Category Archives: Prejudice and discrimination

Implicit Bias Against Atheists?

Cognitive psychology, Prejudice and discrimination, Religion, ,

Consider the following problem:

Linda is 31 years old, single, outspoken and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

Which alternative is more probable?

A. Linda is a bank teller.

B. Linda is a bank teller and is active in the feminist movement.

“A” is the correct answer. Since there are undoubtedly some bank tellers who are not feminists, “B” cannot be more probable than “A”. To answer “B” is to commit a conjunction fallacy, since the conjunction of two events (bank teller and feminist) cannot be more probable than one of them (bank teller) alone. We commit this error because we associate the other qualities mentioned in the description with being a feminist.

Will Gervais of the University of Kentucky and his colleagues used the conjunction fallacy to measure what they call “extreme intuitive moral prejudice against atheists.” Participants were 3,256 people from the United States and 12 other countries. (See the chart below for the countries). They read a description of a man who tortured animals as a child. As an adult, he engaged in several acts of violence, ending with the murder and mutilation of five homeless people. Half the participants from each country were asked:

Which alternative is more probable?

A. He is a teacher.

B. He is a teacher who is a religious believer.

The other participants were asked:

Which alternative is more probable?

A. He is a teacher.

B. He is a teacher who does not believe in god(s).

“B” is always the wrong answer, but the authors infer that if more people give this incorrect answer when the target is described as not believing in a god than when he is described as a religious believer, then the participants are (collectively) biased against atheists. Presumably, the respondents believe serial murderers are more likely to be atheists than religious people. Here are the results.

The chart shows the probability of a participant answering “B” when the target is an atheist compared to when he is religious, while statistically controlling for the participant’s gender, age, socioeconomic status and belief in god(s). There was bias against atheists in 12 of the 13 countries, the exception being Finland. Overall, people are about twice as likely to commit the conjunction fallacy when the target is described as an atheist (61%) than when he is described as religious (28%).

What is the effect of the respondents’ own belief in god(s) on answers to these questions? In the chart above, the individual’s certainty of the existence of a god increases from left to right. People at all levels of religious belief show prejudice against atheists, including atheists themselves—that is, people at the left who answered that the probability of a god’s existence is zero.

The authors did several followup studies. Using the same research method, they found that:

  • People are more likely to assume that a person who does not believe in god(s) is a serial murderer than a person who does not believe in evolution, the accuracy of horoscopes, the safety of vaccines, or the reality of global warming.
  • People are more likely to assume that a priest described as having molested young boys for decades is a priest who does not believe in god than a priest who does believe in god.

The assumption that morality depends on religious belief seems to be quite widespread, since it was obtained in religiously diverse cultures, including Christian, Buddhist, Hindu and Muslim societies. This association between atheism and bad behavior is all the more impressive given the lack of empirical evidence for a moral effect of religious beliefs.

On the other hand, 28% of the respondents who were given that choice saw the target as more likely to be a murderer if he was described as a religious believer than when his religiosity was not specified. This suggests that a minority of respondents associate religiosity with violence.

The authors describe their results as demonstrating an “intuitive” prejudice against atheists. They don’t indicate whether an intuitive belief operates consciously or without conscious intention. However, this prejudice seems to have some of the characteristics of an unconscious or implicit bias. It was measured using a fairly subtle technique. Participants were never asked to directly compare atheists with religious believers (although when the target was described as just a teacher, participants may have made the default assumption that he was religious). Furthermore, it is a bias shared by atheists themselves, suggesting that participants are repeating a popular cultural assumption, rather than reporting a belief that they have thoughtfully considered.

You may also be interested in reading:

The Implicit Association Test: Racial Bias on Cruise Control

Teaching Bias, Part 1

A Darker Side of Politics

Jim Crow Policing

Politics, Prejudice and discrimination, ,

The nonstop humiliation of young black and Hispanic New Yorkers, including children, by police officers who feel no obligation to treat them fairly or with any respect at all is an abomination. . . Rather than a legitimate crime-fighting tool, these stops are a despicable racially oriented tool of harassment.

Bob Herbert

Bob Herbert’s angry 2010 essay, “Jim Crow Policing,” was critical of the stop-and-frisk policy of the New York Police Department (NYPD), but it could just as easily have been directed at their differential enforcement of marijuana laws.

Surveys show that Blacks and Whites use illegal drugs at similar rates. Surveys conducted by the U. S. Department of Health and Human Services show that both lifetime marijuana use and use in the past year is slightly higher for Whites than for Blacks and Latinos. Yet Blacks and Latinos are arrested and incarcerated much more frequently.

In 2013, when Bill de Blasio was running for mayor of New York City, he promised to reduce the frequency with which citizens were arrested for low-level marijuana possession and the racial bias in these arrests, referring to such policies as “unjust and wrong.” He has been mayor since January 2014, so how is he doing? The Drug Policy Alliance (DPA) recently published an assessment by Harry Levine, a sociologist at Queens College, CUNY, and Loren Siegel, an attorney.

On the positive side, the number of arrests for marijuana possession has gone down from about 40,000 per year to about 20,000 per year, as the chart below shows. In other words, it now takes Mayor de Blasio and the NYPD two years to make as many “unjust and wrong” arrests as his two immediate predecessors averaged in a single year.

However, there is no evidence of any reduction in racial bias. Blacks and Hispanics account for 51% of the population of New York City, with Whites accounting for most of the remaining 49%. Yet Blacks and Hispanics account for 86% of those arrested for marijuana possession and these percentages are unchanged from the Bloomberg administration.

Black and Hispanic defendants are also convicted at higher rates, although this does not necessarily imply racial discrimination by the prosecution or the courts. It may be due to their having a greater number of prior offenses.

The persistence of racial discrimination in marijuana arrests seems to be due to a combination of institutional and individual racism. Levine and Siegel suggest that two processes are at work in producing these racial disparities. First, NYPD concentrates its enforcement of marijuana possession laws in public housing projects and neighborhoods in which Blacks and Latinos make up the majority of residents. Public housing residents are 5% of the city’s population but account for 21% of marijuana arrests, with 92% of those arrested being Black or Hispanic. The city’s 37 majority Black or Hispanic precincts have about half the city’s population, but account for 66% of marijuana arrests, with 92% of those arrested being Black or Hispanic. Since the police usually base their decisions of where to deploy officers on prior arrest records, differential patrolling of Black and Hispanic areas is a type of self-perpetuating institutional bias.

The higher conviction rates of Black and Latino defendants noted above, if they are due to their prior arrest records, can also be seen as self-perpetuating institutional racism.

Secondly, NYPD also targets commercial and night life districts in mid- and lower Manhattan which attract out-of-town visitors and tourists, such as Greenwich Village, perhaps out of concern for the city’s public image. Blacks and Latinos make up relatively few of the residents of these areas, but are arrested at disproportionately high rates. In an analysis of 15 such areas, the authors report that Blacks and Hispanics were 23% of the population but 72% of those arrested. The fact that Blacks and Hispanics are in the minority in these areas suggests that their higher arrest rate is due to racial bias by individual police officers.

It’s not clear whether this lack of progress in eliminating discrimination is due to Mayor de Blasio’s lack of commitment to his campaign rhetoric or NYPD’s refusal to comply with his orders. If the latter, why was NYPD was willing to cut back on marijuana arrests but not willing to cease its racial discrimination?

Mayor de Blasio released a statement criticizing the DPA study as “misleading.” Rather than challenging their data, he reframed it. He pointed out that the absolute number of Blacks and Latinos arrested for possession of marijuana had gone down under his administration, but he failed to mention that the percentages by race were unchanged. He also attacked the DPA as “a group committed to legalization,” which is irrelevant.

A marijuana arrest can interfere with a young person’s ability to get a job, go to college, take out a loan, or even find a place to live. There is no evidence that eliminating these arrests has any negative impact on public safety. In fact, there seems to be widespread public support for legalization of marijuana, and there is no justification for racially discriminatory marijuana enforcement. Yet NYPD seems to have considerable ability to resist these policy changes.

You may also be interested in reading:

In Perspective

Racial Profiling in Preschool

Making a Mockery of the Batson Rule

Why “Bad Dudes” Look So Bad

Prejudice and discrimination, Social psychology, ,

A 2016 Washington Post analysis showed that Black Americans are 2.5 times as likely to be shot and killed by police officers than White Americans, and that unarmed Blacks are 5 times as likely to be shot dead than unarmed Whites. While there are many explanations for this finding, there is little support for the knee-jerk conservative response that attributes this racial disparity to the fact that Blacks commit more crimes. An analysis of the U. S. Police Shooting Database at the county level found no relationship between the racial bias in police shootings and either the overall crime rate or the race-specific crime rate. Thus, this racial bias is not explainable as a response to local crime rates.

When police officers shoot an unarmed Black teenager or adult, they are not likely to be convicted or even prosecuted if they claim to have felt themselves threatened by the victim. This suggests that it’s important to look at factors that affect whether police officers feel threatened. A study by Phillip Goff and others found that participants overestimated the ages of teenaged Black boys by 4.5 years compared to White or Latino boys, and rated them as less innocent than White or Latino boys when they committed identical crimes. While age may be related to perceived threat, the present study by John Paul Wilson of Montclair State University and his colleagues is more relevant, since it looks at the relationship between race and the perceived physical size and strength of young men.

The researchers were extremely thorough. They conducted seven studies involving over 950 online participants. Unless otherwise specified, participants were shown color facial photographs of 45 Black and 45 White high school football players who were balanced for overall height and weight. In the first study, the Black athletes were judged to be taller and heavier than the White athletes. Furthermore, when asked to match each photo with one of the bodies shown below, they judged the young Black men to be more muscular, or, as they put it, more “formidable.”

In a second study, participants were asked to imagine that they were in a fight with the person in the photograph, and were asked how capable he would be of physically harming them. The young Black men were seen as capable of inflicting greater harm.

In the third study, the authors examined the possibility that racial prejudice might predict these physical size and harm judgments. A fairly obvious measure of prejudice was used. Participants were asked to complete “feeling thermometers” indicating their favorability toward White and Black people. This measure of prejudice was only weakly associated with the participants’ judgments of Black-White differences in harm capability and not at all with Black-White differences in harm perception.

Up to this point, Black participants were excluded. However, the fourth study compared Black and White participants. Both Blacks and Whites saw the young Black men as more muscular, though the effect was larger for Whites. Only White participants saw the Black men as more capable of inflicting harm. Apparently Black participants subscribe the the size stereotype, but not to the stereotype about threat.

The fifth study was an attempt to apply these results to the dilemmas faced by police officers. Once again, both Blacks and Whites participated. They were asked to imagine that the young men in the photographs had behaved aggressively but were unarmed. How appropriate would it have been for the police to use force? White participants saw the police as more justified in using force against the young Black men than against the young White men. For the Black participants, there was no difference.

Previous research had shown that Black men who have an Afrocentric appearance—that is, who have dark skin and facial structures typical of African-Americans—are treated differently than Black men who are less prototypical. For example, in a laboratory simulation, participants are more likely to “shoot” a Black man if he has Afrocentric features, and a Black man convicted of murder is more likely to be sentenced to death if he is prototypical. The sixth study showed that young Black men whose facial features are prototypical are seen as more formidable and the police are seen as more justified in using force against them. Furthermore, this is true even when participants are shown photos of young White men. That is, White men with darker skin and facial features resembling Black men are seen as more muscular than other White men, and participants believe the police are more justified in using force against them.

In the final study, participants were shown the exact same photographs of men’s bodies with the head cropped off, but they were given additional information indicating the man was either White or Black. The photos were color-inverted to make the man’s race difficult to detect. The man’s race was indicated either by a Black or White face said to be the man in the photo, or a stereotypically Black or White first name. Results indicated that the very same bodies were seen as taller and heavier when the man was presumed to be Black than when he was presumed to be White.

You might be wondering whether Black and White men actually differ in size. Data from the Center for Disease Control shows that the average Black and White male has exactly the same weight, and that Whites are on average 1 cm taller. Therefore, when participants see Black men as larger, they are not generalizing from their real world experience.

These studies are important in explaining why police officers feel more threatened by young Black men than young White men, and why jurors are more likely to see the killing of young Blacks as justified. It may help to explain why no charges were brought against a Milwaukee police officer who shot Dontre Hamilton 14 times. The officer described Hamilton as “muscular” and “most definitely would have overpowered me or pretty much any officer I can think of.” Hamilton was 5’7” and weighed 169 lbs.

It is important to realize that the results of these studies are not readily explained by conscious race prejudice. This size estimation bias is probably automatic and unconscious, and is most likely to affect behavior when a police officer must make a split-second decision. The fact that officers are likely to be found not guilty of using excessive force against a Black victim if they testify that they felt threatened is troubling, since it suggests that implicit racial bias can be used successfully as a defense when charged with a violent crime.

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Publicizing “Bad Dudes”

Teaching Bias, Part 1

Making a Mockery of the Batson Rule

Publicizing “Bad Dudes”

Cognitive psychology, Politics, Prejudice and discrimination, , ,

The other day in California, last week, a woman, 66 years old, a veteran was killed, raped, sodomized, tortured and killed by an illegal immigrant. We have to do it! We have to do something! We have to do something!

Presidential candidate Donald Trump

Judgmental heuristics are the simple rules or mental shortcuts that people use to make decisions quickly and efficiently. One of those rules is the availability heuristic, which states that the frequency of an object or event is judged on the basis of the number of instances retrieved from memory and the ease with which they come to mind. The easier it is to think of examples, the more frequent the object or event is assumed to be.

The availability heuristic often leads to correct inferences. In the northeastern United States, robins are in fact more common than other birds. But availability can be misleading. For example, when estimating the frequency of various causes of death, people overstimate dramatic events such as homicides and traffic accidents and underestimate less public illnesses such as strokes and diabetes. The presumed explanation is media salience. Estimates of the frequency of causes of death are highly correlated with space devoted to types of death in recent newspapers.

The availability heuristic is one explanation for for a common cognitive error known as the base-rate fallacy. This refers to a tendency to overgeneralize from individual examples while ignoring statistical base rates. A specific case is more emotionally interesting and easier to remember; it is more available. A statistical statement is not as interesting. Base rates are usually underweighted, and sometimes completely disregarded, especially when specific instances are available. It follows that if propagandists want people to overestimate the frequency of an event, they should publicize examples of that event, preferably with vivid pictures and lots of memorable details.

Availability biases can influence social policy. An availability cascade is a self-sustaining chain of events that starts with a small number of cases that are heavily publicized by the media, leading to public panic and large-scale government action. One goal of terrorism is to start availability cascades. An availability campaign occurs when some pressure group, for altruistic or self-interested reasons, tries to instigate an availability cascade.

I was reminded of this by last Tuesday night’s address to Congress when President Trump introduced four alleged victims of crimes committed by immigrants who were seated in the audience and announced an executive order creating an office called Victims of Immigration Crime Engagement (VOICE) within the Department of Homeland Security, whose purpose is to make public “a comprehensive list of criminal actions committed by aliens.” (He didn’t say that the “aliens” had to be in the country illegally.) Right-wing news organizations have been heavily reporting real or fake crimes committed by immigrants for several years.

Apparently the President thinks that one way to increase support for his immigration policies—the wall along the Mexican border, mass deportations, the Muslim ban—is to induce Americans to overestimate the frequency of crimes committed by immigrants. To this end, he is starting an availability campaign.

What is the actual base rate of crimes by immigrants? Research consistently shows that immigrants commit crimes at a lower rate than native-born Americans. Robert Adelman and his colleagues analyzed data from 200 metropolitan areas from 1970 to 2010. They found that as immigration increased, rates of murder, robbery, burglary and larceny decreased, and rates of aggravated assault remained the same.

In a forthcoming study, Charles Kubrin and Graham Ousey conducted a meta-analysis combining the results of over 50 studies examing the relationship between immigration and crime published between 1994 and 2014. Their conclusion: “More immigration equals less crime.” However, the rate of crime by second generation immigrants–that is, the children of immigrants–does not differ from than of other Americans.

Kristin Butcher and Anne Piehl studied why immigrants commit crime at lower rates than non-immigrants. They concluded that people who self-select to immigrate to the U. S. are less criminally active than the native born population, and are more responsive to deterrents to crime, such as the threat of a jail sentence.

This is not the only instance in which the president has presented misleading information apparently intended to persuade us that the exception is the norm. He has criticized the media for “underreporting” acts of terrorism by Muslims, when in fact the opposite is the case. In last week’s address, he cited an unrepresentative 116% increase in health insurance premiums in Arizona to support his claim that the Affordable Care Act was failing.

Anti-Semitic Nazi propaganda, 1937.

Trump’s behavior is a classic example of scapegoating. Scapegoating refers to the singling out of an individual or group for blame that is not deserved. Scapegoating is presumed to be responsible for the increase in prejudice and violence toward already stigmatized minority groups during economic hard times.

Until 1938, it was the policy of Hitler’s Ministry of Justice to forward all criminal indictments of Jews to the press office to be publicized. With VOICE, the U. S. now has its own government-run ministry of propaganda given the mission of convincing us of something that isn’t true—that immigrants commit more crimes than native born Americans.

You may also be interested in reading:

So Far, It Looks Like It Was the Racism

What Does a Welfare Recipient Look Like?

Trump’s Trump Card

Teaching Bias, Part 2

Prejudice and discrimination, Social psychology,

Before continuing, please read Part 1 of this article.

Since people are usually not aware of their nonverbal behavior, nonverbal bias is a common feature of everyday life. As a result, families and friends routinely teach children racial and ethnic preferences without intending to. These biases are also taught through the mass media. A 2009 series of studies by Max Weisbuch and his colleagues, done with college students, demonstrates the teaching of implicit racial bias by television.

These researchers recorded 90 10-sec segments from 11 popular television programs in which White characters interacted with either White or Black targets. The clips were edited to eliminate the soundtrack and to mask the White or Black target to whom the character was talking. Twenty-three judges rated how positively the targets were treated. The (unseen) White targets were perceived as being treated more favorably than the (unseen) Black targets. This study established the existence of nonverbal racial bias on television. It seems unlikely that the actors and directors of these programs were aware that they were transmitting bias. These 11 shows had an average weekly audience of 9 million people.

The remaining studies were designed to test whether nonverbal race bias affects the viewer. In the second study, the 11 programs in Study 1 were scored according to the amount of race bias in the clips. The participants were asked which of these programs they watched regularly. It was found that watchers of the more biased programs showed a greater preference for Whites on the Implicit Association Test (IAT), a standard measure of implicit racial bias. (See this previous post for an explanation of the IAT.)

Since this is a correlational study, it does not demonstrate that exposure to biased programs causes prejudiced attitudes. An alternative explanation is that viewers prefer TV programs that reinforce their pre-existing attitudes. The remaining two studies, however, were true experiments in which participants were randomly assigned to be exposed to different televised content.

In these two experiments, participants were shown one of two silent videos constructed from clips used in Study 1. The pro-White tape featured White targets receiving positive nonverbal signals and Black targets being treated more negatively. The pro-Black tape featured favorable treatment of Black targets and unfavorable treatment of Whites. The participants were then tested for implicit racial bias. In Study 3, the IAT was used as the measure of bias. As expected, those who had seen the pro-White video showed a greater preference for Whites than those who had seen the pro-Black video.

Study 4 involved a different measure of implicit racial bias, an affective priming task. This task measures whether subliminal exposure to photos of White and Black faces speeds up the recognition of positive or negative images. Subliminal means below the level of awareness. Photos are presented on a computer so quickly that they are not consciously perceived. Nevertheless, they influence behavior. The premise, well established through previous research, is that you respond more quickly to an image if it is preceded by another that elicits a similar emotional response. Therefore, if you are subliminally exposed to a photo of a liked person, you can recognize a positive object, i.e., a puppy, more quickly, while exposure to a disliked person allows you to identify a negative object, i.e., a rattlesnake, more quickly.

This experiment was strengthened by some additional controls not present in Study 3. In addition to pro-White and pro-Black videos, there was a race-neutral control video. Photos of White, Black and Asian-Americans were used as subliminal primes. The results are shown below.

A higher number on the vertical axis indicates a faster response to that prime. The people who had seen the pro-White video showed faster positive associations to White faces (compared to Black faces), while those who had seen the pro-Black video showed faster positive associations to Black faces (compared to White faces). The control video had the same effect on both Black and White associations. Asian faces had no priming effect.

The studies cited in these posts make it clear that we don’t have to be explicitly taught to like or dislike members of different racial or ethnic groups. Our social environment contains nonverbal cues which encourage the reproduction of prejudice and discrimination from one generation to the next.

You may also be interested in reading:

What Does a Welfare Recipient Look Like?

Racial Profiling in Preschool

A Darker Side of Politics

Teaching Bias, Part 1

Prejudice and discrimination, Social psychology,

You may be surprised to hear that White children show evidence of bias against African-Americans as early as age 3. How does this happen? Since there is evidence that the implicit biases of adults leak out through their nonverbal behavior, it seems reasonable that children pick up these cues from their parents and older acquaintances. A new study by Allison Skinner and her colleagues shows how exposure to positive or negative nonverbal cues can create social biases in preschool children. The studies are simple, but they are awkward to explain, so please bear with me.

In the first experiment, 67 4- and 5-year-old pre-school children watched a video in which two adult female actors each exhibited nonverbal bias toward two adult female targets. The targets were idenified by the colors of their shirts, red or black. Although the actors used exactly the same scripts when talking to the two targets, one target received positive nonverbal signals (i.e., smiling, warm tone of voice, leaning in) and the other received negative signals (scowling, cold tone, leaning away). Since these were two different women, the actual identity of the targets who received the warmer and colder treatment was counterbalanced; that is, each woman received positive and negative treatment an equal number of times over the course of the experiment.

After the video, the researchers gave the children four tasks designed to measure which target they preferred. The first was a simple preference question asking which woman they liked better. For the second, they were given an opportunity to behave prosocially. They were asked to which target the experimenter should give a toy. The two remaining tasks were opportunities to imitate one of the two targets. In the third task, they had to choose which of two labels to give to a toy which the two targets had called by different names. In the fourth, they had to choose one of two actions, ways to use a cone-shaped object, which the two targets had used differently.

The children showed a preference for the target who received the positive nonverbal treatment on three of the four tasks—all but the action imitation. A summary measure of the number of times out of four they showed favoritism toward the preferred target was statistically significant.

The researchers were less interested in demonstrating favoritism toward specific individuals than in the development of favoristism toward groups of people. In a second experiment, they measured whether the preferences demonstrated in Study 1 would generalize to other members of the target’s group. The two targets were introduced as members of the red group and the black group, matching the colors of their shirts. After the video, the children were given three tasks—preference, prosocial behavior and label imitation. The results replicated those of the first study.

Then the children were introduced to two new adult woman targets, said to be members of the red and black groups (wearing appropriate-colored shirts), who were best friends of the previous two women. They were asked which friend they liked better and were asked to imitate the actions of one of the two friends. The results showed greater liking for and more imitation of the friends of the preferred target on the video. In other words, the favoritism toward the preferred target (and against the non-preferred target) generalized to other members of their groups.

This study is a demonstration experiment. To prove that they understand how a widget works, researchers will show that they can create a widget in the laboratory. The widget in this case is group favoritism. We should not be put off by the fact that the groups are artificial, defined only by the colors of their shirts. Suppose the researchers had used members of real groups, such as White and African-American women, as their targets. In that case, the researchers would not have created group biases, since 4- and 5-year-olds already have racial attitudes. For evidence of how pre-existing attitudes can be strengthened or weakened by the way targets are treated, please read Part 2 of this post.

You may also be interested in reading:

What Does a Welfare Recipient Look Like?

Racial Profiling in Preschool

A Darker Side of Politics

In Perspective

Economics, Prejudice and discrimination

The corporate media seem to have accepted Donald Trump’s emphasis on the economic problems of working class Whites. This ignores the fact African-Americans experience more of these same stressors, as we are reminded in this video from the centrist think tank, the Brookings Institution.

None of these statistics–with the exception of the marijuana arrest rate–tell us whether the problems of Black Americans are a result of racial discrimination or some other cause. However, we can be fairly confident that when Whites experience the same difficulties, they are not a result of discrimination.

So Far, It Looks Like It Was the Racism

Politics, Prejudice and discrimination, Social psychology, , , ,

One question has dominated the conversation among political scientists attempting to explain the presidential election: Were Trump’s supporters motivated primarily by economic anxiety or racial resentment? So far, I’ve avoided weighing in on this question, hoping that the definitive study would appear. It hasn’t yet, but a new experiment by Michael Tesler is interesting enough to warrant giving you a progress report.

The corporate media narrative clearly favors the economic explanation. In a typical article, we are told (correctly) that the family incomes of working class families have been stagnant for 35 years, that trade agreements and the 2008 recession have caused widespread unemployment and underemployment, and that both political parties have ignored the plight of these Americans. This is followed by interviews with a couple of Trump supporters who express pain and anger over the way they have been treated. However, this is anecdotal evidence. The answers given by Trump supporters are partially driven by the questions they are asked. For the media, framing the election in terms of economic anxiety rather than racism avoids offending Trump and his supporters.

Much of the evidence available prior to the election failed to support the economic anxiety narrative. Surveys showed that racial attitudes predicted Trump support better than economic attitudes—for example, these two, and this one. This large sample Gallup poll also cast doubt on the economic explanation. The median household income of a Trump supporter in the primaries was $72,000, higher than the median income of Clinton supporters ($61,000) and the general population ($56,000). In addition, post-election analyses showed that Clinton received more votes in economically-distressed communities—those with a higher percentage of their population below the poverty line.

Michael Tesler has been studying the racialization of politics for over a decade. Racialization refers to the tendency of racial attitudes to influence opinions toward a variety of other issues not obviously related to race, such as health care or gay marriage. Tesler embedded an experiment within a YouGov/Huffington Post national survey of 1000 voters conducted on December 6 and 7. Half the participants were asked if they agreed with the following statement:

Over the past few years, Blacks have gotten less than they deserve.

Ths is an item from the Symbolic Racism Scale, which is used to measure racial resentment. The remaining respondents were presented with this statement.

Over the past few years, average Americans have gotten less than they deserve.

Most people assume an “average American” is White. In 2005, Devos and Banaji conducted a series of five studies showing that the category “American” is more strongly associated with the category “White” than either “African-American” or “Asian-American.” Based on this evidence, Tesler assumed that respondents would interpret the second statement as referring to Whites. He then compared the responses of people who reported that they had voted for Clinton and Trump to these two questions.

This study pits the economic anxiety and racial resentment explanations against one another. Would Trump voters be more likely than Clinton voters to agree that average Americans have gotten less than they deserve? Or would differences emerge only when the question referred to Black Americans?

The results on the left show a typical racial divide between Black and White respondents. White participants were more than twice as likely to think that average Americans had gotten less than they deserve than to think that Blacks had gotten less than they deserve. Black participants thought everyone had gotten less than they deserve. Since there were more White than Black participants, the averages for the full sample resembled those of Whites.

The data on the right address the research question. Clinton voters were almost as likely (57%) to say that average Americans have gotten less than they deserve as Trump voters (64%). Since this was a large sample, this 7% difference is probably statistically significant, but it is small in comparison to the difference on the racial resentment item. Only 12% of Trump supporters agreed that Blacks had gotten less than they deserved, compared to 57% of Clinton supporters—a difference of 45%. The data are more consistent with the racial resentment interpretation of Trump’s victory.

Tesler frames the responses of Trump supporters as an example of the ultimate attribution error. Attribution is the processes by which we infer the causes of behavior. The ultimate attribution error is the tendency to take personal credit for our own successful behavior and that of our in-group, and blaming our failures on environmental obstacles, while at the same time blaming members of out-groups for their failures, and attributing their successes to unfair advantages. Given this bias, it follows that Whites have gotten less than they deserve, while Blacks have gotten more.

Were the election results caused by economic anxiety or racism?  We still await a more definitive study. It will require a larger sample of voters and a valid measure of economic anxiety, with statistical controls for other variables known to influence voting decisions. If I see such a study, I’ll let you know.

You may also be interested in reading:

Trump’s Trump Card

What Does a Welfare Recipient Look Like?

Framing the Debates

What Does a Welfare Recipient Look Like?

Politics, Prejudice and discrimination, Social psychology,

Economic inequality in the United States is at record levels. In surveys, Americans say they would prefer a more equal distribution of wealth. However, the majority consistently votes against public assistance programs that redistribute wealth. Political scientist Martin Gilens, in his 1999 book Why Americans Hate Welfare, attributes this primarily to racial prejudice. Gilens examined the photographs that accompanied stories about poverty in the news magazines Time, Newsweek and U. S. News. African-Americans accounted for 62% of the poor people shown in the photos. On the ABC, CBS and NBC nightly news programs, 65% of poor people shown in reports on poverty were Black. In reality, as of 2010, 32% of welfare recipients were Black, 32% were White and 30% were Hispanic.

Gilens also did an experiment in which a “welfare mother” was identified as either White or Black. Participants who read about a Black welfare recipient were more opposed to welfare than those reading of a White recipient. The implication of Gilens’ research is that White Americans’ disdain for welfare is explained in part by racial prejudice. Americans hate welfare because they overestimate the percentage of recipients who are African-Americans. However, there is a missing link in this analysis. Gilens implies, but does not show, that Americans are influenced by these misleading media reports—that is, that the average American’s mental image of a welfare recipient is a Black person.

A research team headed by Jazmin Brown-Iannuzzi of the University of Kentucky sought to measure their participants’ mental representations of a typical welfare recipient using an unusual technique. I’m not sure I completely understand it without seeing a demonstration, but the image generation phase of their study goes something like this: First, they constructed a computer-generated “base face,” a composite of a Black man, a Black Woman, a White man and a White woman. Then, on each of 400 trials, the computer introduced noise which altered the base image in two opposite directions. The participants were asked to choose which of these two altered faces most resembled a welfare recipient and which one resembled a non-welfare recipient. (Race was never mentioned.) The computer then generated a composite image of a typical welfare recipient and a typical non-welfare recipient, based on all the responses of all the participants.

This was done twice, with 118 college students participating in Study 1 and 238 internet volunteers in Study 2. The composite faces from the two studies are similar and are shown below. Although the composite faces of the welfare recipients look like African-Americans, I presume this was less apparent to the participants as they made their 400 decisions.

During the second phase of these two studies, 90 different participants were shown one of the composite faces and were asked to rate the person on a number of different dimensions. No mention of welfare was made to these participants. The raters judged the welfare recipient composites as more likely to be African-American (rather than White) than the non-welfare recipient composites. The welfare recipients were also rated more negatively on 11 different traits, including lazier, more incompetent, more hostile, less likeable and less human(!). These studies fill in the missing link in Gilens’ research. The average person’s mental image of a typical welfare recipient is of an African-American.

Finally, Brown-Iannuzzi and her colleagues did a third study, an experiment in which 229 internet volunteers were shown one of the composite images—either a welfare recipient or a non-welfare recipient—and asked a number of questions. The critical items were whether they would support giving this person food stamps and cash assistance. The other questions repeated some of the ratings used in the previous studies. Here are the results. This study replicates the Gilens experiment mentioned in the second paragraph.

In summary, the first two studies showed that when asked to imagine a typical welfare recipient, people generate a mental image of an African-American, while their mental image of a non-welfare recipient is that of a White person. The third study demonstrated that when other people are shown these mental images, they were less supportive of giving welfare to the composite typical welfare recipients than the composite non-welfare recipients.

Finally, the authors did a mediational analysis to see which variables mediated between the composite images and the decision to support or not support giving welfare to that person. The data were consistent with the following causal chain (see below): The image leads first to an inference that the person is either Black or White. This, in turn, leads to a judgment of how deserving the person is. (Black people are less deserving.) Finally, the judgment of deservingness leads the decision of whether to support giving welfare to the person.

We are going through a period of extreme racialization of politics. Americans’ racial attitudes influence their opinions about other political issues that may or may not be related to race. In some cases, survey participants’ racial attitudes determine their attitude toward a policy merely because they believe President Obama does or does not support the policy. Not only do racial attitudes appear to have been the strongest predictor of support for Donald Trump, they mattered more in electing Trump than Obama.

Nowhere is racialization more evident than in attitudes toward financial relief for the poor. People support income redistribution in principle, but they overestimate the percentage of poor people who are Black. As a result, their racial prejudice discourages them from supporting income redistribution policies.

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Old-Fashioned Racism

The Singer, Not the Song

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What Happened? What Will Happen Next?

Politics, Prejudice and discrimination, , ,

This post is not completely thought out and is inadequately sourced.  I decided to write it quickly in order to compare my initial impressions of a Trump presidency to what happens weeks, months, or years from now.

What happened? And what will happen next? The first question must be approached with caution. I hope social scientists have collected good data on the demographic and ideological characteristics that are associated with support for Donald Trump. My guess is that the two leading contenders will be economic deprivation and racial or ethnic prejudice.

The corporate media have attempted to “normalize” Trump’s candidacy by suggesting that his support comes mainly from less educated Whites who have seen their standard of living decline in recent years. A couple of early studies cast doubt on this explanation and suggested that “racial anxiety” was the stronger motivator of Trump supporters. (See also this previous post.) A study by Rothwell and Diego-Rosell of the Gallup organization—the best I’ve found so far—finds only limited support for the economic explanation. Trump supporters are less educated and more likely to be blue-collar workers, but they are wealthier than either Clinton supporters or the population generally, and are no more likely to be unemployed. In other words, Trump is supported by the traditional Republican base of relatively affluent people hoping to increase their wealth. These authors also found that Trump supporters tend to live in racially isolated communities. However, their study lacked a measure of prejudice. Let’s hope some political scientists have included measures of racial attitudes in their research.

Why were the polls so wrong? The most likely explanation is the so-called Bradley effect, named for LA Mayor Tom Bradley, in which pre-election polls overestimate support for Black candidates. The flip side of this is that polls underestimate support for candidates who appeal to voters’ prejudices. The best indication of a Bradley effect so far has been the finding that Trump did better in online polls than telephone polls, possibly because respondents were embarrassed to admit they support Trump to a live person. (Of course, there are other explanations for this finding.)

To determine what will happen next, we need to divide Trump’s campaign promises into those that he can easily fulfill on his own, those that will require the cooperation of Congress, and therefore can be disrupted either by lack of unanimity among Republicans or a Democratic filibuster in the Senate, and those that will be difficult or impossible to carry out under any circumstances.

The easiest thing for Trump to do is abandon efforts to control climate change. Both the Obama Clean Power Plan and the United States’ ratification of COP 21, the Paris climate change agreement, are essentially executive orders by President Obama. They can be undone with the stroke of a pen, and most likely they will be. The latest studies of climate change are extremely alarming, suggesting that previous climate models have dramatically underestimated the problem. Any international climate agreement will collapse without U. S. cooperation. This suggests that by electing Trump, Americans may have inadvertantly brought about the end of human life on Earth within a couple of decades.

All the rest is merely rearranging the deck chairs on the Titanic.

Since Republicans control the Senate, it is likely that Trump will be able to ensure conservative domination of the Supreme Court for at least the next three decades. If so, Roe v. Wade is likely to be overturned, and the few remaining barriers to racial discrimination will be eliminated. But the best descriptor of the Roberts court is “pro-corporate.” This is important due to corporations’ tendency to sue any time a law is passed which they find inconvenient. Needless to say, they will find a sympathetic audience in a Trump-appointed court.

I also believe that Trump will have little difficulty getting approval for elimination of the minimal protections against Wall Street risk taking and outright fraud provided by the Dodd-Frank Act. This will likely include elimination of the Consumer Financial Protection Bureau. However, this may not make much difference since Dodd-Frank is so weak. In other words, it’s likely that we will have another Great Recession fairly soon, regardless of what Trump does.

At an intermediate level of difficulty for Trump are actions that require Congressional approval, and which all Senate Democrats and some Republicans may be reluctant to go along with. I put the repeal of the Affordable Care Act in this category, since it is essentially a massive giveaway of public funds to the insurance, medical and pharmaceutical industries, all important Republican donors. More likely to happen are modifications to Obamacare that increase corporate profits and make it more difficult and expensive for less affluent Americans to obtain medical care.

Another change requiring Congressional approval that will elicit Congressional resistance is Trump’s promise to cancel and/or renegotiate so-called “free trade” agreements such as NAFTA, or to withdraw from the World Trade Organization. These treaties, the primary goal of which is to increase corporate dominance of the international economy, have always had greater support from Republicans than Democrats.

On the impossible side is Trump’s immigration policy. In the final months of the campaign, he began to back off from his promise to build a wall on the Mexican border. More importantly, it is difficult to imagine the kind of chaos that would result from any attempt to deport the approximately 11 million undocumented people living in this country. More likely, he will cooperate with Congress in passing laws that make it more difficult or impossible for people of certain religious or ethnic groups to enter to the country in the future.

Now for two wild cards.

Will Trump be more or less likely than Barack Obama or Hillary Clinton to involve us in any more than the five foreign military interventions in which we are currently involved? My guess is that he will escalate the war against ISIS, with totally unpredictable consequences, but be reluctant to deploy American troops in new wars. But given Trump’s childlike temperament, this prediction could be way off base.

Finally, it is important to remember that George W. Bush and Barack Obama have created a massive national security apparatus, including the capability of spying on virtually any electronic communication between American citizens, and the militarization of the police, who can bring overwhelming force to bear against protesters and demonstrators. This is important because if Trump is able to fulfill his campaign promises, there will be widespread dissent on the left, and if he blunders badly, there will be buyers’ remorse among his current followers. Some of us were dismayed by FBI Director Comey’s recent intervention in the presidential election, but we should be prepared for the possibility that Trump will not hesitate to use the national security state for political purposes, including attempts to influence future elections.

You may also be interested in reading:

Trump’s Trump Card

The World According to the Donald

Framing the Debates