By Alexander Perepechko
Published on February 4, 2017
After the 1948 presidential election in the United States, the Chicago Daily Tribune ran with the headline “Dewey Defeats Truman.” Actually, Harry Truman beat the Republican Thomas Dewey. A copy fell into Truman’s hands and he simply smiled at the mistake because the Republican-supporting Chicago Daily Tribune had once referred to him as a nincompoop (Greenslade, 2016). Since that time electoral forecasts have improved dramatically: social scientists and political technologists can now forecast election results with more than 95% certainty. But in 2016 history repeats itself. Mass media, social networks, academics, experts, and analysts in the United States and abroad almost unanimously forecasted the victory of Hillary Clinton in the presidential election. The Democratic presidential nominee signed her autograph on the Newsweek “Madam President” commemorative magazine backstage after a campaign rally on November 7, 2016 in Pittsburgh. 125,000 copies of this magazine are for sale on eBay, Amazon, and similar commercial websites and can be purchased – if you are lucky – for 80-100 American dollars.
The vast majority of predictions failed miserably. American voters and the Electoral College worked against the liberal establishment candidate Hillary Clinton. She was sponsored by Wall Street, part of the IT sector, and some special interests and globalist institutions. Today these same organizations and individuals predict major trouble in the United States because Donald Trump won the election.
Indeed, a few polls and analysts anticipated the victory of Donald Trump, and the independent American filmmaker and writer Michael Moore was one of them. After the election, Moore (2016) acknowledged: “Fire all pundits, predictors, pollsters and anyone else in the media who had a narrative they wouldn’t let go of and refused to listen to or acknowledge what was really going on. Those same bloviators will now tell us we must “heal the divide” and “come together.” They will pull more hooey like that out of their ass in the days to come. Turn them off.” In fact, only two polls consistently showed Trump in the lead—the USC Dornsife/Los Angeles Times and the IBD/TIPP tracking polls.
Results of the 2016 US presidential election are still, in fact, an enigma. Attempts to explain the shocking activities of the Trump administration today will fall short without understanding the election. The reasons he was elected help to explain the development of the current political phenomenon. Was the electoral carnival merely a farce? If the answer is no, how can we explain the outcome of the presidential election in terms of elitology?
A chimera? Or, a valid outcome of risk and uncertainty?
In the previous research paper (parts 1 and 2) I noted that in this world of fundamental uncertainty, risks, and destabilizing forces, it is next to impossible for a social scientist to foresee the consequences of elections. In that paper I suggest that the main political challenge in the United States is that increasing risks in socio-economic development go hand in hand with growing imbalance in elite circulation. I also surmised that special interests took advantage of the presidential candidates’ desire for power. Also, postmodernist media and social networks made open, honest nationwide discussion about the future of this country next to impossible. Indeed, the electoral carnival reached the point that many voters who supported Donald Trump were undercounted in polls because they were rebuffing poll takers’ questions (Flint & Alpert, 2016).
In December 2016 the Laboratory for Social Machines at the Massachusetts Institute of Technology (MIT) Media Lab published several social network maps which explain, to some degree, my assumptions. Scholars involved in the lab’s “Electome Project” studied communication on Twitter during the election. Twitter users are a self-selected subset of people not necessarily representative of America. Nevertheless, the Twitter network has 67 million active monthly users in the United States and is a lively political forum. Scholars used machine learning algorithms to measure all political conversations from June 1 to September 18, 2016, on the following topics: guns, race, immigration, terrorism, employment, seniors and Social Security, the economy, and education. The scholars initially searched for “high-precision” phrases and hashtags (e.g., “2Amendment” and #buildthewall) directly related to guns, immigration or other subjects. These terms were then used to train a computer classification system to increase the pool of possible terms and hashtags (including misspellings) that might relate to the issues (Thompson, 2016). Since new terms and phrases are continually brought into the conversation, the system automatically retrained itself once a week. This is what was found.
1) Trump supporters on Twitter formed a highly insular group when discussing politics (figure 33a). His followers have closed themselves off from supporters of Hillary Clinton, perhaps to avoid inconvenient information.
2) Clinton supporters – institutional mass media users (see Lüders, 2016) who are supposed to be the political discourse’s immune system – often overlapped with Trump supporters (again, see figure 33a). However Clinton-oriented Twitter followers had some political bias (Cox, 2016; Oakwood, 2016).
3) Almost all verified journalists separated themselves from Trump supporters on Twitter and thus denied themselves a natural information flow (figure 33b).
4) Guns (10.05%), race (8.65%), immigration (8.65%), and terrorism (8.3%) were major issues discussed on Twitter (figure 33c). These issues are about philosophical worlds and foundational principles. Together they accounted for about 36% of issues discussed and were discussed much more often than socio-economic issues (jobs, economy, and education), which accounted just for about 16%. Gun rights supporters and gun control supporters live in separate Twitter worlds. Pro-immigration supporters and anti-immigration supporters are also located on opposite ends of the spectrum and are almost completely disconnected. The extremely high level of connectivity among those focused on racial issues suggests both cohesion and insularity of this group. Supporters of Trump’s political stance on terrorism are dispersed along his part of the spectrum and supporters of Clinton’s position on the issue are scattered along her part of the spectrum. These two groups are weakly connected.
5) Trump’s supporters and to a lesser degree Clinton’s followers were able to mobilize themselves into parochial groups by using modern communications and social networks. More than 100 years ago one of the founding fathers of elitology, Robert Michels (1962: 125) from Germany, suggested that difficulty in mobilization is one of the main deficiencies of western democracy. In the 2016 presidential election, American voters challenged this idea. However, even as voters have instant access to more information than ever before, they have segregated themselves into clusters of like-minded people often with little connection to those with different views.
6) When combined with mobilization, the self-segregation indicates the growing trend of political Balkanization – division of a multiracial, multi-religious, or multiethnic state into smaller homogeneous Balkanization is a consequence of cultural conflict (or war) – political fragmentation followed by the breakup of states and their devolution into dictatorship, racial, religious or ethnic cleansing, and civil war…
Figure 33a. Donald Trump and Hillary Clinton supporters live in their own Twitter worlds. (Source: The Electome. The Laboratory for Social Machines at the MIT Media Lab, 2016).
Figure 33b. The media bubble. (Source: The Electome. The Laboratory for Social Machines at the MIT Media Lab, 2016).
Figure 33c. Issues on Twitter. (Source: The Electome. The Laboratory for Social Machines at the MIT Media Lab, 2016).
British elitologists Alasdair Marshall and Marco Guidi (2012) suggested that we study this kind of situations in terms of risk and uncertainty. Risk is regarded as a state of the world and uncertainty is viewed as a state of mind of a decision-maker. To think and act well in the middle of political chaos and wars, a ruler must see things for what they are and see them well (Machiavelli, 2005). This is important today, isn’t it?
Late Modernity is a runaway world with great increases compared to the past in the pace, scope, and profoundness of change. Like the Juggernaut cart (a term used in sociology after Anthony Giddens (1990: 151-154)), mercilessly destructive forces push the world relentlessly forward and almost out of control. This juggernaut intensifies existing risks, multiplies new threats, and jeopardizes our ontological security. In the rapidly changing and increasingly chaotic and dangerous world of late Modernity, complete objectivity (lack of bias, judgment, or prejudice) is almost unachievable. Our failure to resist or steer the juggernaut is related to the high level of uncertainty within expert knowledge and how this knowledge is used in political and social institutions. Liberal social scientists and institutions in the United States often produce ideologically, politically, religiously, or racially biased knowledge. This “post-truth” has increased the uncertainty in American society. Moreover, the American institutional mass media time and again offer propaganda instead of news. In these circumstances, Donald Trump outfought Hillary Clinton. How?
Trump detected the high level of uncertainty within expert knowledge and ignored experts who, he believed, had led citizens off track (Yates & Whiton, 2016). Indeed, political correctness became an impediment to the development of new research methodologies and quantitative techniques in the social sciences. Arcane sects of Marxist, Leninist, Maoist, anarchist, postmodernist, gender and neo-liberal ideologists on campuses lost touch with America. These facts explain, to some degree, why Trump ran an emotional – postmodernist! – campaign. He focused on the emotional appeals of fear, humiliation, “the enemy” that threatens us, and the perceived weakness and incompetence of all around him. He described present conditions as full of risks. When people are anxious and afraid they turn to someone – a “great leader” – who promises certainty, solutions, and strength (Leahy, 2015). Trump bluffed, persuaded, intimidated, flattered, and bribed whomever he was dealing with (Luce, 2016). He acted relentlessly and boldly. Donald Trump, the decider, outmaneuvered Hillary Clinton, the reasoner…
Some observers believe that Trump is an intense realist preoccupied with objective reality. And elitologists link the intense realism to a strategic advantage (see Marshall & Guidi, 2012). Since our risk environment is quickly changing and becoming increasingly dangerous, it is reasonable to expect that the 45th president of the United States has to develop a strategy, continually update this strategy and adapt it to changing conditions. Trump understood this – perhaps intuitively – and “Make America Great Again” emerged as his “strategic” slogan.
These subtleties indicate that theories of elites developed by Vilfredo Pareto, Gaetano Mosca, and Robert Michels work in the time of globalization and late Modernity. These concepts can be used to connect risk and uncertainty in a particular way. In doing so, we might see in a different light the “non-logical” result of the presidential election of 2016.
Awaken Machiavellian intelligence?
Culture and personality form states of mind and furnish humans with strategies for engaging with uncertainty and risk in reliable and predictable ways. According to Vilfredo Pareto (1935), our affective, emotional, and intellectual experience of cultural and personological factors makes up our experience of uncertainty. This experience of uncertainty supports each decision we make, especially when we are actually at risk or when we act as if we are at risk (Marshall & Guidi, 2012). But regardless of our experience, there is always uncertainty pertaining to our motivations, our beliefs about the world, and the best means by which we might pursue our goals. In other words, any change in motivations, beliefs, or means impacts the way in which we act as decision-makers.
A certain set of risks impacts the subjective experience of uncertainty (Marshall & Guidi, 2012). We learn from the consequences of behavior in complex social settings (Byrne, 1997; Byrne & Whiten, 1997; Schmitt & Grammer, 1997; Wilson, Near, & Miller, 1996). In situations that involve danger (ontological insecurity), the consequences are especially important but learning from them is very risky, difficult, and time consuming. The notorious failures of political planning are a good example. In risky situations, beliefs in tradition, imitation, imprinting or even innate knowledge (phylogenetic adaptivity) are more effective mechanisms.
In accordance with elitology, alternating personological and cultural expressions of human nature could have the evolutionary function of placing us within two alternating background sets of risks. Success in politics and society is often promoted by seemingly altruistic, honest, and pro-social behavior. Machiavelli suggested the presence of two alternative expressions of human nature: “[It is useful] to appear merciful, faithful, humane, trustworthy, religious, and to be so; but with his mind disposed in such a way that, should it become necessary not to be so, he will be able and know how to change to the opposite” (Machiavelli, 2005: 61). Here Machiavelli talked about a successful leader. The leader’s strategy of social conduct involves manipulating others for personal gain, often against the other’s interest. Simultaneously, the leader acts to help and cooperate — conventionally seen as an alternative strategy. Machiavelli describes complex social strategies that combine immediate self-interest with unselfishness and altruism as a way to achieve ultimate personal gain. For leaders and elites, these strategies constitute a craft to be mastered to achieve success in politics and society.
Recall that for Machiavelli the ideal leader must be both a fox using the strategy of fraud and a lion relying on the strategy of force. Leaders and elites must use both strategies to successfully negotiate risks and make decisions pertaining to these risks. Note that Machiavellian intelligence has nothing to do with intellectual superiority. In elitology, intellectual superiority is the one with which political leaders have least to do. That is why politicians have rarely defended their rule on the basis of intellectual superiority alone, but rather on the basis of their superiority in character and wealth (Mosca, 1939: 63). Even a record of public service can be less important than character and wealth.
Following Machiavelli, Pareto showed that people have evolved two separate patterns of behavior when living through upswings versus downswings of socio-economic and political cycles (see parts 1 and 2 of my last paper). These patterns have contributed to the development of human nature over evolutionary time. Each pattern corresponds to particular kinds of risk. As we learn these patterns, we are more prepared as a species to face the risks (see Marshall & Guidi, 2012).
Upswings of socio-economic and political cycles are a good time for Pareto’s fox personality, associated with deceitful craft and cunning. Late Modernity in America tends to make this fox narcissistic and even psychopathic. During upswings, risks between competitive individuals are most common. Interactions within complex, fast-paced, social and highly individualized environments are short-lived and guided by relaxed norms.
Downswings are related to an increase in in-group altruism as well as prejudice and suspicion toward out-groups (“others”). During periods of resource scarcity or crisis, risks to social solidarity dominate. This is a good time for Pareto’s lion, which can describe the conservative authoritarian personality.
The phenomenon described here is known as Machiavellian intelligence. When we must act under uncertainty (as a state of mind) with incomplete information about risks and threats (the world is almost out of control in the late modern juggernaut) our “non-logical” conduct follows from a particular belief about the world in conjunction with a particular sentiment, desire or psychic state. This conduct is guided by two permanent sets of assumptions associated with two particular ways of life shaped by evolution. The two specific cultural and personological patterns, developed over time to help us withstand different threats during upswings and downswings of socio-economic and political development, influence our experiences of uncertainty into one of two fixed ways. In a competitive individualist environment a fox can discover snares. In a time of resource scarcity or crisis a lion can terrify the wolves…
These complex and seemingly abstract arguments will look much more entertaining when we apply them to the current situation. In part 2 of this paper the 45th President of the United States will look less enigmatic. When we learn more about the genesis of the 2016 election, we may better understand the current actions of Donald Trump.
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