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By Comson Cao

It’s difficult to live in the West today and not constantly hear some kind of call for social justice. Claims of racism, sexism, and a billion other ‘-isms’ and ‘-phobias’ abound. Even fairy tales are problematic because they enforce the patriarchy by upholding gender roles, according to my most recent reading in English class. All of these terms express a perception of oppression. Activists believe that unfair treatment or discrimination pervades “the system,” while they see themselves as “the little guy”: helpless, bullied, and taken advantage of by those with power. But is this always the case, or should we avoid taking these narratives at their face value? 

A 2004 study titled “You’re Just Saying That Because I’m a Woman: Stigma Consciousness and Attributions to Discrimination” by Elizabeth C. Pinel had a group of female college students fill out a questionnaire, asking them their thoughts on anti-female bias (i.e. sexism). Their results were then compared to a group which was given a questionnaire about anti-college student bias. They then took part in an interview where they were told their responses would be judged by a male named “Mark.” A portion of each group was told to think about gender bias before the interview. “Mark,” meanwhile, gave the exact same evaluation to all of the subjects. After the interview, the subjects were then asked their thoughts on the interview. The study found that women who had been given the questionnaire about anti-female bias were more likely to perceive Mark’s evaluation of them as being motivated by sexism, while those who had been told to think about gender bias before their interview were even more likely to blame sexism for their evaluation. But since Mark was a “confederate” (i.e. someone who is in on the experiment) and had given the exact same evaluations to all of the subjects, the bias that the women perceived  could not have existed.

Similarly, a 1980 study done by Robert E. Kleck and Angelo Strenta titled “Perceptions of the Impact of Negatively Valued Physical Characteristics on Social Interaction” looked at perceived stigma due to physical appearance or condition. In this experiment, the subjects were told to converse with someone who—they were told—was just another participant, but was in fact a confederate. The subjects were put into three different conditions: the first had the subjects believe that their conversation partner was told that they (the subjects) had epilepsy, the second that they had allergies, and the third had actual makeup applied to create a fake scar. After each interaction, the subjects were asked to rate how the other person treated them. Those who were given the “scar makeup” or “epilepsy” reported greater tension and patronization from their partner. Those subjects also reported that the partner kept a greater distance from them, and that they appeared to have less attraction. Yet the conversation partner was never actually told that the subject had epilepsy nor allergies, nor even the fake scar—which had been removed with a moisturizer without the subjects knowing, prior to the conversation taking place. This perception of stigma existed only in the subjects’ heads, but this was enough to make them feel as though they were treated differently. 

There’s no reason to think that the same couldn’t hold true for other narratives. What about those of racial bias, for instance? In terms of pure “in-group bias,” Zach Goldberg, a Paulson Policy analyst from the Manhattan Institute, plotted responses from the  2018 ANES Pilot Survey which showed how white-Americans have the lowest in-group bias while black-Americans have the highest. To add on to that, L.J. Zigerell, an Associate Professor of Politics and Government at Illinois State University, used reports from the ANES 2020 survey to show that white-Americans, on average, give the most equal ratings to all races, whereas black-Americans give the least equal ratings. 

When it comes to supposed racial bias in moneylending, a 2013 study by Mariela Dal Borgo found that even after controlling for differences in income, age, family size, education, and marital status, black homes had lower saving rates than white homes, which helps explain why even at the same incomes, the credit scores between black and white people are not equal, at the national level. However, even when the credit scores are equal, the scores are worse at predicting loan performance for black households than white ones, as explained in a 2007 report by the Federal Reserve. A more recent 2020 study by Bhutta and Hizmo sees this effect disappear when using  a model that controls for lender effects, credit score, income, and discount points. Doing so indicates no racial bias in borrowers’ expected pay schedules, as well as the fact that the expected revenue generated by a loan does not significantly differ by the race of the borrower. 

Yet another significant narrative is that of racial bias in policing. When it comes to police stops and searches, a 2015 study of the NYPD’s “stop-and-frisk” policy by Coviello and Perisco found that, “after accounting for the fact that different precincts have different baseline rates of arrest conditional on search, African Americans are no longer less likely to be arrested conditional on being stopped.” This is significant because the common narrative—that stop-and-frisk is purely motivated by racial bias against black people—would be true if, per-capita, black people who were stopped were less likely to be arrested (i.e. they’re innocent) than their white counterparts. But if the arrest rates are the same, as the study indicates, it means they’re not being arrested just for being black. Finally, a 2018 study by Cesario et al. looked at data from the FBI’s Summary Report System, the FBI’s National Incident-Based Reporting System, the Bureau of Justice Statistics National Crime Victimization Survey, and the CDC’s WONDER database, and found that once crime was adjusted for, not only were black people not more likely to be killed by the police than white people were based on nearly all the benchmarks used, but in fact, white people were the ones who were actually over-represented in being killed by the police across almost all of the benchmarks. Now, the authors of this paper did mention a “most damning result” which was that when looking at shootings involving object misidentification, even after adjusting for violent crime rates, a disparity against black people was observed. This may indicate a tendency for officers to assume worse intentions for black people than white. However, as the authors themselves noted, due to the extremely small number of actual cases, the high uncertainty means this result should be taken with caution.

Another example of false perceptions would be the ‘minority stress hypothesis,’ which argues that minorities face unique and hostile stressors that result in worse mental health outcomes for them. This doesn’t comport with a 2009 study by Breslau et al. which demonstrates that non-white people report better mental health and fewer mental health problems compared to white people. There’s also data from the CDC which breaks down the suicide rates by race and sex and in both 1997 and 2017, showing that white-Americans had the second highest suicide rates of all the races, behind just American Indians. The suicide rates of all races has increased, with white people and American Indians showing the greatest increase from 1997 to 2017. The minority stress hypothesis, therefore, would only make sense with American Indians, and does not explain the lower suicide rates of other groups.

With regards to gender bias in employment, a recent 2023 meta-analysis by Galos and Coppock purported to show gender bias against women in employment. However, correcting for publication bias (by using a selection model that penalizes p-hacking) causes this effect to disappear. Furthermore, a 2021 retrospective study by the economist Tom Stanley regarding statistical power in research has found that meta-analyses like these are rarely replicable and often produce false positives. Finally, a 2015 study by Williams and Ceci found that female applicants are preferred 2:1 over equally qualified male applicants in STEM, which remains male-dominated. Overall, the evidence for direct sexism in employment seems thin—despite perceptions to the contrary. These should be alarming because it puts into question the reliability of narratives formed on the basis of perception. This can go with any sort of grievance narrative, whether historical or modern.

Truth must be the basis for any sound decision-making on the individual and societal level. Yet it’s not always clear whether or not something is true. Humans are social animals after all—we like to be trusting of each other. Most people neither have the time nor dedication to do deep research on their own, and will just outsource to ‘the experts’ and use the opinion of said ‘experts’ as a heuristic for the truth. Yet these ‘experts’ are often terrible at predicting things. Not only was it shown in Philippe E. Tetlock’s book Expert Political Judgment: How Good Is It? How Can We Know? that the predictive ability of experts is comparable to dart-throwing chimps, but several studies such as one from 2003 by Lecoutre et al., a 2016 one from McShane and Gal, and a 2019 one from Luy et al. found that many misunderstand statistical concepts like p-values, confidence intervals, and t-tests. Furthermore, stories are not evidence. The only way we can hope to make sense of the world with certainty is empirical data. All of this story-telling might be effective rhetorically, but it should not hold up in any meaningful discussion on those issues. The next time you hear another one of these narratives of perceived oppression, whether it’s from school, media, or someone you know, always keep in mind that it’s a narrative, not a fact. There is a very high demand for oppression, but fortunately (or unfortunately, depending on whom you ask), the supply is often too low. It’s worth asking yourself just how much of what you think you know is substantiated, and being willing to ask that question is the first step towards uncovering the truth.

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