Bigotry
Bigotry can be addressed by removing prejudices associated with subgroups, removing the social schema making it OK to act on these prejudices, filtering individuals who might act on bigotry from positions of power, or creating structures that reward/punish one group more than another to correct for these injustices.
While systems for altering culture and education can be used to fight bigotry, they are only relevant at the level of nation states that have an unhealthy level of control over what their citizens think. We say “unhealthy,” as a government being able to alter its citizens’ opinions on things naturally leads to the politicization of the educational system, which in turn almost always ends with one side “winning” and controlling said brainwashing system.
This leads to a snowballing power consolidation, with more brainwashing giving one party more power, which in turn they use to do even more extreme brainwashing, which destroys the educational system.
But if you are not going to change culture using top-down mandates, what options do you have in the fight against inequality?
The Equilibrium Problem
Research on solving equality at the level of governance becomes excruciating as one quickly realizes the field is so polluted by politics that it has stopped outputting honest results. Several academics and journals have been attacked for publishing research results that fail to align with certain political narratives (for example, research that showed women being hurt by female managers). Many in this field of academia care more about ensuring that their political “team” is seen as being “correct” than actually resolving inequality in a sustainable manner.
One of the greatest problems in combating bigotry in governments that address large areas/populations is what we call the “equilibrium problem.” Essentially bigotry does not exist in all places at the same level, meaning some methods used to address bigotry will result in unfair penalties and advantages in the opposite direction within certain populations.
Let’s use an extremely simple hypothetical example:
- A nation’s population is highly prejudiced against women, on average.
- This “average level of bigotry” could be ameliorated to some extent by applying a modifier to the employment of women that artificially favors female resumes by Y% or frames women as being extra competent or moral in media and education by Z%.
- But any sweeping Y% or Z% intervention that would lead to an “average level of no bigotry when selecting between female and male job candidates across the country” would still subject women to prejudice in areas culturally intolerant toward women while giving women a significant advantage in regions that are culturally more feminist. Women in regions that presented little bigotry against women before the intervention would gain such an advantage from sweeping anti-bigotry interventions that the intervention could even breed resentment and cause an eventual backlash—leaving the situation still bad for women in areas of high discrimination while increasing discrimination in areas of previously low discrimination by stoking resentment among the few who still had discriminatory attitudes in those regions.
We visualize this as the “ocean of bigotry.” We have a false perception that, were the ocean drained, it would reveal a giant, flat plane—yet this is not true. Were the ocean drained, vast mountains and valleys would be revealed. Equality can’t be achieved just by draining the ocean; one needs to then plow down mountains and fill trenches to create a flat seabed.
Imagine “fairness” sits on a numerical spectrum between -10 and 10, with 10 being unfairness in favor of a group, -10 being unfairness against them, and 0 being a state of perfect fairness. Now think of a large country like the United States. Each state within the U.S. will have a different “fairness” number associated with any given group. Any nationally implemented policy that tries to remove negative discrimination against a particular group by just applying a “+X” modifier to every state until every state has a fairness number for that group that is greater than or equal to zero will lead some states to feature extremely high positive discrimination in favor of this group (which technically isn’t fair). If your goal is not the promotion of a specific subgroup but actual fairness, sweeping, national attempts to counteract discrimination are suboptimal.
One who is not serious about addressing the issue will just jump to a proposed system that outlaws advantages based on a given characteristic—but such systems don’t really work. If you just say: “Don’t take race into account when hiring,” certain racial groups will still be disadvantaged due to the minor bigotry they face throughout the day. We don’t believe anyone really believes such policies can remove discrimination in the long run. Thus, such systems are rarely used and only really mentioned as arguments by individuals who prefer inaction on such issues.
While bigoted individuals often make the following point to support doing nothing about bigotry, it is also a factually true statement: Prejudice will be exacerbated in the long run by systematically placing less competent members of discriminated groups in positions they would not have won without positive discrimination.
Imagine if a government intentionally selected a super-competent group of males and a group of average females, then had this mixed gendered group replace news anchors for a year. Or imagine your board of directors replacing the management positions of your company with this group of people. If you didn’t know why they had done this, you would think the government was trying to brainwash you into believing women were stupid when compared to men. Yet, this is functionally what many organizations “fighting” discrimination end up doing. By increasing the status of the discriminated-against group within a single generation one increases the number of people who secretly think that group actually is systematically less competent.
We must be conscious of this effect when designing systems that utilize positive discrimination. Don’t dismiss this truth just because it leads to the “wrong” ultimate conclusion. When positive discrimination is implemented in its most extreme form, the results naturally and logically breed bigotry in a population. Policies with the potential to inspire bigotry where none existed before will not resolve discrimination.
Equilibrium and positive discrimination problems are relevant in state governments as well as nonprofits, family offices, and even corporations. Imagine that professionals with technical backgrounds are underrepresented in a company’s senior management due to its culture and that, to counteract the imbalance, the CEO artificially makes it easier for programmers and other technical employees to rise to senior management positions. Such a change may create the perception that technical employees are less competent at management than other individuals, even if this is factually not true.
So how do you solve the equilibrium problem? The second guess after general positive discrimination one might jump to is to require that leadership bodies have equal representation (e.g., every company’s board must proportionally represent the gender/racial/religious/political/cultural/whatever composition of its stakeholders/nation’s populace/shareholders/whatever). Superficially, this sounds like a good idea. This is the solution that those in power are most likely to select as it earns them the most brownie points with their friends within discriminated classes (i.e., fellow rich and powerful people who also happen to technically be in discriminated classes). That said, in practice it always ends the same.
Specifically, it helps the least vulnerable individuals of a discriminated class while ignoring the vast majority of said class. Obviously, the argument one might use here is that putting unusually privileged members of a discriminated class into positions of power will help all people of that class. Studies show this sometimes—but not always—works. For example, females vastly prefer male managers (this was found in a study of over 60,000 women).[[22]](#_ftn22) Heck, one study of 142 legal secretaries found not a single one preferred female bosses to male bosses.[[23]](#_ftn23)
But stats like this are the exception to the rule. Most studies suggest that it is beneficial for a company to have female managers and that once female managers become fairly common in an organization, more are likely to be hired in the future.[[24]](#_ftn24) (For a great unbiased breakdown of this, see Harvard Business Review’s article: “Who Wants to Work for a Woman?” [[25]](#_ftn25))
One can also argue that even if only the already-privileged members of classes facing discrimination are placed in positions of power through quotas, these quotas still help the non-privileged members of those classes by providing them with role models and blazing trails. People often gravitate toward aspirational figures “like them,” so the existence of a female president, for example, might inspire more young women in that nation to aspire to the role themselves.
The larger point is that creating upper management quotas doesn’t always benefit the groups we wish to elevate. That said, they mostly do, and instances of quotas not being beneficial typically involve issues of perception (i.e., women not wanting to work under other women), so this point can be taken with less emphasis.
The bigger problem with “management quota” systems is that they ignore an obvious truth—inequality within heavily disadvantaged groups is almost always dramatically higher than inequality in a system as a whole. Creating a vacuum that pulls from the top without any mechanism pushing from the bottom only serves to increase inequality within the discriminated group faster than it can resolve their discrimination. This in turn can generate subcultures within these groups that come to see successful peers as “traitors” due to the larger group’s inability to relate to their successful members at a cultural level given the vast divide in lifestyle created by the artificially large inter-group wealth gap.
This inclination to dissociate oneself from people who have a large wealth gap from you is not unique to discriminated populations and is seen in virtually every population. For an extreme example, consider people who think the rich and powerful are secretly lizard people.
Essentially, management quota systems leave the most vulnerable individuals in the dirt while creating a veneer of a solution by empowering those least in need of empowerment. Yet management quotas are favored because the individuals they help most (wealthy, powerful members of a class facing discrimination) are the most likely to be the lens through which a society’s influencers and elite see that class (most rich and powerful people’s friends are also rich and powerful).
If that’s the case, what is the solution? Clearly a solution is needed.
The Pendulum Effect
Not so fast! One devastating subset of the equilibrium problem is the pendulum problem. While equilibrium problem looks at how discrimination can vary across geographies, the pendulum problem looks at how discrimination varies across generations.
Solutions to inequality in a society typically focus on resolving it among youth populations, as their perceptions are most malleable. As such, it seems most pragmatic to declare bankruptcy on bigoted, ossified adult populations and instead erase discrimination among the young. But the same groups that make this choice often continue to measure inequality from population pools sampled across individuals of all age groups—or worse, from exclusively older age groups. For example, a group trying to promote women in business may focus on young people while using the fact that 80-year-old male CEOs are paid more than their female counterparts as a sign their efforts have not gone far enough. When a society is making rapid progress on the topic of inequality, it is possible for that society to reach a point at which, even though on average a group is still discriminated against, certain age ranges have the game rigged massively in their favor.
The problem here comes when the younger demographic ages and the older demographic dies, causing the pendulum of unfair advantage to swing in the opposite direction. To recreate equality, the new, younger generation pushes the pendulum back in the other direction, creating a society oscillating between two extremes that is never fair for any demographic. In the long run, people will suffer if this effect is ignored (while it will lessen with each swing, it is best to prevent the effect to begin with).
The “obvious” solution is just to measure inequality from the youth’s perspective. If one were measuring a female wage gap in such a system, they would only measure it in twenty-somethings.
The reason this is a bad solution is twofold:
- The solution actively abandons anyone over a certain age.
- It would not effectively capture glass ceilings of oppression that do not manifest until later in one’s career. (E.g., If discrimination still existed in the promotion of women to upper management, just measuring how they are doing in their 20s won’t capture this effect.)
While some political writers have alluded to similar trends among nations’ political parties, the pendulum problem as it pertains to fighting discrimination is purely theoretical. Some groups clearly face more discrimination from older populations than younger populations, however there is no apparently organized and incontrovertible instance yet of society pushing back.
One might argue that The Red Pill or GamerGate movements represent examples of this in the case of women, but one could equally argue that they are the last gasps of a dying worldview. Only the future will tell. That said, we mention the pendulum effect as theoretically it makes sense and we suspect that future studies will show it to be real. Were we to design solutions to inequality, we would keep it in mind.
The Solution
Finding a solution to discrimination within a system entails more than imposing simple rules because the amount of discrimination varies within any given system’s hierarchy. Typically, there is less discrimination at the very bottom and very top of a system. Finding the place within a system at which discrimination begins to peak is critical in resolving it.
To double click on what we mean when we say discrimination is lower at the top of a system, we mean this in a relative sense, not in an absolute sense. We are contrasting representation of disadvantaged groups in the highest positions of power with those in positions immediately below the highest level of power, not as a share of the general population. Workplace discrimination is like a filter that appears between every institutional layer of power, but is almost always dramatically more strict in certain layers. For example, in the case of women, research has shown this occurs in their first management positions.
Think of discrimination as being like a clogged pipe, you must identify the point in the pipe where the highest amount of water pressure is absorbed and clear it out. If you only focus on what is going into the pipe or out of it, you solve the wrong problem and in the long run make the situation worse.
In an ideal system, each disadvantaged group’s representation won’t necessarily be in direct proportion to the general population, but there should be no clear signs of bottlenecks—points in the system at which members of a certain group are clearly facing discrimination and being weeded out. This statement comes with two huge caveats.
First, a group of people is less likely to bother joining a system if they believe that system discriminates against them (why enter a pipeline if the pipes are clogged?). Second, sometimes resolving “clogs” in a system requires erasing part of a group’s culture. For example, fewer Muslims are likely to be found working in a sausage factory due to their religious prohibition against pork.
When culture leads people to self-select out of a system (and therefore be poorly represented within it), there is no obvious solution. Both corporate and government systems often make the problem worse by trying to resolve it. The problem of course comes when people blame culture when attempting to explain away what is actually institutional sexism or racism. Unfortunately, we can’t think of a good solution here except to say sometimes one side is right and sometimes the other side is right and one should not assume that disproportionately low representation of a population in a system is due only to discrimination or only to culture.