The Repudiation of the Elite in the Media and the “Science” of Political Science
“Political Science: Intellectually dissecting the process by which the dishonest lead the uniformed.” ~ Anonymous
During this election cycle, we saw poll, after poll, after poll get it wrong. Dreadfully so. The media made an embarrassment of themselves by proudly proclaiming Trump’s easy defeat, and Hillary’s triumphant victory. Our generation’s version of President Truman holding up the newspaper declaring Dewey the winner of the 1948 Presidential Election is in the form of a now redacted Newsweek Special Edition magazine with a nice picture of Hillary Clinton with the emboldened title “Madam President.” In other words, these people acted as if the polls were representative of reality. In other words, despite the “science” of the polls and the numbers, these people acted on ignorance. Which is an major pet-peeve of mine, actually – when people act on a lack of info, despite knowing that they likely do not have all of it. Ugh. Hate that.
In any case – and in other words – these people were idiots. Or, as Nicholas Nassim Taleb calls them, IYIs – Intellectual Yet Idiots. If that doesn’t encapsulate the American media nicely, I don’t know what does.
But why were the polls wrong?
Because the polls are incapable of predicting anything truly astounding. Truly revelatory. It’s not how they’re designed. They’re designed to reveal things that fit within certain parameters of belief, or predictability. This is exemplified by the backbone of modern statistics, the Gaussian Bell-Curve, which Taleb has excoriated enough that I’m not going to go into it here. (It’s statistics, and I hate statistics).
But when the belief is that the establishment candidate will win – that is to say, a non-outsider, an already involved political player – (and looking at the history of Presidents within the United States, that seems to be the case), then it appears to make sense that someone like Hillary would easily take down somebody like that Trump. It “worked” during the Democratic primaries. The “outsider” in the form of Bernie Sanders lost to the established candidate. Surely the same would hold true during the national election. And if this election were held 100 more times, according to both the law of large numbers and using the Gaussian Bell-Curve model, that is perhaps true.
But the devil is in the details, and those damn outliers that nobody pays attention to (the tail ends of the bell-curve on the left and right) provide some clues. Those little details that the mainstream media elected to ignore were the rise of the alt-right, the populist movements of people like Ron Paul, Gary Johnson, and Bernie Sanders, as well as Trump himself. Ron Paul had sold-out crowds in 2012. They were the same size or even bigger than both Bernie Sanders’ and Trump’s crowds. But the RNC screwed him out of a justified and legitimate chance of nomination (And that rule change has and will continue to come back to bite them). And the Republicans paid dearly for it. The DNC seemingly did very similar things to Bernie Sanders. And this time around, those two candidates had drawn crowds that Hillary couldn’t even pay to keep on pace with. The RNC even got to a point where it stopped providing funds for Trump’s campaign. The Libertarian ticket during the last election (ctrl-f “2012” on that link) and during this election saw historic rises in percentages of people voting for and supporting Gary Johnson.
Those “outliers” don’t seem like outliers much now, do they? The writing has been on the wall since the 2012 election, but the media missed it. And all because of their reliance on a phony statistical model that can’t predict anything truly groundbreaking because it’s not designed to.
I received my Bachelor’s Degree of Political Science in 2015. To receive that degree, you have to study the “scientific” portion of PoliSci, which is called “Political Inquiry.” Political Inquiry is just a fancy way of saying “statistics for political science.” It’s the subject Political Scientists and Professors point to when they claim “See! We’re scientific! We’re doing science and math and stuff!” In talking with my Professor of Political Inquiry, he exclaimed many times how, even during his PhD process, he never once discovered anything not already determined by common sense using political science stats. Not one thing. Because it’s based on the Gaussian model. It’s incapable of it. I sat in class while students asked “So, what are we using this for?” The answer? “To get the degree.”
Needless to stay, I stopped going or very rarely went, and ended up figuring out a way to get out of the second course by taking an additional class related to my minor degree (philosophy). It was a complete waste of time, energy, and the theory it’s based on hurt my rational-leaning brain.
The main weakness, in my opinion, of the Gaussian model, is the fact that it ignores the tail ends of the bell-curve, the outliers. The majority of events will fall under the bell, under realms of predictability. Which is kind of…like “duh.” We should be seeking to learn and understand under what circumstances those outliers occur, which is where the real spice of life happens, for better or worse.
Trump winning the election was an outlier. The bell-curve didn’t predict it. It might’ve resided on the tail end. Therefore, it was ignored. It was outside the realm of conceivable possibility, so it was disregarded. Yet that is precisely where the msm should’ve been looking. But they were so enamored with Hillary, and completely content to not do their jobs, that when it hit, it hit the msm like a ton of bricks. We can prepare for what we can see coming. That isn’t an issue. It’s learning to prepare for the absurd, the inconceivable, that is difficult to do. There are ways to do that, of course. (I highly recommend Taleb’s book, “The Black Swan,” for starters.) But so long as Political “Science” continues to be based off of inadequate statistical models of prediction for major events, it will never be scientific. And it will also never predict anything of value. Not in the way Free-Market Micro-Economics is scientific and predicts things. And certainly not in the way Physics is scientific and predicts things. Not in any meaningful way will Political “Science” ever be scientific. And yet, that’s what these polls were based on. And the media is happy to continue feeding it to you, despite the 2016 Presidential Election proving once and for all how bogus it is.
The subject really should just be changed to “Political Discourse and Theory,” or something like that, and just drop the “Science” moniker altogether. In any case, this election cycle provided the final piece of damning evidence against the usefulness of the Gaussian model in politics, and of the media’s reliance on it to get people the information they’re craving. It really is no wonder that blogs, the alternative-media, even state controlled news media outlets (like RT, or Al-Jazeera) are seen as more reliable, accurate, and trustworthy.