Not surprisingly lots of close observers of national politics and public affairs have been reflecting deeply on the 2016 Presidential election. The Woodrow Wilson School of Public Affairs has sponsored a series of lectures, which culminate on Wednesday, November 30, at 4:30 p.m. with an appearance by Ana Navarro, above, a Republican strategist, at Dodds Auditorium in Robertson Hall.
A CNN political commentator and lifelong Republican, Navarro was national Hispanic campaign chairwoman for John McCain in 2008, national Hispanic co-chair for Jon Huntsman’s 2012 campaign, and a Jeb Bush supporter in 2016. Navarro made headlines this year when spoke out prior to the election of then Republican nominee, and now president-elect, Donald Trump, and announced she was voting for Hillary Clinton.
For those not attending the lecture, questions can be submitted via Twitter using #woolection16. The event can be viewed online on the Woodrow Wilson School’s Youtube channel.
Another post-election panel will be held Thursday, December 1, at 6 p.m. in McCosh 50 on the university campus. The speaker will be Jamelle Bouie, chief political correspondent for Slate Magazine and a political analyst for CBS News, covering campaigns, elections, and national affairs. Appearing with Bouie will be Sam Wang, professor of neuroscience and founder of the Princeton Election Consortium. (More about Wang below.)
Other prominent political observers have also weighed in on the election.
Frank Newport, editor in chief of the Gallup Organization, based at 502 Carnegie Center, offered a postmortem, published at Gallup.com.
Unlike so many other polling organizations that had miscalculated public opinion in 2016, Gallup, which was founded in Princeton in the 1930s and pioneered both market research and political polls, bowed out of the presidential race polling game. That decision came after the 2012 election, when Gallup’s predictions had called for a close Romney victory instead of the re-election of Obama by a comfortable margin. The company instead turned to polling on issues and conducting market research for clients.
In his post-mortem posted two days after the election, Newport noted several lessons learned from the election.
The first was that the campaign was highly negative, and the voters absorbed the negativity. Gallup polls showed liberals hated Trump and conservatives hated Clinton more than they supported their own candidates. Love, it turned out, did not trump hate. Gallup measured voter enthusiasm as the lowest in the last four elections, and those polls were mirrored in voter turnout that was also the lowest since 2000.
Also Gallup polls showed very few voters thought Trump was qualified to be president. Almost a quarter of his own supporters told pollsters their man lacked “personality and leadership qualities a president should have.” But this perception turned out in some ways to be a positive for the candidate, since voters wanted someone to bring about change.
Another Gallup poll showed that Trump dominated media coverage, with most respondents reporting having heard or seen something about Trump throughout the entire fall and summer, with Clinton only coming into public consciousness near the end of the campaign when the FBI started talking about her E-mails. According to Gallup’s research, most of what voters heard about Clinton was not about her policies or her record, but her E-mails.
In Newport’s view, Trump took advantage of Americans’ loss of faith in the federal government. He further gained an advantage by speaking in broad terms, while Clinton targeted appeals to different subgroups.
And while Gallup is out of the horse race polling, it’s not entirely averse to making predictions. Newport said the fact that Clinton won the popular vote while losing the presidency is sure to strengthen calls to dump the Electoral College:
“Clinton won the popular vote over Trump, and if recent elections are a guide, Clinton’s popular-vote margin over Trump will increase as votes continue to be counted over the next week. Although this election has seen less short-term controversy over the Electoral College system than the 2000 election, the popular-vote winner — then and now — lost because of the state-by-state nature of electoral votes.
“The American public has favored getting rid of the Electoral College system every time Gallup has asked about it, for decades. As Gallup contributor Lance Tarrance explained in his review of the Electoral College system, that’s a tall order, mainly because of the difficult hurdles the Founding Fathers put into place to change the Constitution (and because some people perceive that there are benefits to the current system). But this arcane system of electing a president may once again become a major focus in the months ahead.”
Newport is not the only local figure with a national platform to talk about polls. Princeton Election Consortium writer and Princeton University neuroscientist Sam Wang was one of the most respected election predictors of the past eight years, but like the others, didn’t see the Trump Train coming. Instead, he was left to figure out how his own models had gone wrong. Wang’s predictions of a Clinton victory were based on the assumption that many polls, taken together, would correct for each others’ quirks and inaccuracies, and yield a fairly accurate picture. However, this assumption proved to be incorrect and now he is sorting out why:
As Wang noted in an op ed piece published in the November 19 New York Times:
“Last weekend I ate a cricket on national television. Based on my statistical analysis of presidential polls, I made a bet that if Donald J. Trump won more than 240 Electoral College votes, I would chow down. Like millions of voters in both parties, I was surprised by the outcome. As a consolation, I’d like to learn what went wrong — and to figure out how pollsters might do better when they puzzle over our polarized electorate.
“Data-based websites, from Facebook on down, have a responsibility to convey accurate information. In this regard, I owe an apology to readers of the Princeton Election Consortium, which I publish. My primary purpose was to show people where to put their campaigning energies by revealing which races were on a razor’s edge. I advised my readers to focus on close Senate races in states where the presidential race was also close. But I also reported an extremely high probability that Hillary Clinton would win, which was published by The New York Times alongside its own model.
“Did we lull voters and the news media into a sense of complacency about the election? In hindsight, it would have been better to express Mrs. Clinton’s polling margin as equivalent to a 2.2 percentage point lead — and that the true margin could be higher or lower by several points. That would have better conveyed the race’s uncertainty. . .
“I suggest that we retire the concept of the “undecided” voter. Based on cognitive science, so-called undecided voters might be mentally committed to a choice, but either can’t verbalize it or want to keep it to themselves. We humans are like this in all kinds of domains, from what to have for lunch to whom to marry.
“Indirect approaches like web search data might provide new ways to predict voter behavior. In one particularly interesting example, during the Republican primary season a reader of my website who goes by the initial N. used Google Correlate, a tool that allowed her to find web search terms that showed the same pattern as state polling data. Using those search terms, N. predicted the outcome in unpolled states more accurately than demographic models of the Republican electorate. Social media may also help gauge voter enthusiasm, especially in midterm elections, when turnout is lower and polls are less accurate.
“Unstated preferences can also be revealed by partisan straight-ticket voting, which has reached record highs. On average, partisan Senate and House preferences tracked the presidential race percentage point for percentage point. Such intense party loyalty provides a way to investigate a preference for Mr. Trump without using the word Trump.
“As a scientist, I am committed to learning from my mistakes. Despite this year’s failure, data is still our best resource for predicting events, but it is important to get good data in the first place. This will be on my mind in the spring, when I am teaching a seminar on the application of statistics to public affairs. A key topic will be partisan gerrymandering, which lends itself much better to hard facts like final vote totals, and not prediction. This year’s election will remind me to add a heavy dose of humility to the proceedings.”