All entries for Saturday 04 August 2018
August 04, 2018
Actions have consequences. People do things and, very often, those things cause other things to happen in the world. This sort of intuitively obvious cause-effect relationship is “causation.” One of the ways that we measure causation is by calculating the extent to which two sets of data are related. Health professionals can look at incidence of lung cancer, and count how often it is that someone who is diagnosed with lung cancer is also a smoker. More specifically, if health professionals structured the study this way, smoking and lung cancer would both be “binomial” variables, because they would have “yes” or “no” answers. We would likely test whether the correlation between lung cancer and smoking was statistically significant with a Chi-Square test. It’s also, course, possible to establish correlations between “continuous” variables—e.g., the number of cigarettes a person smokes and the mass of tumors. This could establish a more linear relationship, like as a person smokes more cigarettes, the mass of their tumors increases. In either case, we’d use this correlation as evidence of causation: smoking cigarettes causes, or at least increases the incidence of, lung cancer.
However, in an equally obvious sense, two things can happen independent of each other. For instance, I taught in an English department at a university in Missouri from 2014 to 2017. During those years, the football team won two national chamionships and the basketball team won one. It is possible that the Powerpoint slides I showed to freshmen about argumentation and sentence structure percolated up to the varsity teams and equipped them with critical thinking and reasoning skills that enabled them to outplay their opponents. In which case, to the fans of Northwest Missouri State University football and basketball, you’re welcome. However, I confess that it’s more likely that I had nothing whatsoever to do with these championships. Furthermore, even though across the whole history of the university, there’s a fairly strong correlation between my being on faculty and national championships (in the case of basketball, the university only won a national championship while I was teaching in the English department!), there’s still no causation. Regardless of statistics, we must use a rational perspective on events to determine (and show) that two events which are correlated are also connected. Otherwise, we risk confusing correlation for causation.
In rhetorical analysis, confusing correlation for causation may be called a “false cause” fallacy. An arguer (either intentionally or unintentionally) interprets two events that are correlated as being causally connected. President Trump, potentially committed this fallacy in his January 2, 2018 tweet, where he suggested that he could claim responsibility for 2017 aviation fatality rates:
Since taking office I have been very strict on Commercial Aviation. Good news - it was just reported that there were Zero deaths in 2017, the best and safest year on record!— Donald J. Trump (@realDonaldTrump) January 2, 2018
Merrit Kennedy reported later that day that there were actually two fatal accidents involving turbo-prop planes in 2017, so there is potentially some equivocation in Trimp’s tweet--there were no fatalities on commercial passenger jets. But, the claim that 2017 was the safest year on record is valid.
The issue is whether Trump’s being “very strict on commercial aviation” in the time “since taking office” caused the safe year. In order to show that the correlation between Trump being president and the absence of air traffic fatalities is connected in a causal relationship. To make this claim, we would need to know in what ways Trump has been “very strict on commercial aviation.” Ideally, we could point to a specific event. For instance, if Trump had signed an executive order directing the Federal Aviation Administration to increase penalties on airlines for pilots who fly fatigued, then Trump could claim that greater enforcement of safety regulations had flights to be safer.
It’s not clear that any action taken by Trump during 2017 could have contributed to a increase in passenger air safety. Alternatively, Trump could have a stronger claim to causation if the event of his inauguration corresponsed to a change in airline safety numbers. However, Kennedy quotes an Associated Press report that, at the time of Trump’s tweet, in the United States there had been no air fatalities since 2013 when an Asiana Airlines flight crashed in San Francisco. So, airline safety during Trump’s presidency appears to be a continuation of airline safety during Barrack Obama’s presidency, rather than a consequence of any action by Trump. It seems likely, then, that Trump has committed a false cause fallacy by claiming credit for airline safety as a result of his being “very strict.”
On the other hand, Trump may be indexing some more complex psychological frames. It’s possible that he means for “very strict” and for references to airlines to subconsciously recall his travel ban. In this frame, his tweet about air statistics would actually mean something like:
I signed Executive Order 13780 on March 6, 2017, which banned entry by immigrants under various conditions from Chad, Iran, Libya, North Korea, Somalia, Syria, Venezuela, and Yemen. People traveling on planes from these countries would have committed terrorist attacks by exploding or crashing these planes, thereby causing passenger air fatalities. Because of my Executive Order, these people didn’t fly on planes, and so they did not commit terrorist attacks, and so there were no air fatalities.
I think this may have been what Trump actually meant by the real tweet on Jan. 2, and may have been something like what it encoded for his supporters. While there are clearly other reasoning issues in the hypothetical tweet, it would at least do better to establish that an action caused a consequence, so that correlation is connected to causation. The actual real-world tweet of Jan. 2 doesn’t do this, and thereby commits a false cause fallacy.