Week 5 – Difficulties In Coding

Last post, I talked about how I had watched debates the first time around and observed more frequent and stronger violations from Trump than other candidates in general. After watching debates for the second time, a good deal of that struggle revolved around coming up with stricter definitions by which I could judge whether something constituted a norm violation or not. I’m doing this because part of my conclusions aim to be focused on quantitative recordings of the frequency of norm violations, meaning I’d need an accurate and specific way of deciding that.

One of the norm violations I’m coding for is demonstrably false claims. By this, I mean claims that can be logically and proven false. As a result, one of the extremely tedious processes I had to go through last week was fact-checking. This is particularly difficult because a good deal of times candidates (or even certain politically-motivated websites) will say that an opponent’s claim is deliberately untrue when in reality, they believe a claim is misleading or may promote an argument they disagree with. Charlie Crist often said “That’s not true and you know it” to his opponent, and John Fetterman liked to promote the “Oz rule,” meaning Mehmet Oz was lying. Crist and Fetterman repeated such claims multiple times, yet this was often in an indication of opinions disguised as facts, or sometimes allegations that have some evidence to suggest they may be true, yet have not been proven, or may otherwise be difficult to judge.

For example, one of the statements Fetterman called his opponent out for exhibiting the “Oz Rule” was: “John Fetterman calls fracking a stain on Pennsylvania. He says that he will sign a moratorium to ban its continued use. He’s against pipelines”. In researching this, Fetterman did indeed call for a moratorium a few years ago, but he has since made public comments suggesting a reversal of his position. Since this statement was made in the present tense, it isn’t straightforward to judge if this claim falls victim to the “Oz Rule.” What makes this process more difficult is that many fact-checkers may rate claims as “mostly false” or “partly false,” in addition to judging claims based on the severity of the falsehood. Because I’ve decided that claims need to be demonstrably false for my project, I expect this claim, in addition to many claims that have been ruled “partly false” by my fact-checkers, to not constitute a norm violation.

I plan on spending the next week or so wrestling with the data I have assembled and practicing my presentation. Thank you for reading.