Cause and Effect and the Campaign of 2016

[donna_winchell]

One type of analysis that plays a role in argumentation is causal analysis. I started trying to do a causal analysis of some of the arguments in the recent presidential campaign, but the cause-effect relationships soon took on the complexities of the New York subway system. I decided to look only at some of the causal relationships involved in the infamous email controversy. That alone shows that we generally err in assuming that one cause produces only one effect.

Consider the letter that James Comey, Director of the FBI, sent to Congress on October 28, 2016. It certainly had multiple effects. It sent Trump into a paroxysm of delight and Clinton into a rage.  Both were understandable reactions. What a difference there was when he wrote his second letter on November 6, 2016, announcing that the “new” emails found (on Anthony Weiner’s computer) had been studied and that they reinforced Comey’s original conclusion  that there were no grounds for prosecuting Clinton.  And the effect on the voting public? That depends. For some, neither letter made any difference at all. In many states, voters heard about the first letter, went to vote, and then heard about the second. The first letter had the potential to affect their vote, but they didn’t find out about the second in time. Those in states with no early voting at least had the chance to know about both letters. Many of those who heard Trump’s explanation of the meaning of the first letter went to the polls believing that the investigation into Clinton’s emails had been reopened.

Let’s consider an example of working in the opposite direction, from effect back to cause. Again, a one-to-one correspondence is often an oversimplification. One news commentator pointed out—and I paraphrase—that Comey’s role in the presidential campaign would not have been an issue if Clinton had not done something that warranted an investigation in the first place: use a private email server. So using a private email server was the effect that caused the investigation into her emails, which was the effect that caused Comey to reconsider his conclusion not to recommend that she be prosecuted for wrongdoing, which was the effect that caused the respective reactions from the Trump and Clinton camps—a causal chain.

Clinton’s use of a private server was often given as a reason for not voting for her. I suspect, however, that that was only a contributing factor. More likely a number of different factors went into a decision not to vote for her. By the end of the campaign, critics were poking fun at Trump for responding to every accusation with a reference to Hillary’s emails. He hammered at that reason for not trusting Clinton, but the intensity of his outrage at what he considered to be crimes for which she should be jailed was probably the result of more than the email issue.

Causal analysis is another means of exploring an issue to discover all of the arguments that can be made about it. With enough time, someone could analyze many of the complex reasons that people voted the way they did in 2016. To oversimplify the cause-effect relationships is to cheapen people’s reasons for voting as they did.

Credit: Clinton vs. Trump 2016 by Marco Verch on flickr