explicit and behavioral indicators.  Shanto Iyengar and Sean Westood of Stanford University and Princeton University, respectively, designed a set of four studies — titled “Fear and Loathing Across Party Lines: New Evidence on Group Polarization” to further investigate political dichotomy in America.

1. What They Did – Intervention Summary:

Study participants completed selection tasks.  Each participant was randomly assigned to one of two tasks that modeled existing scholarship assessments.

Participants in the first task had to choose to give a scholarship to either a Democrat or Republican high schooler.   Those in the second task had to choose between a European American and an African American candidate.  The academic and extracurricular achievements of each candidate were randomly varied, which allowed the study to measure the effects of partisan and racial bias without qualification confounds and compare the relative strength of in-group preference.

2. What They Found – Results:

Despite the lack of direct political connection, this study found that the party cue had the biggest impact on candidate selection.  Approximately 80% of participants, Democrats and Republicans alike, who participated in the partisan design selection chose the candidate who identified with their own party – even when the candidate from the opposing party was more highly qualified.  There was no evidence that those who participated in the partisan design took academic achievement into account.

Participants assigned to the race design selection showed relatively weak effects of in-group bias and tended to select candidates based on qualification instead of race.

3. Who Was Studied – Sample:

SSI

4. Study Name:

Iyengar and Westwood et al. 2014, Study 2

5. Citation:

Iyengar, Shanto & Westwood, Sean J. (2014).  Fear and loathing across party lines: New evidence on group polarization. http://pcl.stanford.edu/research/2014/iyengar-ajps-group-polarization.pdf

6. Link:

http://pcl.stanford.edu/research/2014/iyengar-ajps-group-polarization.pdf

7. Intervention Categories:

Perspective

8. Sample Size:

1,021

9. Central Reported Statistic:

“Democrats were more likely to select a fellow Democrat (b=1.04, p<.01) and Republicans were more likely to select a fellow Republican (b=1.60, p<.001).”

10. Effect Size:

The probability of a partisan selecting an out-party candidate never rose above .3.

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How Deeply Ingrained in our Heads is Partisan Affect?

Polarization of American partisans continues to increase.  Liberals and conservatives alike have obvious contempt for opposing partisans — this is universally demonstrated by implicit, explicit and behavioral indicators.  Shanto Iyengar and Sean Westood of Stanford University and Princeton University, respectively, designed a set of four studies — titled “Fear and Loathing Across Party Lines: New Evidence on Group Polarization” to further investigate political dichotomy in America.

1. What They Did – Intervention Summary:

Study 1 assessed implicit partisan affect and anchored it to implicit racial affect. used two different brief versions of the Implicit Association Test (IAT) to measure implicit racial affect and implicit partisan affect.

Participants first completed four rounds of a BIAT created by the researchers to measure their implicit attitudes.  Their “D-scores” were calculated by subtracting their mean response times when pairing a Democratic mascot with “good”.  Positive D-scores (between 0 and 2) indicated greater positive affect for Republicans and inverse responses times indicated greater positive affect for Democrats.

To further validate the tests, the relationship between partisan D-score and a difference in feeling (regarding Democrats and Republicans) thermometer test was examined.

Finally, participants’ scores on the partisan BIAT and the race BIAT were compared.

2. What They Found – Results:

As was expected, they found that partisan D-scores corresponded closely with which party a participant self-identified with.  “Strong Republicans”, for example, produced the most bias in favor of Republicans.

The thermometer test validation, despite a small amount of divergence, correlated strongly (r=.418) with the D-scores.

Racial affect BIATs showed a substantial black-white implicit bias, but the race effect size was not nearly as strong as the party effect size.  When compared to party BIATs, it was discovered that negative associations of opposing parties are faster which, in this case, means more automatic and/or stronger, than negative associations of African Americans.

This tells us that, since racial identity is, obviously, acquired at or before birth and racial attitudes are deeply ingrained, for partisanship to exceed race, its underlying hostility must be immense.

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3. Who Was Studied – Sample:

SSI

*In order to capture racial affect among non-whites, African Americans were oversampled.

4. Study Name:

Iyenger and Westwood et al. 2014, Study 1

5. Citation:

Iyengar, Shanto & Westwood, Sean J. (2014).  Fear and loathing across party lines: New evidence on group polarization. http://pcl.stanford.edu/research/2014/iyengar-ajps-group-polarization.pdf

6. Link:

http://pcl.stanford.edu/research/2014/iyengar-ajps-group-polarization.pdf

7. Intervention Categories:

Observation

8. Sample Size:

2,000

9. Central Reported Statistic:

“The spread between Democrats and Republicans on the partisan D-score was massive… (p<.001).”

10. Effect Size

D(Republican) = .27, D(Democrat) = -.23

 

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Our goal is to educate the public about social science research on improving inter-group relations across moral divides.