U. professor eats bug on live television, discusses polling errors in 2016 election
Professor of molecular biology and founder of the Princeton Election Consortium Samuel Wang devoured a bug Saturday during a live interview with CNN to make good on his promise in the event that president-elect Trump won over 240 electoral votes.
Like polling and predictions industries across the country, Wang had made projections about the race that were nowhere near the eventual election outcomes. The Princeton Election Consortium website gave democratic nominee Hillary Clinton a 99 percent chance of winning. In a previous interview with the ‘Prince,’ Wang even stated that the question of the 2016 election was not about the presidency, but about control over the Senate.
But Wang would like to avoid a mistake of this scale, he said in a statement released to the ‘Prince.’ For the most part, Wang had based his predictions off of state polls, which he believes to be adequate in surveying voter opinion. The method of relying on and borrowing from a variety of state polls practiced by major poll aggregators such as FiveThirtyEight and The Upshot, he explained.
However, this election proved an exception, as state polls understated the Republican-Democrat margin by 4 percentage points in the presidential race. The disparity of nation-wide predictions in the Senate was higher: most polls underestimated the divide by 6 percent, with a margin of error of 2 to 3 percent.
Wang then suggested that pollsters had failed to identify “a hidden tranche of Republican voters.” He attributed this polling error partly to partisanship, claiming that some of the last-minute swings likely arose from “the hardened partisan divide.” He recounted that earlier during the primaries, a fraction of Republican voters had struggled between party loyalty and whether to accept Trump. Ultimately, party loyalty won out, Wang said. He also noted that the decision of FBI director James Comey to reopen the investigation into Clinton in late October played a role in swinging undecided voters.
Connor Pfeiffer ’18, a member of Princeton College Republicans who had worked with polling and data analyses for various political campaigns, had predicted a 322-216 Clinton victory on social media. Similarly to Wang, Pfeiffer noted that state polls across the country made erroneous assumptions about likely voters. Particularly, the state polls underestimated the number of lower-class white voters who would show up at precincts on election day, he said.
Looking into the future, Wang explained that alternative methods, such as social media trends and web search data, must be utilized to capture the leanings of undecided voters.
“Based on cognitive science, these voters might be mentally committed to a choice — they just aren’t able to verbalize it,” Wang said.
Pfeiffer also noted that changes in polling methodologies are increasingly necessary. Specifically, the reliance of pollsters on cell phone surveys, Pfeiffer says, may heavily skew the data against places where many people do not have mobile phones.
The large number of polling errors in this election cycle carried major implications for both the candidates and voters. Like other forecasts, Wang’s prediction of a near-certain Clinton victory led his readers to believe that the election had been settled, Wang said. This was the opposite of the intended effect, which was to encourage activism and greater discussion of policy issues, according to Wang.
Pfeiffer concurred, noting that as Clinton consistently polled 4 to 6 percentage points ahead of Trump nation-wide, an element of complacency dissuaded her from campaigning heavily in places like the Rust Belt. Indeed, Clinton did win the popular vote as polls had predicted, Pfeiffer noted. However, during the last few days leading up to the election, the Republican National Committee continued to devote resources to its “ground game,” particularly in the states that eventually cast electoral votes for Trump.
“My bug-eating promise was, itself, a sensationalist step in the wrong direction,” Wang said.