Conservatives have started calling their political opponents “groomers.” This term is shorthand for an accusation of sexualizing children or grooming them for sexual advances. The term has been used by online extremists since at least last year, but it has gone mainstream more recently as conservative writers have started using the term to defend Florida’s “Don’t Say Gay” bill, HB 1557. Florida Governor Ron DeSantis’ press secretary described the bill as an Anti-grooming bill, and said that if you’re against the bill, “you are probably a groomer.”
In a similar manner, the “groomer” discourse overshadows real issues in the world. First, it perpetuates myths about LGBT people. One such myth is that LGBT people are more likely to engage in sexual misconduct with a child. The truth is that children are no more likely to be molested by a homosexual person relative to a heterosexual person (after controlling for the fact that there are far more heterosexual people). Another myth is that trans and homosexual identities are somehow inherently sexualizing or obscene while cis and heterosexual identities are not. Of course, these myths just further the existing stigma and discrimination faced by sexual and gender minorities.
The groomer discourse also overshadows evidence-based approaches to addressing child sexual abuse. One of the common refrains from people who support HB 1557 is “keep sex out of the classroom.” Unfortunately, if this were translated into a policy, it would be the exact policy that would exacerbate sexual abuse by keeping children unprepared and ignorant of how to respond to advances made by sexual abusers. Meta-analyses of child sexual abuse prevention studies have demonstrated that children in pre-school and elementary benefit from learning about sexual abuse concepts and self-protection skills. A retrospective study found that girls who haven’t participated in child sexual abuse prevention programs were about twice as likely to have experienced sexual abuse. Importantly, these trainings often involve explicit conversations about sex that go far beyond the simple explanations of homosexuality and trans identities that animated the Florida law and its defenders. For example, one training program for preschoolers (performed by parents or teachers) involved discussions of genitalia, where it is located, and how to identify inappropriate touching. To the extent that this conservative push to fight “grooming” is truly driven by a desire to help children, it is sadly likely to have the opposite effect.
Sexual abuse, LGBT discrimination, teen pregnancy are all major problems. Unfortunately, all of these problems are likely to be made worse by laws like HB 1557 and the right wing approach to label LGBT people and their liberal allies “groomers.” Solving these problems requires an evidence-based approach in identifying the real problems and their solutions. Laws like HB 1557 will only be another divisive obstacle in solving these problems that draws us away from the evidence-based solutions. There is no evidence that LGBT inclusive sex education will “groom” kids to be easier to sexually abuse. In fact, the evidence goes in the other direction: Inclusive and evidence-based sex education is a vital part in preventing sexual abuse, anti-LGBT sentiment, and teen pregnancy.
Belief in “learning styles” is widespread despite there being no compelling scientific evidence for the theory. Read more on the problems with learning styles, how widespread beliefs in learning styles are, and why these beliefs persists.
Are you a visual learner? You know, someone who needs to see a diagram or picture to really learn something. Or maybe you’re an auditory learner? I mean, you are always listening to podcasts and audiobooks, right? Maybe you’re a kinesthetic learner, because you like to play sports and garden?
If you were a student in the last five decades, you probably took a quiz (like this one) ostensibly designed to determine your learning style. Your teacher’s quiz probably had you respond to items like: “I want to learn how to play a new board game or card game. I would:”
Read the instructions.
Listen to somebody explaining it and ask questions.
Use the diagrams that explain the various stages, moves and strategies.
Watch others play the game before joining in.
As someone who taught high school for a few years before graduate school, I can tell you that my fellow teachers and I were taught to consider learning styles. In 2009, I was trained to think of students as having a preferred learning style that reflects how they need to be taught in order to be most successful in academia. Furthermore, I was taught that a good way to teach is to figure out the learning styles of your students and construct assignments, lessons, and assessments that appeal to their individualized learning styles. So, in my first year of class, I administered a learning styles quiz and taught my students that they are a specific type of learner based on their quiz results.
This reflects the two underlying assumptions of the “learning styles” approach. First, students have a stable learning style that doesn’t change much over time and can be determined using a questionnaire. Second, students learn better if they are taught (or if they learn on their own) using their preferred learning style.
Unfortunately, there are many problems with this approach. First and foremost, there has never been strong empirical evidence supporting the above assumptions about learning styles. This is the conclusion of a 2009 review of the scientific evidence and the conclusion of another review completed in 2015. A separate 2015 article focused on the two assumptions of the learning styles approach (i.e., learning styles are stable and measured with questionnaires, and they improve achievement). Is there evidence that the visual learners of today will be the visual learners of tomorrow, or in more technical language, are learning style questionnaires “reliable”? The answer from the review: No. Learning styles are not consistent for most people. A learner may be categorized as a visual learner today and take the same assessment a month later and be categorized differently. What about the second assumption that learners perform better when their lessons are matched to their style? Decades of research revealed “no viable evidence to support the theory.” It is for these reasons that learning styles are frequently described as a “neuromyth” in some of the current education research on the topic.
Of course, “there is no evidence” is generally a great reason to cast aside an idea. But, lacking evidence isn’t the only problem with belief in learning styles, there are potential harms. One potential source of harm is that learning styles may reinforce an essentialist view of students’ learning abilities as fatalistically fixed. Essentialism also tends to carry with it the assumption that fixed differences are genetically inherited and are rooted in brain differences. A recent study found that about half of people who believe in learning styles hold fairly essentialist views. Importantly, an essentialist view runs counter to maintaining a “growth mindset” where students are seen as capable of making significant improvements to their intelligence and academic performance, a perspective that is associated with academic improvement.
Beyond the empirical and essentialist problems with the learning styles approach, there are more hidden costs. The learning styles approach is a fruitless blind alley that many teachers invest time, money, and effort into when those resources would be better spent on evidence-based approaches. As a first year teacher, I took up a significant portion of a class administering a survey and painstakingly walking through the “learning styles” concept. I also pigeon-holed students with “individualized” assignments that increased their chances of primarily getting one specific type of lesson instead of receiving a wider variety of approaches in their education. Though, I didn’t do this as much as I could have since it is exceedingly difficult and time consuming to individualize to that level.
Despite the clear status of learning styles as a non-evidence-based and non-scientific idea, the concept is alive and well among members of the public, educators, and shockingly, among researchers. Around 80-95% of the general public and educators in Western, industrialized countries endorse the learning styles myth. A 2020 study found that 89% of over 15,000 educators from 18 countries, spanning 2009 to 2020, reported believing in teaching students based on their learning styles. While there aren’t similar surveys of beliefs among education researchers, a 2015 review of higher education research found that 89% of recently published research papers on learning styles “implicitly or explicitly endorsed the use of learning styles in higher education”. It’s hard to imagine that so many pro-learning styles academic papers could be published without significant levels of personal belief in learning styles among academics.
Why is the belief in learning styles still so prevalent? In some ways this is the same question we find ourselves increasingly asking in an era filled with misinformation, conspiracy theories, and pseudoscience: Why are beliefs in false and incorrect ideas so prevalent? As with many widely believed falsehoods, there are structural reasons behind misinformation. In the case of learning styles, researcher and school psychologist Dr. William Furey has written about how 29 states require new teachers to be tested on learning styles in order to be accredited. Twenty-one of those states require teachers to complete a “test of instructional knowledge” created by the Educational Testing Service (ETS) which asks questions pertaining to learning styles. Dr. Furey points out how this incentivizes perpetuating the myth, because you need to know learning styles to pass through the accreditation process. Worse, the inclusion of this debunked concept in the education curriculum pulls time and effort away from evidence-based teaching methods. He bolsters his case by citing a National Council on Teacher Quality’s textbook evaluation, which found that 59% of textbooks do not mention the six highest-impact teaching methods (yet advocate planning instruction around learning styles).
Beyond these structural issues, learning styles appeal to our intuitive perceptions of ourselves and others. It seems like people tend to be better at some things over others. It makes sense that matching a person with what they prefer would make them more successful. We generally struggle to understand how behavior emerges from the complex interactions between our biology and our environments. Learning styles are another appealing overly simplified categorizing system, like astrological signs, Myers-Briggs personality types, and whatever sigma, alpha, and beta males are. Unfortunately, these categorization systems aren’t supported by evidence and can even lead to harmful consequences.
Originally published on The Pipette Pen and peer edited by Victoria Hope Williams
Are liberalism and conservatism associated with unique psychological tendencies and behaviors? Or are the extreme left and right mirror images of each other? The political psychology literature sometimes characterizes this question in terms of ideological symmetry vs. asymmetry. According to the asymmetric perspective, the two political ideologies result from different motivations and satisfy different psychological needs. For example, there may be an asymmetry such that conservatism is associated with less flexible thinking and liberalism is associated with more warmth in people’s interpersonal relationships (Figure 1, top). In contrast, the symmetric perspective suggests that the same psychological motives and needs drive people to political extremes, whether it is to the right or the left of the political spectrum. Using the same example from before, this perspective would suggest that extremists on both sides are less flexible and less warm in their interpersonal relationships (Figure 1, bottom). The symmetric perspective is often referred to as the “horseshoe theory,” a term attributed to the French philosopher Jean-Pierre Faye, because the far-right and far-left closely resemble each other, analogous to the ends of a horseshoe.
Irrespective of the terms used to describe these two theoretical perspectives, people’s perceptions of conservatism and liberalism as symmetrical or asymmetrical colors their perception of the political landscape. For example, if you see the two political parties as essentially the same with only minor differences in what shirts are worn at political rallies or what slogans are shouted at political opponents, then you might not see a reason to choose one over the other in the voting booth. If both parties are equally irrational or biased, you might perceive outrage from one side on issue X as equally valid as outrage from the other side on issue Y. Thinking through the similarities and differences between political parties can be an important part of making up your mind about your own ideological perspectives and participating in the voting process.
As with many debates in the social sciences, one can point to different research to find evidence for either the symmetry or asymmetry perspective. Researchers often describe political symmetry or asymmetry in terms of cognitive dimensions (i.e., how people think) and affective polarization (i.e., how people feel about their ideological opponents). Asymmetry proponents often cite research finding that unique psychological variables predict political conservatism. For example, the need to reduce uncertainty and ambiguity, to experience order and closure (i.e., definitive knowledge on something), and to defend one’s status are correlated with political conservatism. Conservatism is also argued to be built upon a distinct set of moral foundations–which includes purity, sanctity, and in-group loyalty–compared to liberalism. Indeed there is a rich history of investigating the psychological profile of conservatism as associated with emphasizing tradition, conformity, security, power and achievement, having more rigid thinking, and perceiving the world as more threatening and dangerous, but also see the inequalities of the world as more justified.
While this first body of research suggests that liberals and conservatives are quite distinct, there is a second body of research that challenges these data and proposes that liberals and conservatives engage in many of the same cognitive biases. Is dogmatism really a feature of the political right if extremists on both sides of the political spectrum feel superior about their beliefs? Why is it that supposedly open-minded liberals are similarly motivated to avoid exposure to opinions from the other side? Liberals and conservatives also engage in motivated disbelief in politically convenient ways. Both sides find it equally difficult to identify flaws in arguments from the other side and struggle to find the flaws in their own ideological arguments. A recent meta-analysis of 51 experimental studies showed that both liberals and conservatives tend to evaluate identical information more favorably when it is consistent with their beliefs and preferences.
This second body of research supports the symmetry perspective and suggests a similarity in the cognitive profiles of those who identify as liberal vs. conservative, with those on the extreme ends of the political spectrum showing the same kind of inflexibility. Researchers also found consistencies in how ideologically-driven humans engage those with whom they disagree. For example, research consistent with the symmetry hypothesis shows that liberals and conservatives both report prejudice against their ideological opponents. Put simply, those on the left and right hate each other to similar degrees. However, much of this research hasn’t taken into consideration the implications of such prejudice. The demographic compositions of one’s political opponents are quite different, depending on whether you are on the left or right. Voters who identify as Republican are more homogeneously white, wealthy, male, Protestant and older. Democratic voters are a more diverse group, composed of most of the country’s Black, Hispanic and Asian voters, most of the college and postgraduate educated voters, most of the Jews and Hispanic Catholics, and the majority of LGBT folks. Thus, while it may be true that both groups engage in discrimination or prejudice against their ideological opponents, the targets of that prejudice are quite different.
Because of their respective demographic makeups, when conservatives hate liberals, they are holding prejudices against historically marginalized groups and the policies they support. When liberals hate conservatives, they are holding prejudices against groups that wield disproportionate power in society. This dynamic may partly explain why researchers do not find ideological symmetry in racism, sexism, homophobia, or any form of prejudice towards a group based on immutable characteristics. Conservatism is uniquely linked to more racial resentment, more sexist attitudes, and more homophobic attitudes. Conversely, claims of anti-white, anti-man, and anti-straight biases and their link to liberalism remain unsubstantiated. Although these biases may very well exist, they are not situated in the context of historical and systemic inequalities that amplify the consequences of bias toward historically marginalized groups.
Clearly, understanding similarities and differences between those on the political left and right is complex. After reviewing all of the evidence, can we definitively say whether liberals and conservatives are psychologically asymmetrical vs. symmetrical? The answer is not straightforward. In some ways, we find evidence of symmetry; and, in others we find evidence of asymmetry. We have seen that liberals and conservatives both fall prey to the same kinds of biases. Those on the left and right also show the same kinds of prejudices against their ideological opponents. Yet, due to differences in the demographic composition of these groups, the consequences of these prejudices are asymmetrical. In other words, there is evidence of asymmetrical marginalization such that conservatives, relative to liberals, will be more likely to hold biases against people from marginalized backgrounds and their views.
As we continue to advance our understanding of politics and partisanship, we must keep these complexities in mind. We must focus on understanding the asymmetrical downstream consequences that arise from symmetrical cognitive and interpersonal biases. Because the prejudice partisans hold towards each other implicates different groups, it may be that such animosity arises from different underlying motives and needs on the left vs. right. For instance, if those on the left indeed show anti-white, anti-man, and anti-heterosexual biases, these may stem from an interest in advancing an egalitarian redistribution of power and wealth in society. Or, they may simply reflect an intolerance of perceived intolerance. In contrast, the animosity held by those on the political right towards historically marginalized groups may arise from zero-sum beliefs, where attempts to increase equality are seen as “unfairly taking” from those who have a privileged status now. This is consistent with research showing that perceptions of anti-white discrimination are due to seeing racial biases as zero-sum, such that white Americans see falling bias against Black people as a sign of rising bias against White people. It is clear that there is still much to learn about the psychology of politics. As we embark on advancing our scientific understanding of these issues, we must keep in mind the reality of asymmetrical marginalization and leverage these insights to build a more equitable, fair, and just society.
The above tweets (and meme) were published as part of a larger social problem of what to do about the proliferation of misinformation. These tweets have many embedded and interrelated arguments. I’m going to focus on just one of these arguments, namely, that “censorship undermines media trust.” There is an obvious truth to this argument: authoritarian censorship undermines trust in the media. But, there is a different implicit argument: unfettered free-speech will promote trust in the media. What follows is my attempt to look for evidence for this argument.
There have been calls for platforms like Spotify and Substack to reign in COVID related misinformation. The issue of whether tech companies should administer editorial oversight or content regulation has become yet another partisan issue. But again, this is in the broader context of an incredible explosion in the capacity to reach an audience of millions with little to no expertise or editorial oversight. Since the invention of the printing press in the 1400s and the evolution of newspapers, magazines, radio, and TV, there has generally been editorial oversight. People with educational qualification, journalistic experience and/or ethical responsibilities, or otherwise, have regulated the extent to which ideas could reach large audiences. This new era of new media content is a historically unprecedented inflection point in our cultural evolution, where an audience of millions is only a few viral stories away. I mention this context to immediately note that our perception of media and its relationship to free-speech is likely far from straight forward.
Nevertheless, a simple straightforward idea like “unfettered free-speech predicts trust in media” can be imperfectly investigated using a straightforward analysis. Upon encountering this argument, I went looking for data that would speak to it’s veracity. I looked for data on how much people trust the media in a variety of countries and then looked for data that might “explain” the cross country differences in media trust. I should make a pedantic note that I cannot draw causal conclusions from these data, so I use “explain” in the correlational sense. I’m just looking at what factors are associated with cross country differences in media trust. If the causal narrative that “unfettered free-speech predicts media trust” is true, I would expect to find that factors related to free-speech would predict media trust. I found data on free speech preferences, human freedom, press freedom, polarization, inequality, and anti-vax conspiracy beliefs. Below I describe all the data and then run a couple simple correlations. I also have provided all the data here.
Of course, we should take the findings with a grain of salt. No simple collection of data will completely model the massive sociological problem we are facing related to free-speech, censorship, and media trust. Those caveats stated, let’s take a look at some data that may inform us about how free-speech, censorship, and media trust relate to one another in 2022.
Are higher degrees of free-speech support, free speech access, and free press conditions associated with more media trust? Let’s see.
Data point 1: Media Trust
As shown in the meme above, one relevant bit of data that is circulating on social media is a study purportedly showing that the US ranked dead last among 46 countries as having the least trustworthy media. This data comes from a report released by the Reuters institute for the Study of Journalism at Oxford. It surveys 92 thousand people in 46 countries. I want to see what other data explains the ranking of trust in news media.
Data Point 2: Free speech support
Compared to other countries around the world, US citizens are the most supportive of free speech, according to a Pew Research analysis from 2016. Maybe countries with a lot of free-speech support would trust the news media more.
This level of support for free-speech reflects our fairly loose restrictions on free-speech. For example, unlike most other countries, the US lacks restrictions on hate speech. Of course, there isn’t a perfect correlation between free-speech support and actual free-speech as evidenced by the Polish government which has arrested LGBT activists, and people who insult monuments. Even in the US, there are obscenity laws that prevent the freedom to say certain words and display certain images on radio, TV, and newspapers.
Fortunately, there are other data sources to evaluate the degree to which we have free speech in the US relative to other countries.
Data Points 3-5: Personal Freedom, Economic Freedom, and Human Freedom
Two think tanks, the libertarian Cato Institute and conservative and libertarian Fraser Institute produce an annual report on their global measure of “personal, civil, and economic freedom” which grades countries along 82 distinct indicators of “freedom.” Relevant to my investigation is their indexing of freedom of association, assembly and civil society, freedom of expression and information. They quantify these complex societal variables into 2 unique indexes: Personal freedom, and economic freedom. Both of which are combined to create a “human freedom” index. To state the obvious, these measures are certainly imperfect, but they are some relevant data points related to actual freedom people have in society, rather than just the stated preferences people have toward free speech. Maybe these measures will help us explain the degree to which people distrust the media.
Data point 6: Press Freedom
The French International NGO Reporters Without Borders has its own annual report on press freedom; the World Press Freedom Index. This index is designed to measure a country’s press freedom by evaluating seven criteria: media pluralism (if there are a variety of opinions represented), environmental and self-censorship, legislative frameworks, transparency, infrastructure, abuses, and media independence. Higher numbers indicate less freedom. They rely on the input of many experts to create this index. Surely where countries fall on the World Press Freedom Index would predict some of why people distrust the media.
Light yellow = most freedom of the press, Black = Least freedom of the press
Data points 7-9: Polarization
The UK based marketing research company Ipsos MORI evaluated the extent to which the world had grown more polarized across 27 countries in 2018. Specifically for my investigation, I looked at their data on whether participants thought that people in their countries were more (or less) divided than they were ten years ago, and a second question on whether they thought people were tolerant to those “with different backgrounds, cultures, or views.” I sought out polarization data because polarization is often cited as one of the most relevant factors related to media distrust by political scientists. Maybe this explains the media distrust we are seeing?
Data point 11: Anti-Vaccine conspiracy theory beliefs
YouGov and the Cambridge Globalism Project teamed up in 2020 to interview 22,000 people in 21 countries to estimate beliefs in conspiracy theories. I took data from a single question about the extent to which people believe that “harmful side effects of vaccines are hidden from the public.” Maybe this kind of misinformation is related to media distrust.
So, what story is there to tell with all of these data?
Let’s take a look at a simple correlation table among the variables we are using to relate to media distrust. Many of the relations make sense. For example, support for free-speech correlates well with personal freedom and more press freedom (remember low free_press = more freedom). The three indexes of freedom from Cato correlate well with the free-press index from Reporters Without Borders. These correlations are reassuring; the variables are relating to each other the way we would expect. On the other hand, surprisingly, support for freedom of speech is correlated to a perception of being more divided now than 10 years ago.
Importantly, these effects aren’t due to the US being an outlier, they aren’t meaningfully different when the US is removed.
So, how do these variables predict media distrust?
Well… they don’t. None of them even correlate with media distrust. To some extent this is probably related to the relatively small sample size, but the direction of the relationships are also backwards. Media distrust has a non-significant negative correlation with free-speech preferences, and free-speech freedoms.
What conclusions can we draw from this collection of statistically non-significant findings? In some sense, it evidences my original point: This stuff is complicated and none of these variables are sufficiently capturing the dynamics that explain media distrust. Remember, the implicit argument is that “unmitigated free-speech promotes media trust.” But we looked at data representing the degree to which free-speech is mitigated and we looked at data representing media trust and found them to be uncorrelated. This doesn’t disprove anything, but it also doesn’t offer supporting evidence for an argument that is being proffered so vehemently. The fact that the non-significant correlations trend in the opposite direction is also quite interesting. Maybe countries that allow more unmitigated free-speech will have a more difficult time tamping down on misinformation that could damage public trust in media, government, and medicine during a global pandemic? Likely, there is a bunch of complex stuff going on all at once and simple narratives about what does and doesn’t undermine or promote media distrust are likely to be, well, oversimplifying. Clearly a more principled and extensive investigation is necessary to fully flesh out the associations here.
As stated in the beginning, surely authoritarian censorship will degrade media trust, but that is an extreme case. Authoritarian censorship isn’t really relevant to the state of free-speech in the democratic developed world. Instead we have a constantly evolving media ecosystem in which each country has negotiated a set of laws that protect free speech as one of many freedoms to consider. Would more strict rules, terms of service, or even laws regulating free-speech make people distrust the media more? Well, some countries that have more regulations have more trust in their media, not less. In the data I looked at, free-speech and media distrust seem fairly unrelated to one another, at least among democratic societies. Then again, maybe the US is a unique context where it would be particularly hard to reign in speech without exacerbating existing distrust. In the end we don’t know. But we should strive to not get overly attached to narratives stated with such certainty and without evidence.
Scientists warned policy makers about a global pandemic for years, and we were still unprepared. What other predictions are scientists making that we should be reacting to?
In the Greek tragedy of Agamemnon, Cassandra, the princess of Troy, is given the ability to see into the future but is cursed to never be believed. In the tragedy, Cassandra knows of the impending doom of all she holds dear, her own life, the lives of her family, and indeed Troy itself. But she was powerless to stop it. No matter how much she implored those around her towards action… she was ignored.
The story of Cassandra can be seen as an allegory for actionable knowledge that, for one reason or another, is ignored to tragic ends. This dynamic of ignoring accurate predictions of the future is more prevalent now than ever before. In the 21st century, people don’t pay much attention to dodgy prophecies from temperamental gods or elaborate spooky rituals. Instead, the world has millions of the best and brightest scientists making predictions based on empirical evidence, complex technology, and scientific consensus. Our predictive ability has gotten humans to the moon, has prevented hundreds of deadly diseases, and has made it possible for me to easily share this thought with you now. Yet, the curse of Cassandra lives on and we, as a result, all live in our own modern tragedy.
Of course, President Obama didn’t have the gift of prophecy, he was reacting to other infectious diseases that impacted the US and the world during his presidency, H1N1, Ebola, SARS, and ZIKA. While none of these 4 diseases became as big of a problem as the novel Coronavirus–in terms of number of deaths or infectivity–they signaled the possibility of a global pandemic. But decades before the slow reactions of politicians, scientists had been sounding the alarm.
For example, in the mid-1980s a leading influenza vaccine researcher named Edwin Kilbourne participated in a virology conference, and proposed a highly contagious virus with scary properties–actually far worse than those of the coronavirus–that would wreak havoc on the globe. 30 years later, prophecies of a global pandemic reached a fever pitch in the 2010s. But, a consensus had been building for years in the public health and virology community that a virus with the right characteristics to lead to a global pandemic will inevitably emerge. Experts implored us to get prepared right away.
“Agamemnon is coming! Troy will fall and we will all die unless we do something now!” said the prophets.
And some did listen! There are plenty of success stories from countries who successfully navigated the global pandemic by heeding scientific expertise. Some countries, like New Zealand and South Korea, are all but back to normal (minus the usual influx of tourists) while comparably wealthy countries like the US and the UK continue to have massive spikes of infections. In other words, some saw past the curse and escaped Troy, while some are still not listening to reason as Troy burns down around them.
But the Coronavirus pandemic of 2020 is just a very obvious example of the much larger problem. There is a curse on science, where scientific consensus emerges that identifies a problem and solutions to that problem and then these prophecies go unheeded. I will quickly explore two general types of cursed scientific prophecies. The first category– the “easy problems”–of cursed scientific prophecies are of an almost banal nonpartisan nature. The second category–the “hard problems”–are those prophecies that found willful partisan political opposition.
Antibiotic resistance occurs when disease-causing microorganisms (i.e. bacteria and fungi) evolve the ability to survive treatment from antibiotic drugs designed to kill them. The World Health Organization (WHO) describes antibiotic resistance as “one of the biggest threats to global health, food security, and development”. This danger has been discussed as early as 1945 when Alexander Fleming raised the alarm, and the problem has only worsened. To some extent, resistance is naturally occurring, but it is exacerbated by sparse regulations in many countries, inappropriate prescribing, and overuse in agriculture. These issues continue, despite WHO guidance on how to prevent and control the spread of antibiotic resistance.
To be clear, I don’t think these are “easy” problems in that solving them would be simple and quick. Rather, I mean that they are problems that a) have been documented for decades, b) have readily available solutions that are under-utilized, and c) do not have an obvious political or ideological opposition (debatably at least). These problems may not create the attention-grabbing headlines they deserve, but they don’t exist in some political or scientific grey area; these problems are widely acknowledged. Nor do solutions require a vast renegotiation of the political system. And yet, over the decades, scientists raising the alarm (and providing solutions) simply hasn’t led to the resolution one would expect of a constructive society that reacts to actionable scientific knowledge. Sadly, it only gets worse from here. If these “easy” problems seem difficult to address, imagine the difficulty that emerges when those in power disagree on whether the problems even exist or deserve to be addressed. In other words, think of how much more intractable these problems become when they are politicized.
The “Hard” (Politicized) Problems
This is a massive subject that I will quickly overview by noting several “sub-crises” under this umbrella.
We are living through the 6th mass extinction event in the earth’s history, but this time it is largely due to human activity. The extinction rate of species is hundreds or thousands of times faster than the estimated “background” rate seen over the last tens of millions of years. A recent UN report describes the “overwhelming evidence” of this “ominous picture” and provides a road map of the “transformative change” needed to address this issue.
Again, this is a massive topic with a mountain of research on a global level, within specific countries and within specific communities around the world. I will provide only a brief summary of poverty in the US. We know that child poverty costs around $1 trillion per year, unstable housing will cost an estimated $111 billion over the next ten years, the cost of food insecurity alone was $178 billion in 2014, and in the year 2000 172,000 deaths could be attributed to individual- and area-level poverty. According to the U.S. Department of Health and Human Services, 12% of the US population (40 million people) in the US live in poverty. But this is a low estimation. The international Organisation for Economic Co-operation and Development (OECD), estimates that 18% of Americans (~59 million people) live in poverty (meaning they have less than half the American median income). By looking at other countries like Denmark and Finland where only 5-6% of the population is in poverty, we can see that our level of poverty is not an intrinsic aspect of human society. Indeed, of the 37 countries in the OECD, 35 of them have less relative poverty compared to the US. It is for these reasons that the US government has been called on by the UN and Human Rights Watch to address poverty. Furthermore, the American Psychological Association has made several recommendations for how to address poverty in the US, for example by raising the minimum wage (which likely will not occur in 2021).
Economic inequality, meaning the size of the gap in incomes and wealth between different economic class groups, is a distinct problem to poverty that also predicts social problems. Inequality is easily seen by statistics like: 80% of the wealth in the US is held by 20% of it’s wealthiest citizens. I’ve discussed the link between inequality and health and social problems in a previous article, but the gist is that economic inequality predicts lower life expectancy, math and literacy skills, trust, and social mobility as well as higher infant mortality, homicide, imprisonment, teenage births, obesity, and mental illness. In other words, the harms of economic inequality are very clear and solutions are available.
Curses aren’t real, so why is this happening?
As with the “easy” problems, the “hard” problems are well-understood and the solutions are readily available. However, politicization of these issues adds a deep layer of intractability to these problems. In part, politicization is to be expected because there are extremely influential vested interests in environmental and economic issues. There is a long history of corporations opposing environmental regulations intended to protect human health and the environment. Similarly, campaign contributions and lobbying can facilitate the development of pro-corporate economic policies at odds with egalitarian policies.
Another reason for the intractability of politicized problems is ideology. In general, political conservatism in the US is related to ideals of individual freedom, private property rights, limited government, and promotion of free markets. Political liberalism in the US is related to collective rights, market regulation to protect citizens and public goods, extending rights to underprivileged groups, and expanding the social safety net. This ideological framework can explain why, research has found that conservatives tend to attribute poverty to self-indulgence and laziness, while liberals tend to view poverty as a result of a poorly functioning society. Similarly, other research has found that conservatives are more likely to tolerate and justify inequality and deny or minimize problems associated with high inequality. Liberals and conservatives tend to differ on climate change as well, such that liberals are more likely to recognize the problem and support policies that address climate change.
It is important to state unequivocally: science is no replacement for politics or policy-making. As recently argued by Dr. Carlo Rovelli in Nature Materials, politics requires the navigation between competing values and interests and science is not suited to replace this process. That being said, in a world without divinely granted gifts of prophecy, science is the best tool we have for predicting the future, for identifying problems in society, and for developing evidence-based solutions. Thus the default position of politicians should be to often consult with scientists and give heavy consideration to scientific evidence for or against a policy. Furthermore, policy-makers should be held to account by the public and journalists when they take policy steps that are counter to the scientific consensus. Science is the best method we have to make accurate predictions of the future and members of the public and policy-makers ignore the warnings and prophecies of science at our collective peril. We live in an age of truly awe-inspiring scientific prophesizing beyond what was anticipated by the mind that dreamed up the Princess of Troy; let us act like it.
Racial disparities are not new; they are a continuation of the legacy of 246 years of slavery followed by 100 years of virtually no citizenship rights for Black people in North America
Racial inequality is a well-documented phenomenon in the United States. Based on polling data taken in 2019, most Americans agree that Blacks are at a disadvantage compared to whites. Those polls also show that whites and conservatives (as groups) are least likely to agree that Blacks are at a disadvantage. In a previous article, I outlined two competing narratives used to explain racial inequality between whites and Blacks. One narrative favored by the majority of liberals and Black people in the US is that historical and current discrimination is the primary cause of Black/white racial inequality. The other narrative favored primarily by conservatives and by a significant portion of the white population is that individual differences in things like cultural orientation, values, motivations, and behaviors are the primary cause of Black/white racial inequality. I outlined evidence that shows that a science-based model of the causes of inequality accepts both narratives as partly true and not mutually exclusive. In this article, I would like to cover this topic more by exploring the relevant history that precedes racial inequality. We will continue with these two competing narratives in mind.
We have already looked at the most powerful method for investigating cause and effect: scientific experimentation. I described the experimental and empirical evidence that supports the claim that racial inequality in the US is due both to discrimination and individual differences. But there are other ways to evaluate cause and effect besides conducting experiments. One can evaluate evidence for “temporal precedence”, i.e., that the cause precedes the effect in time. For A to cause B, A must occur before B. In the case of racial inequality, there are two timelines that come from the liberal and conservative narratives. By claiming that discrimination is the cause of racial inequality, liberals are implying that discrimination precedes inequality. Alternatively, conservatives that claim individual factors like culture, values, and behavior cause racial inequality, are implying that individual factors precede racial inequality. Let’s consider the liberal perspective and then the conservative perspective.
From a historical standpoint, current inequality is entirely consistent with previous inequality. Racial disparities are not new; they are a continuation of the legacy of 246 years of slavery followed by 100 years of virtually no citizenship rights for Black people in North America (a cumulative total of 87% of the relevant history starting in 1619). It is only in the last 54 years of US history where Black Americans have had access to rights as citizens. Yet despite these legal advances, many racial gaps have not closed in that time. It is a historical fact that the worst form of discrimination (brutal dehumanization and enslavement) preceded the inequality that Black people face today in the New World. In fact, researchers have predicted the level of implicit bias in a US geographic region today based on the per capita enslaved population in that region in 1886. Basically, the degree to which a county or state depended on slavery before the civil war predicts how much pro-white bias exists in that same region today. Not only that, but slavery was also linked to forms of contemporary structural inequality such as black poverty rates, racial segregation, and Black social mobility. This is striking empirical evidence that the legacy of slavery persists into the current era in both the structure of society and attitudes of many. Of course, since the ending of slavery there were other intervening instances of codified racism such as redlining, the practice by which Blacks were systematically discriminated against when buying a home (until it became illegal in the 70s), which still has negative effects today. In other words, we have good historical and scientific reasons to think that the timing (discrimination precedes inequality) fits the narrative that discrimination causes inequality.
What about the conservative viewpoint that choices and cultural values precede racial inequality? Did racial inequality emerge out of the choices of Black people in the United States? Well, let’s consider the timeline. Over 90% of Black Americans are the descendants of people who were captured, enslaved and brought to the New World. When they arrived, they were intentionally stripped of their culture and separated from their families. Over the course of many generations, millions of African Americans were forced to live in a state of deadly inequality for around 200 years (depending on when they arrived). It isn’t until 1965 that Black Americans could even have the possibility of making free choices that could result in parity with whites. So as we can see, the idea that choice, values, and culture could cause inequality is not supported by the timeline: inequality preceded legitimate self-determination of African Americans to make their own choices, establish values, and build a sense of culture.
Of course, people who endorse this narrative may balk at this line of reasoning and clarify that the persistent inequality in the modern era is the result of choices, values, and culture because now people of all demographic backgrounds are free. To evaluate this perspective, let’s consider an analogy where we think of life in America as a foot race. We start this race from the moment we are born and how far we get is a measure of our health, wealth, and status. Those who run the least distance over time are least successful and those who cover the most ground are the most successful. But, this isn’t the only measure of success, another important measure of success is just how far you have gotten, which is not just about your ability to cover ground, but also a question of where you started in the race. This is because life isn’t just a foot race, it’s a relay race! Meaning, people “pass the baton” to their familial successors in the race, so that those who are related to people who succeeded in earlier eras of the foot race (say from 1619 – 1964) are more likely to succeed in the current era. In life, this is analogous to the intergenerational passage of tangible resources like money, homes, vehicles, and economic opportunities, and also intangible resources like familial support, role-modeling, motivational orientation, and values.
But, intergenerational transfer goes beyond tangible assets like wealth and homes. Something as intangible as propensity to be incarcerated is intergenerational. A 2017 meta-analysis that synthesized results from 3 million children found that risk of criminal behavior is 2.4 to 1.8 times higher for kids with criminal parents (a trend that has actually gotten worse since 1981). This is partly because parents (even those who have not been incarcerated) often have little choice but to pass their low income, high crime, and overpoliced community to their children. In highly policed areas, children’s contact with law enforcement is linked to psychological distress that predicts criminal behavior (even after controlling for prior delinquent behavior). Black kids that do not have life altering experiences with crime or police find similar intergenerational effects apply to educational advantage. If they do get to college, Black Americans are far more likely to be first-generation college students who do not have the benefit of parents who successfully navigated college. The intergenerational passing of educational advantage is a well-documented mechanism in the white/black achievement gap. People also inherit a positive attitude towards working hard from their parents according to another meta-analysis of nearly 10,000 people. Even the propensity to participate in political struggles that can address some of the systemic issues at play here is itself intergenerational. In the year before Trump won the election with 3 million less votes than Clinton, a study found that political participation intention is partly intergenerational.
So yes, conservatives are correct in some sense, individual differences matter, but individual differences are largely passed intergenerationally and thus are in large part the result of past discrimination and racial inequality. Like everything else, behaviors and choices don’t emerge out of nowhere, they emerge from a specific historical and social context. As we have seen the relevant historical context is quite unequal. This is a rehashing of the point I made in my last article that bears repeating: The conservative position does not really grapple with the full problem. Sure, there are differences in choices and values within certain communities, but why?
Here, I should note that for some, this question leads to a fundamental notion in the history of psychology: nature vs nurture. In previous eras racial disparities were thought to be either due to the environmental differences in the lives of Blacks and whites, or they were due to genetic differences (an idea with an ugly past and present). Scientists now know that this is a false dichotomy, it’s not nature or nurture, it’s both in a complex and often hard to predict interaction. Separating them can be impossible, particularly when certain environmental conditions, like experiences of discrimination are inseparably linked to one’s genetically determined race. For these reasons, the history of focusing on genetics as a cause of racial inequality is both racist and seen as pseudoscientific. But even from a strictly pragmatic perspective, we can only influence environmental factors since we don’t have the tools to ethically influence genetics. Besides, given that around a quarter of the population today were alive when overt discrimination and racism was legal and normalized, and we have compelling evidence that previous inequality intergenerationally became current inequality (as previously discussed), we have every reason to focus on addressing environmental causes for racial inequality.
Whether we rely on empirical experimental evidence or evaluate temporal precedence, it’s clear that the origin of racial inequality is historical and current discrimination. In view of all the facts, there is not a solid basis to argue that somehow the black community is ultimately to blame for their lower position on the social and economic hierarchy. Racial discrimination was codified into law for 87% of the relevant history for US citizens. In the remaining 13% of history, progress towards racial inequality has been slow. The intergenerational transmission of both tangible and intangible resources has ensured that those who benefited from subjugation and discrimination continue to win the relay race of life in the US. Likewise, the descendants of those who suffered through this history remain behind with little recourse but to continue to struggle for equality hopefully with the allyship of people from other racial groups who understand the need for racial equality.
Conservatives and liberals offer differing views on the causes of racial inequality. What does the experimental evidence say?
The Black Lives Matter protests and associated high profile cases of police violence against unarmed Black men has catalyzed a conversation about race in the US. However, the problem of racial inequality extends far beyond policing. Racial inequality has a deep history in the US and despite the struggles in the Civil Rights Era that resulted in (mostly) legal equality, there is still vast inequality between Black and white citizens in practice.
It is hard to overstate just how clear the evidence is for the claim that racial inequality is an ongoing problem in the United States. While there is probably a handful of people who would deny this reality, most people across the political spectrum agree that there is racial inequality. Where people disagree is on the question of why there is racial inequality. There are essentially two competing narratives: 1) “Racial inequality is caused by historical and ongoing discrimination,” or 2) “Racial inequality is due to differences in choices, culture, and/or values.” The former narrative emphasizes that the Black community has been (and continues to be) held back by racism on an individual and systemic basis. The latter narrative emphasizes the legal equality that Blacks and whites share and thus attributes disparities to differences across individuals in each group.
Which of these narratives one endorses is highly correlated with their demographic group. Conservatives (compared to liberals), are more likely to adopt the latter narrative. In other words, they are much less likely to agree that discrimination is the main reason Black people can’t get ahead. Similarly, whites (compared to Black Americans), are much less likely to cite discrimination, lower quality schools, and lack of jobs as the causes of inequality. The polls cited above also show there are similar racial and ideological splits on perceptions of the Black Lives Matter movement. Beyond this polling data, you can find plenty of examples of these narratives emerging out of their respective demographic camps.
In the conservative magazine National Review, attorney Peter Kirsanow argues that “individual behavior, family structure, perverse governmental policies, and culture” are largely ignored when discussing racial inequality. He also claims that “systemic, structural, or institutional racism” are over-emphasized by liberals in a politically convenient ploy. Popular conservative commentator Ben Shapiro echoed this perspective here saying racial inequality, “has nothing to do with race, and everything to do with culture.”
The alternative narrative, that racial inequality is caused by historical and ongoing discrimination, is actually quite widespread in the news media even within outlets that are somewhat “down the middle”. For example, this USA Today article connects disparities in police violence and coronavirus deaths to systemic racism. The author argues that aspects of racial inequality are “intimately connected” and points to a legacy of discrimination as the cause of current housing disparities between white people and Black people. For a more liberal example, this Mashable article succinctly claims that systemic racism “is everywhere” and also links it to racial disparities related COVID-19 and high profile policing deaths.
The statistics about racial inequality are basically correlations. Being Black is correlated with a variety of disadvantages; being white is correlated with a variety of advantages. So how can we understand what causes these advantages and disadvantages? Well, how do scientists typically establish causation? The best tool scientists have to determine cause and effect is the Randomized Controlled Trial (RCT). In an RCT, researchers randomly assign participants to a treatment condition, where they undergo some sort of intervention, or to a control condition. Since the assignment to condition is random, we can assume that any differences between the treatment and control conditions are the result of the intervention, since without it the groups would be the same. This methodology is the gold standard for investigating the cause of something. However, in many cases, there are practical and ethical reasons for why we cannot do the experiment we would need to do in order to fully establish causality.
As an example, take the assertion that racism is responsible for an academic achievement gap between Black people and white people. This claim could be experimentally tested by exposing white and Black children to racism against their groups, and then testing their academic achievements. We would want to control for other factors, so the children would need to be moved to three isolated communities that are treated identically except for how they are treated in terms of their race. In one community, the white children would be taught about the long history of their subjugation and then be subject to systemic and individual discrimination. In another community the Black kids would get this treatment. In the control, there would be no racial inequality or discrimination. We would test them every year for ten years to see what the effect of racism is on the achievement gap. Clearly, the above example would be an ethical nightmare. There is no way to (ethically) randomly assign the things that are said to cause racial disparities we see in society. We cannot randomly assign people to be white or black, or to be subjected to racism and discrimination, or to have specific values and culture. However, scientists have found ways to conduct ethical experiments to test the effects of discrimination.
For example, consider disparities such that compared to white people, Black people were less likely to be employed, more likely to be in poverty, have about 10% of the net worth of whites, and have half the median income of white people. Is there any experimental evidence that this situation is the result of discrimination? The quick answer is yes. Hiring discrimination occurs when equally qualified Black people are less likely to receive a job offer than their white counterparts. Researchers study this phenomenon through what are called “hiring audit studies”. In these hiring audit studies, researchers respond to job advertisements with 2 job applications that are identical in every way except the race of the applicant (usually using a Black-coded name like “Jamal” vs a white-coded name like “Steve”). In 2017, a meta-analysis representing data from 28 previous hiring audit studies found evidence of racial bias in hiring such that whites receive 36% more callbacks than identically qualified Black people. They also did not find evidence that this level of discrimination had changed over the last 25 years. Worse, these researchers also found that discrimination doesn’t stop at callbacks, even after getting callbacks, black applicants face further discrimination. These experiments demonstrate that discrimination has been happening for the last few decades and is currently ongoing, and it is keeping qualified Black people out of work.
Over this same period of time, dozens of similar audit studies have been completed to detect housing discrimination, where Black prospective home-buyers or renters are denied housing while identically qualified white buyers or renters are welcomed to the neighborhood. In these studies, there are white and Black auditors who submit housing applications with identical information, except the person submitting the application is either Black or white. Often, the auditors are even trained to give the same responses during interactions with realtors. Again, scientists here try to control for every other conceivable factor besides race. In a meta-analysis representing 72 housing audit studies in the US, Canada, and Europe, researchers evaluated the level of housing discrimination since the 70s. During the 70s through the 90s, Black people were about 50% less likely to receive a positive response from a housing application compared to whites. Other studies showed that discrimination decreased after the 90s so that Blacks are only 25% less likely to receive a positive response on a housing application. The most recent estimate shows that Black people today are still about 15% less likely to get those positive responses compared to whites. While it has decreased, this current level of discrimination still represents a significant difference in how equally qualified Black people and white people are treated. Worse still, this decrease has coincided with other forms of housing discrimination such as on Airbnb where applications from accounts with Black names are 16% less likely to be accepted relative to identical white accounts. Homeownership is an effective way of building wealth, particularly for low-income and minority households, so housing discrimination has likely had important downstream effects that have contributed to economic inequality across the generations.
Economic discrimination between equally qualified Black and white people is found in a variety of domains, such as car purchasing, getting home insurance, getting a mortgage, and even hailing a taxi! The discrimination Black Americans face is sickening–literally. A 2015 meta-analysis documented that experiences with discrimination and racism in day-to-day life predicts poorer health for Black people. Data taken from 293 studies showed that reported racism predicted both poorer mental and physical health. Even within the doctor’s office, patients cannot escape the effects of racial discrimination. An audit-style study was done with physicians making recommendations about Black and white patients portrayed by actors with identical histories. Black patients were less likely to be referred for potentially life-saving treatment compared to whites with the same clinical presentation. Similar audit work has found racial discrimination towards middle class Black patients in the mental health context. Doctors have been found to harbor a racial bias that Black people are less sensitive to pain (which is likely the opposite of what is true) and thus under-prescribe pain medication to Black patients. But the effects of bias extend beyond just pain treatment. A 2015 systematic review found that racial bias of medical professionals predicts racial disparities in treatment decisions, treatment adherence, patient-provider interactions, and ultimately patient health.
The evidence is clear*: discrimination does indeed cause racial disparities. It’s important to recognize that these studies demonstrate discrimination between otherwise identical people. In the audit studies I reviewed above Black people weren’t discriminated against for being poor, or uneducated, or having a criminal background. All of that is controlled for in these studies. These studies demonstrate in no uncertain terms that Black Americans in the modern era are being discriminated against simply because of their race. As discussed above, racial discrimination accounts for some significant portion of disparities in employment, income, wealth, housing, transportation, and medical treatment. Black people are even discriminated against in the primary domain they have to meaningfully influence the policies that could change this situation: voting.
But, what about the conservative position that individual factors cause racial disparities? We run into a bit of a problem at this point; while researchers have cleverly devised a way to experimentally measure the effects of discrimination through audit studies, there is no way of auditing the effects of culture, choices, motivation and/or values. To credit the conservative position, psychologists study individual differences in choices, cultural orientation, values, or behavior, and we know that these things play a role in success. But again, this is correlational. How do we know if these individual factors play a causal role in racial inequality?
Well, in some sense this topic is at the center of a lot of academic research. Researchers in psychology often cannot experimentally change the systematic factors related to racial disparities (like policy-makers could), so they come up with interventions to influence characteristics of individuals to help alleviate gaps. For example, Black students who enter college often do not feel a sense of belonging and this lack of perceived belonging is linked to worse academic outcomes for Black students compared with white students. Researchers designed an intervention where participants read stories from other students that encouraged participants to think about belonging as something that develops over time and strengthens as you make connections with students and faculty. This simple one-time intervention was replicated across a wide variety of schools and resulted in a 31-40% decrease in the achievement gap between advantaged and disadvantaged students.
At the heart of this approach is seeing individual differences as a component of a recursive cycle, where disadvantage facilitates the development of tendencies (such as a lack of belonging and the resulting vulnerability to failure or academic disengagement) that maintain or exacerbate disadvantage (which reinforce negative tendencies, etc). This cycle means that something like feeling you don’t belong is both a result and cause of racial inequality. This theory has led to wonderful scientific findings! For example, there was a 2009 intervention where students participated in a series of writing tasks to reflect on their values. In the task, students wrote about the personal importance of a self-defining value. This simple task in early seventh grade resulted in Black students having a stronger belief in themselves to fit in and succeed in school. These changes in the psychological orientation of students accounted for a significant decrease in the white/Black achievement gap by 8th grade graduation. There are plenty more examples of these types of interventions throughout psychology.
Thus, the conservative viewpoint is partly correct: choices, values, and behavior can lead to differences in terms of who gets into college, who succeeds academically, and who becomes successful. I suspect most liberals and academics would agree with this view but do not agree that this view should be used to dismiss discrimination and systemic problems. Racial differences in choices, values, and behavior may help maintain and exacerbate racial inequality but we need to ask, “where do racial differences in choices, values, and behavior come from?” The academic answer is that they emerge from contexts that are deeply related to discrimination in the past and in the present. Furthermore, by understanding the origins of racial differences in behavior we can more effectively develop interventions that mitigate these differences. But it’s important to note that interventions like the belonging intervention are attempts to address the symptoms of racial inequality; they do not deal with inequality at its source by ameliorating historical injustice or correcting current discrimination (as found in the hiring and housing studies discussed above).
Taking in all of the research discussed above, the role of discrimination in racial inequality has such a strong foundation in historical and empirical facts that denying the role of discrimination is to depart from a scientifically informed view. On the other hand, the notion that racial inequality is at least in part due to values, behavior, and choices is true to some extent as well. Indeed, this is at the heart of much of the research about how to close achievement gaps between Black and white students. However, the perspective found in academic journals is communicated in quite different terms compared to some conservative arguments. Scientists and historians know that racial disparities in values, behaviors, choices, and even culture have emerged in a continually discriminatory environment with intergenerational disadvantages that maintained racial inequality (the subject of another article of mine). My investigation suggests that a science-based model of the causes of inequality accepts both narratives as partly true and not mutually exclusive.
If someone uses the argument that individual differences in values, culture, or behavior accounts for racial disparities as a way to deny discrimination as a cause, they are no longer aligned with the scientific evidence; we know discrimination is real, is currently happening, and is part of the story of inequality. If they cite individual differences as a way of blaming disadvantaged groups for their own disadvantage, they are also not aligned with the scientific evidence; we know that many of these individual differences emerge from a historical and current context of inequality that Black communities have had minimal control over. On the other hand, if someone is denying any role for individual differences, they have also departed from the relevant science.
In this era of extreme partisanship and misinformation, it is more important than ever to ensure that our ideological perspectives are tempered and informed by the scientific evidence. The causal story behind racial inequality is extremely complex; I have barely scratched the surface in this article. We should leave no tool out of our tool box in order to solve the problem of racial inequality. We need people to investigate and study discrimination, the individual differences that account for inequality, the contexts that give rise to the individual differences, and the systematic forces at work. We also need science-based interventions and advocacy to address both the causes and symptoms of racial inequality. The resulting research should guide our thinking about these topics and help us find solutions. That means admitting the interplay between contexts and choices, between decisions and discrimination, and between history and the here-and-now.
It is hard to overstate just how clear the evidence is for the claim that racial inequality is an ongoing problem in the United States. There are many studies documenting the disparities that exist between Blacks and whites in the United States. The following is a list of evidence for the claim that racial inequality is an ongoing problem in the United States. This list is a “living document” that will be regularly updated to incorporate new scientific data as it comes in (or as I become aware of it). Please use this resource to make evidence-based contributions to discussions about racial inequality in the United States.
Also, use the button on the right side of the screen to subscribe to my blog to get notified of my upcoming articles on the causes of racial inequality in the United States. There are compelling scientific reasons to see that racial inequality today is linked to past inequality. There is also compelling evidence from experimental research that current discrimination plays a role in current racial inequality.
18.7% (see table 2 here in 2019) of Black Americans live in poverty, compared to 7.3% of white Americans.
32% of Black American children live in poverty, compared to 11% of white American children.
19.1% of Black households have an inability to obtain adequate nutritious food, compared to 7.9% of white households (as of 2019).
Black households have about 10% of the median net worth compared to their white counterparts (as of 2016).
Black household median annual income is nearly half that of white households (as of 2018).
15.4% of Black Americans are unemployed, compared to 10.1% white Americans (as of 2020).
1% of fortune 500 company CEOs are Black, despite Black people making up 13% of the American population (as of 2020).
36% of blacks have money in the stock market, compared to 60% of whites (as of 2017).
Typical Black households have 46% of the retirement wealth of typical white households (as of 2016).
47% of Black families own a home, compared to 76% of white families (as of 2nd quarter 2020).
20% of black households are extremely low-income renters, compared to 6% of whites (as of 2019).
40% of the homeless population is Black, despite only representing 13 percent of the general population (as of 2019).
790 in 10,000 loans for black households were foreclosed upon, while only 452 in 10,000 loans for non-Hispanic white households were foreclosed upon (between 2005-2008).
80% of K-12 educators are white, while only 6.3% are Black.
In a 2016 study, Black and white teachers were asked to identify problematic behaviors in a group of children (there were in fact no problematic behaviors in the video). Eye-tracking methods showed that they excessively monitored the black boy in the video.
64% of Black American children attend low income (i.e. Title 1) schools, compared to 33% of white American children.
37% of Black Americans age 18 – 24 enrolled in college in 2018, compared to 42% of whites
22.8% of Black Americans age 25 – 29 graduate from college, compared to 42.1% of white Americans (as of 2017).
42% of Black college students are first generation (i.e. parents didn’t attend or graduate from college), compared to only 28% of white students (as of 2012).
30% of Black and Hispanic students with 3.5 or higher high school GPAs attend community colleges, compared to 22% of white students (as of 2009).
72% of Black students go into debt to pay for their education, compared to 56% of white students (as of 2016).
5% of professors, associated professors, assistance professors, instructors, lecturers, or other faculty are black compared to 70% that are white (as of 2017).
Something to note about police statistics, is there is often not national data that can be used to understand racial disparities. Instead, specific police departments share data with a specific group of researchers. Thus many of the data points below are not taken from the US as a whole.
The likelihood of incarceration was higherfor Black people at every level of wealth compared to the white likelihood.
Black and white Americans sell and use drugs at similar rates, but Black Americans are 2.7 times more likely to be arrested for drug-related offenses (as of 2015).
A 2017 study of 20,000,000 traffic stops in North Carolina revealed that Black drivers are 95% more likely to be stopped (after controlling for amount of driving), and when stopped are 115% more likely to be searched.
A 2017 study of 4.5 million police stops in North Carolina revealed that blacks are more likely to be searched in comparison to whites even when controlling for the rates of carrying contraband.
Minneapolis police use force against black people at 7 times the rate of whites between 2015 and 2020.
Black Americans (from nationally representative data) are 1.7 times more likely to be arrested over a misdemeanor than whites, a trend that is remarkably consistent from 1980 until 2015.
Black Americans (from a national study) were the targets of 39% of SWAT deployments in comparison to whites only making 20% (numbers disproportional to their population).
Blacks were 10% more likely to be detained before their trial compared to whites, while controlling for other factors, including charge seriousness and prior record.
Blacks were 20% more likely to be detained before a misdemeanor trial compared to whites.
Blacks were 9% more likely to have their cases dismissed compared to whites.
For Blacks sentenced for misdemeanors, they are 47% more likely to received custodial offers (i.e. serving reduced time or time-served in pre-trial) as opposed to non-custodial sentences (i.e. community service, probation, and fines) compared to whites.
Blacks were 5% more likely (compared to whites) to be sentenced to prison, after controlling for a range of factors. This can be broken down further into the following:
15% more likely for misdemeanor person offenses.
15% more likely for misdemeanor drug offenses.
14% more likely for felony drug offenses.
In a 2011 study of 5 counties in Texas, California, Florida, and Illinois, Black Americans were held at a higher bail compared to whites, even after controlling for failure to appear in court.
In a 2014 study of 4 counties in Texas, Iowa, New York, and Oregon, Black probationers had higher odds (18 – 39%) of having their probation revoked, even after controlling for available factors (such as crime severity, criminal history, drug/alcohol problems, risk assessment scores, etc.).
A 2016 report shows that 45% of prisoners in solitary confinement (i.e. restricted housing) are black despite making 40% of the prison population.
Using data from 1973 until 2019, defendants were 17 times more likely to receive the death penalty when they are convicted of killing a white victim than when convicted of killing a black victim.
Black people are 5% more likely to receive the death sentence after controlling for culpability (as of 1998).
1,730 per 100,000 (about 1.7%) Black Americans are incarcerated, compared to 270 per 100,000 (about .3%) white Americans. For reference, Blacks make up about 13.4% of the population, compared to 76.3% of the population
In 2013, 18.8% of (nonelderly) Black Americans were uninsured while 12.3% of white Americans were. In the years since the ACA was implemented, this gap has closed a bit such that in 2019, 11.5% of Black and 7.5% of white Americans were uninsured.
11.4 per 1,000 Black American infants die in childbirth, compared to 4.9 per 1,000 white American infants (as of 2015).
The likelihood of a Black mother dying during childbirth is 4-5 times higher than for white women (as of 2016).
Racial/ethnic minorities are 1.5 – 2 times more likely than whites to have most of the major chronic diseases.
Age-adjusted death rate for non-Hispanic Black Americans is 876.1 per 100,000 compared to 753.2 per 100,000 for non-Hispanic white Americans as of 2015.
Black mortality rate in 2015 is 16% higher than white mortality rate (a drop from 33% in 1999).
Black mortality rate for people under 65 is 40% higher than the white mortality rate.
Black American life expectancy is 75.5 years compared to 78.9 years for white Americans as of 2015.
Racial health disparities accounted for over $1 trillion (in 2008 dollars) in direct and indirect costs for the years 2003-2006.
Black people breathe 66% more air pollution from vehicles than white residents (as of 2019).
Black children have lead poisoning levels 2-6 times higher than white children (as of 2010).
Black women of reproductive age have nearly 3 times the level of cadmium poisoning compared to their white counterparts (after controlling for other variables; as of 2006).
Science has long been complicit in the perpetuation of racism. Recently, psychologists confronted the fact that racist science is still being published.
June 19th, 2020 commemorated the 155th anniversary of Juneteenth, a celebration of the day black emancipation was solidified in Texas. More recently, this August will mark the 7th year of nationwide Black Lives Matter protests that swell up around extrajudicial killings of black people by the police. However, concerns about racial disparities and bias are not found only in the streets with protesters, they also occupy the minds of many researchers and fill thousands of pages of research literature every year. Yet, this focus on understanding and alleviating racial injustice is relatively new in the social sciences. Much of the history of social and biological science is mired in racial pseudoscience that was used to justify hundreds of years of slavery and oppression. This past week, psychologists were confronted with the realization that these racist ideas that took root centuries back still bear fruit.
For nearly 400 years, scientists played a pivotal role in the justification and perpetuation of racism. During the Enlightenment, various European scientists proposed that a gulf existed between “the races”. Then, the general scientific consensus that whites were superior to blacks aided and abetted the colonization and devastation of Africa, Australia, and the Americas. Pseudoscience was proffered by most American intellectuals to defend slavery through the majority of the nation’s history. Eugenics, or the idea that we should strengthen humanity by ensuring those with so called “unfavorable genes” do not reproduce, was a popular scientific idea that served as a defense of black mistreatment from the American Revolution through the Civil War and during the Jim Crow era. Eugenics didn’t fall out of favor until people learned of it’s terrible consequences that culminated in the Holocaust.
In the post-WW2 era, these ideas have been reimagined and repackaged with sanitized monikers, such as “race realism” and “racialism”. Eugenics and its more modern intellectual descendants took root largely in research centered around IQ, of the Intelligence Quotient, a measure of intelligence with a somewhat controversial history. This research attempted to “explain” the state of inequality between whites and Blacks. According to publications like Mankind Quarterly, foundations like Pioneer fund, and researchers like Richard Lynn and J. Phillippe Rushton, racial disparities in criminality, educational attainment, and economic success could largely be explained via genetic differences in IQ. This set of ideas is then often used to discourage the implementation of social programs because, as racialist scientists point out, IQ is hard (if not impossible) to change. In the year 2020 much of this is widely denounced (see Nisbett’s book refuting hereditarianism around IQ), but many psychologists are surprised to learn that the legacy of this racist science lives on.
Dr. Gervais noted that the data used in the article predicts that 43% of Africans have an IQ below 70, which represents substantial cognitive disability. In fact the data indicates that the majority of people in countries like Cameroon, Chad, and Guinea have severe cognitive disabilities. Further, he notes that many of the countries do not have any IQ data. Instead, the IQ estimates of those countries were imputed (or statistically generated) using the IQ samples of neighboring countries. Unfortunately, these were not the only problems with the paper.
In a separate Twitter thread, London School of Hygiene and Tropical Medicine demographer Dr. Rebecca Sear elaborated on just how bad the data source for the Psych Science paper was. She describes that even for countries with IQ data, the data is composed of IQ scores from children and unrepresentative samples. For example, Sierra Leone has a population of 7.8 million and the IQ estimate for the whole country is based on 2 samples from only 1 ethnic group with a total sample size of 119 participants. This violates statistical norms around estimating traits about populations from very small numbers of people who may not represent everyone. And remember, this data was then used to impute the IQs of neighboring countries!
These threads point out what many academics would agree are egregious methodologies and statistical analyses . Furthermore, these errors serve to reinforce a racist narrative that Black people are intellectually inferior. However, the authors of the Psych Science paper did not gather this data. The data was originally published by Lynn and Vanhanen in 2002. Coauthor Richard Lynn is the aforementioned assistant editor of racialist science publication Mankind Quarterly who (according to his Wikipedia page) “associated with a network of academics and organizations that promote scientific racism.” Is it surprising, then, that the database Lynn produced would have methodological problems that severely underestimate the IQ of African people?
The conversations around this Psych Science paper demonstrated that the racism in science still bears fruit. It is a hopeful sign that facing significant critiques to their research, the authors of the Psych Science paper released a statement that they will be retracting their paper because they “no longer have confidence in [their] findings” due to “highly questionable data sources.” Scholars on Twitter praise this move for two primary reasons: the conclusions of the studies are not trustworthy given the methodological problems, but also the authors did not fully grapple with the ethical implications of their research. Given the historical role social scientists played in promoting and reinforcing racism, many see it as the ethical responsibility of today’s social scientists to exercise extreme caution to ensure they do not continue to contribute to that history.
The controversy surrounding the Psych Science paper could just be the beginning. A second paper has been retracted that proposes aggression is a function of the melanocortin system and pigmentation (i.e. black people are more aggressive because they are black). Unsurprisingly, this paper also relies on the Lynn dataset. A substantive criticism of the skin-color aggression paper has already been leveled due to it’s cherry-picked evidence, misrepresentations of theory, and nondisclosure of conflicts of interest (i.e. receiving funding from the aforementioned Pioneer Fund). In the wake of these retractions, a question remains: How many more papers reinforcing racist narratives using shoddy methods are out there?
It is a truism that “the first step to solving a problem is knowing it is there”. In my previous article, I described how rising inequality is associated with greater social and health issues. However, with a problem so mired in policy debates like inequality, it’s not enough for researchers to write papers on the subject. What do voters think? There is a growing consensus that the current gap between the rich and poor is problematic; according to Pew 61% of adults agree that there is “too much” inequality. So the public thinks there is too much, but do they understand just how much inequality there is?
A January 2020 CBS report illustrated two important points about the way people handle information about inequality. As mall shoppers skirted around the journalist’s question, “Want to talk about wealth inequality?”, it was clear that most people would rather not think about the topic. Once lured in with the promise of pie and asked to divide America’s wealth among the different classes, it was also made clear that people don’t understand just how unequally sliced the American economy is.
Although the CBS reporter doesn’t mention it, his demonstration was a replication of a classic finding that people severely underestimate just how much inequality there is. In the original 2011 study, Harvard business professor Michael Norton and Duke psychologist Dan Ariely asked participants to estimate the actual wealth distribution in the U.S. and to propose an ideal wealth distribution. They found that people’s estimated and ideal wealth distributions were in stark contrast to the reality.
The richest 20% of the population has 84% of the 98 trillion dollars of wealth in the US, the next richest 20% own about 10% of the wealth, the middle 20% owns about 5%, and the bottom 40% of the population has less than 1% of the wealth. Taken from the 2011 paper, the figure above shows people’s estimation of the wealth distribution was far more equitable than the much bleaker reality and people’s ideal wealth distribution was relatively even more equitable (many people thought the bottom 20% of people should get 10% of the nation’s wealth, for example). Even more interesting is that people were generally in agreement across most demographics. Liberals, conservatives, rich, poor, men, and women all believed wealth was more equitable than in reality, and everybody thought the distribution of wealth should be even more equitable than it is currently. It seems that in this polarizing era, two things unite us: our preference for more equality and our ignorance of the scale of inequality.
Do people “know the problem is there?” People generally seem to be aware that there is too much inequality, probably in no small part due to discussion on the 2020 campaign trail. Despite this, we still underestimate how extreme inequality has become. Maybe this is because the statistical story about magnitude is just too difficult to communicate given that people are bad with large numbers. One question (of many) that remains: What will happen when our collective desire for equality is confronted with a collective realization of just how unequal things are?