This election, we are so often told, is about demographics. Trump and Clinton are not battling for the votes of Americans, but for Latinas, white men, black youth, evangelicals, or gay women with postgraduate degrees. This is reinforced by the analysis of daily polls on websites like FiveThirtyEight and RealClearPolitics. But we must be careful when reading these polls. While demographic breakdowns are compelling, the categories themselves are essentially arbitrary. Forgetting this distinction and misreading polling data can have grave consequences for our republic, shutting down public debate and dehumanizing our neighbors.
If votes are entirely determined by demographic categorization, then the power of human choice is denied.It is very easy to misread a poll. Even professionals, who really ought to know better, can’t avoid it. Consider this story on a recent CBS Poll. The basic numbers show that, following the Democratic National Convention, Hillary Clinton increased her lead over Donald Trump. The rest of the story repeats this information among various demographic groups. Clinton leads among registered voters, while the two are tied among independents. “Leaners”—undecided voters leaning towards one candidate or the other—prefer Clinton. Women prefer Clinton, but men still prefer Trump. Trump leads among whites without a college degree, but Clinton is up amongst college-educated whites.
The story seems to write itself: a lack of education causes one to vote for Donald Trump. But this isn’t useful for anything except generating a cheap political point. There are two rules for reading polls correctly, and this implied story breaks both of them. First we have the old maxim of the statistician: correlation is not causation. This should be obvious. It is true that Alex Rodriguez has never hit a homerun off of a pitcher named Hercules, but the name Hercules does not cause A-Rod’s failure. The correlation is a statistical fluke, nothing more. The second rule is more difficult to grasp: demographics are arbitrary. Voters can be broken down by age, income, race, gender, favorite television genre, and even whether or not they’ve read Harry Potter. But that does not mean that these categories are real in any meaningful sense. For example, according to most of these breakdowns, a 29-year old voter is placed in the same category as an 18-year old and opposed to 30-year olds. But what sense does that make? We can easily imagine a more extreme distinction. Consider two hypothetical voters. One is a successful mid-40s black woman with a PhD in Massachusetts. The other is a young white woman who dropped out of school to marry her high school sweetheart and raise their child. Should both be lumped together as “women voters”?
Encountering these difficulties, we instinctively look for more detailed categories—but even more subtle distinctions are often unhelpful. The CBS Poll implies that whites with a college degree prefer Clinton because of their degree, but the reality is more complex. According to the Bureau of Labor Statistics, workers without out a college degree earn, on average, $400 less each week than their more educated peers. They are also two to three times more likely to be unemployed. Perhaps this income discrepancy explains some of the preference for Trump. Similarly, Red States simply have more workers without college degrees. The ten least educated states in the union are Idaho, Indiana, Oklahoma, Alabama, Nevada, Louisiana, Kentucky, Arkansas, Mississippi, and West Virginia. Nevada is the only one of these states that did not vote for Romney in 2012. Perhaps Trump support is caused by a lack of education, or perhaps voters raised in a state with conservative values are less likely to see the value of a college degree and the associated debt. I don’t know the answer; the data doesn’t provide one. But I do know that the narrative is more complicated than it first appears.
In and of itself, this data is interesting and potentially useful. But when demographics make the jump from describing the body politic to shaping political activity, they become actively harmful. Arguing from demographics, Sen. Charles E. Schumer (D-NY) recently dismissed the importance of working class voters: “For every blue-collar Democrat we will lose in western Pennsylvania, we will pick up two or three moderate Republicans in the suburbs of Philadelphia . . . They are the college-educated Republicans or independents who lean Republican in the suburbs.” In other words, go pound sand, blue-collar Democrats. We don’t need you; we only care about voters who are smart enough to vote for us. This disgraceful use of demographics is bipartisan. Consider the recently struck-down Voting Rights Act of North Carolina. While often portrayed as “simple” racism, the decision of the court is perhaps even more chilling:
Our conclusion does not mean, and we do not suggest, that any member of the General Assembly harbored racial hatred or animosity toward any minority group. But the totality of the circumstances . . . cumulatively and unmistakably reveal that the General Assembly used SL 2013-381 to entrench itself [politically]. It did so by targeting voters who, based on race, were unlikely to vote for the majority party. Even if done for partisan ends, that constituted racial discrimination. (56)
The General Assembly wasn’t intentionally eliminating black votes—they were eliminating dissident votes. Racism is simply a natural byproduct of this sort of demographic maneuvering. Similar sentiments can be seen at the popular level as well. We have all seen Facebook posts and tweets critiquing certain disapproved demographics. A conservative Uncle may post a meme denigrating millennials, or perhaps a cool friend from college dismisses political opponents as “old white men.”
The dangers of this approach are two-fold. The first is that these arbitrary demographic categories can create the things that they describe. This is something that Michel Foucault observed as a surprising byproduct of observation by systems of power. Although his concerns were quite different from ours, he shows how this process works in The History of Sexuality. Writing on homosexuality, Foucault argues that it did not exist before it was defined as a demographic group: “As defined by the ancient civil or canonical codes, sodomy was a category of forbidden acts; their perpetrator was nothing more than the juridical subject of them.” Sodomy was an action, not a character-defining trait. Yet after an 1870 article defined homosexuality, “The nineteenth-century homosexual became a personage, a past, a case history, and a childhood . . . Nothing that went into his total composition was unaffected by his sexuality.” In other words, “The sodomite had been a temporary aberration; the homosexual was now a species” (43).
It is uncomfortably easy to apply this formula to the current fixation on demographic data: “As defined by the ancient civil codes, voting Democrat or Republican was a category of action; the voter was no more than the juridical subject of them.” Yet after the emergence of our modern pollsters, we may now need to say instead, “The Perot voter had been a temporary aberration; the Trumpkin was now a species.” Perhaps this is why recent studies have shown a dramatic rise in partisanship amongst both the public and even within Congress. In fact, it’s even beginning to affect the dating pool.
This dangerous partisanship applies to both sides of the aisle, of course, but it is perhaps easiest to see with the Trump phenomenon. Prominent voices in the media frequently tell us that “Racism, Not Economic Anxiety, Drives Trump Voters.” While this is undoubtedly true for some of Trump’s supporters, unhelpfully conflating the motivations of all Trump voters does nothing but create the very group that Krugman claims to denounce. Poor white voters driven by economic anxiety are now told by Schumer that their votes don’t matter and by Krugman that they are categorically racist. Their non-racial concerns are dismissed because anyone voting for Trump must be racist. “Nothing that goes into the Trump voter’s total composition is unaffected by his vote,” Foucault might say. These voters now face a choice. They can either surrender their self-interest and vote against Trump to prove that they are not racist or they can vote for candidates who appear to listen to them. The so-called Bernie Bros face the same choice: Get in line and vote for Clinton, or else you’re just privileged, racist white men.
Forcing these voters out of the conversation does not eliminate their voice, however. Instead, it creates a new conversation built upon the very things that were rejected by those in power. Those dismissed because their opinion is considered white and racist will create new conversations centered on their white racial identity. The act of rejection is also an act of definition. This is why Israel’s Law of Return, at least since 1970, is partially inspired by the Nuremburg Laws of Nazi Germany (2.1a). Millenials dismissed for their youth will come to criticize their critics for their age. Here we see the reality. Demographics do not exist to provide voters a voice, but rather to serve those in power. They tell candidates who they must embrace and who may be safely ignored.
This danger is compounded when it is then used to reduce messy, complicated humans to easily digestible data points. If votes are entirely determined by demographic categorization, then the power of human choice is denied. Freedom becomes an illusion, because the human will cannot overcome its circumstances. Clinton will win the race, not because she is the better candidate, but because America is racially diverse. Because of this, efforts to persuade political opponents are doomed to failure—why bother arguing with someone who is unable to change his or her mind?
But as Christians and citizens we must resist the fascism of data. Instead of perceiving our opponents—or even our allies—as collections of data points, we need to instead recognize them as individuals. For Christians, there’s no better model for this than Christ himself. When Messiah encountered the woman at the well, he did not ignore her because she was a woman, an adulteress, or a Samaritan. Focus groups would have undoubtedly shown him that any one of those categories was unlikely to listen to him, but he instead approached her as an individual. Remarkably, she listened. Perhaps this is the true lesson of St. Paul’s famous exhortation to the Galatians: “There is neither Jew nor Greek, there is neither slave nor free, there is no male and female.” Humans are people.
This emphasis on individuality carries with it the danger of a sort-of pseudo-Gnosticism, but resisting demographic determination does not mean denying that humans are shaped by different life experiences. Christ does not avoid discussing the Samaritan woman’s experiences. Instead, he directly engages with her status as a Samaritan and even brings up her five husbands. He does not use this information as a means of dismissal, but instead uses this information to continue their conversation. In other words, Christ does not dismiss her on account of her demographics—but he also doesn’t deny that she, as a Samaritan woman, has led a significantly different life from his as a Jewish man. He recognizes her experiences without letting her become another demographic stereotype. This must be our model for resisting demographic determination: Affirm that others are quite different from us, or perhaps, that we are quite different from them. (It seems just as likely that we are the weird and they the norm.) In that affirmation, we can move into discussion seeking to understand these different experiences. Then when we give in and read the latest polling data, we can remember that it is only a snapshot. It does not tell the many thousands of human stories buried underneath the data.
Image by Unspalsh via Pixabay.