Understanding the Rationalist Failure to Predict Trump – A Precursor

Update: The follow-up to this must unfortunately be deferred to next Monday. This is a complex subject that may need to be broken up into multiple articles.

This is a precursor to an article that I will publish on Wednesday on the failure of established, rationalistic and even ‘scientific’ techniques to predict Donald Trump’s victory in the US Presidential election. Consider it a rough sketch of ideas that I intend to flesh out in more detail on Wednesday.

I will try to understand the failure of conventional wisdom as espoused by data journalism sites like FiveThirtyEight and the mass media in general by comparing their methods to those used by the small minority that called the election in Trump’s favor on the basis of consistent and well-founded principles. Since it is true that there will always be a minority that will successfully predict a highly unlikely outcome as long as it has some chance of happening, it is important that the members of this minority be both significantly dissimilar in their worldview and base their predictions on sound assumptions and analysis for their success to be more than an instance of chance validating ideology.

This, I will argue, is the case. Having intently studied this minority, I can confidently say that in spite of their wildly divergent Weltanschaaungs, these ‘prophets’ did in fact share a common understanding of the Trump phenomenon that provided far better predictive power than that available to conventional news outlets. And they weren’t simply contrarians hitching their wagons onto the ‘outsider’ trope that gained acceptance after the shock Brexit vote. Some of them had locked in their predictions before Brexit – right when Trump announced his candidacy.

As Trump’s presidency becomes normalized for us now, let us not forget how during the campaign he was described at various times the next Hitler, a sexual predator, a KKK enthusiast, a Republican McGovern, etc. That is to say, even though it was accepted that being an anti-Establishment outsider in this election was politically advantageous, it was also understood that Trump’s political untenability and despicable antics would neutralize that advantage entirely. Thus, the outsider meme was hardly sufficient as a basis for an argument, which if defeated, would damage the image of those who were on the wrong side of it irreparably. Predicting something is not the same as wanting it to happen.

So why is it important to understand why they were so successful in their predictions while almost everyone else who mattered wasn’t? On one level this sounds like a ridiculous question if we consider that Trump’s success was the biggest this-can’t-possibly-happen event of the 21st century, that too at the expense of a candidate that had all the aura of inevitability around her. But this project has mostly to do with my personal dissatisfaction with many after-the-fact explanations that have done the rounds. On an empirical level, they will tell you about how fewer people came out to vote, how there was a surge of hitherto non-voting whites, how Trump swung the Rust Belt, how Hillary’s ground game was poor and a bunch of other statistics. The problem with these explanations is not simply that they are almost entirely descriptive; the more fundamental issue is that they operate on the same analytic plane that proved so useless in the task of critically and objectively evaluating the true nature of the election.

The most reasonable explanation going around is that economic anxiety amplifies racial and intolerant attitudes, which means that it is not sexism, racism and xenophobia alone that caused the Trump presidency but their fatal reaction with the economic decline of much of America’s deindustrialized heartland. It is no secret that the advent of the neoliberal era thirty years ago has raised income inequality across the developed West, concentrated power in an unaccountable technocratic elite and caused the shrinking of the safety net that the ever-increasing reserve army of labor relies on for continued existence. At the same time, no one takes seriously the notion that the post-national state is here and that racism, sexism and xenophobia in their institutionalized forms are a thing of the past. Yet how these phenomena interacted to send a vulgar reality TV star-billionaire to the White House remains a mystery – more specifically, how they overwhelmed the narrative of Trump-as-fascist and Trump-as-sexual-predator in the world’s preeminent liberal democracy.

When we frame the question this way, we are immediately at an explanatory loss. Those of a liberal leaning will point to a fusion of a new alt-right with a primordial American sexism, xenophobia and parochialism, a theory that can not account for the anomalous Trump vote of counties that had twice voted for Obama; it can best rationalize it as a ‘whitelash’ – as if eight years of Obama made people suddenly rediscover their inner racist. Those of a more Marxist-progressive leaning will point to a dissatisfaction with a neoliberal professional-managerial class, of which Clinton was the prime example, that made Trump a Brexit-esque hand grenade of resentment. And those who support Trump will simply point to his business talents, his habit of perpetual ‘winning’ and the vices of a corrupt establishment. All of these theories have more than a grain of truth to them (yes, even that of the Trump supporters) but by themselves they explain only a part of the story and taken together they either overlap or cancel each other out.

Thus, we know ‘how’ Trump happened, but not so clearly – and definitely not indisputably – ‘why’. It might be more useful to treat these diverging explanations not as expositions but as masks – as conscious rationalizations of subconscious inclinations that most of us would rather not admit. As stories we choose to believe because they help us most in making sense of the world.

This is a problem with rational discourse that Alasdair MacIntyre identified in his seminal After Virtue – that contemporary moral debate has become interminable and arguments irreconciliable because rationality has emptied out any notion of authority from moral statements. We can find a reason to justify almost any position and contests between positions – Presidential elections, for example – invariably become a power struggle between conflicting rationalizations. I will have much more to say about After Virtue on Wednesday because MacIntyre provides a very useful framework from which to undertake this comparison between predictive methodologies.

If none of these stories can be universal explanations of Trump’s success – if they are rationalizations that evolve from our dispositions and help us maintain our view of the world – then we can’t choose amongst them on the basis of independent rational criteria. Their worth will have to be evaluated by how well they fit the actual data and how well they can predict the future. While only time will tell which one succeeds on those terms, it is worth considering an alternative schema that one might suspect was more successful precisely because it lay beyond the plane of conventional rational discourse.

On Wednesday, I will use as my starting point the writings of an anthropologist, a cartoonist, a Professor of Political Economy and some others who showed a striking similarity in their analytic framework and certainty about Trump. I will be contrasting their views with those of FiveThirtyEight and other news sources, especially their post-election inquiries of ‘what went wrong’. I want to make it clear that by grouping them this way, I don’t suggest that they share any basic ideological beliefs that they haven’t explicitly stated or that they fundamentally oppose each other on anything other than an analytic level. It is only their methods that interest me. More on Wednesday.


Disclaimer: I don’t pretend to any sophisticated knowledge about political analysis and data journalism. I am approaching this project as a student, as someone who wants to understand, not as someone looking to make a point – mostly because I don’t know enough to make one.


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