By ann summers
Nate Silver wrote an extensive mea culpa that ostensibly ignored those media industry resources that ESPN had available to study Trump success. Nate’s omitting the multi-modal effects of looking at Trump’s celebrity media reputation and Q-scores as well as assessing the stupidity of his lizard-brained competitors made a conventional quantitative analysis less analytic and more complex.
The problem is not that Nate was being so pundit-like or that he failed in any way as he was in not appreciating the historical and multiple methodologies needed for an analysis. Sabremetrics and Moneyball notwithstanding, studying the John Miller-Barron political phenomenon is more like thinking all rhizomes are magic mushrooms.
Also Americans are idiots since they were able to elect Ronald Reagan among other fools in US history (see Franklin Pierce, Andrew Johnson, and George W. Bush[Nate could have made the same tRump mistakes with 2000 Florida]).
It’s not so much the scientific method as a unnatural method that’s needed when it comes to tehDonald. The real failure is thinking that pundit journalism and data journalism share common rules and measures. Because as the media industry itself has shown, the customer (rube) is always correct.
Cheer up Nate, you can hopefully predict accurately the success of Russian Olympic athletes now that they’ve claimed that they won’t cheat anymore. Or the real disaster when the House of Representatives selects Paul Ryan as the 45th POTUS. What’s now needed: “measures of oomph and importance” (Ziliak & McCloskey 2008)
Since Donald Trump effectively wrapped up the Republican nomination this month, I’ve seen a lot of critical self-assessments from empirically minded journalists — FiveThirtyEight included, twice over — about what they got wrong on Trump. This instinct to be accountable for one’s predictions is good since the conceit of “data journalism,” at least as I see it, is to apply the scientific method to the news. That means observing the world, formulating hypotheses about it, and making those hypotheses falsifiable. (Falsifiability is one of the big reasons we make predictions.1) When those hypotheses fail, you should re-evaluate the evidence before moving on to the next subject. The distinguishing feature of the scientific method is not that it always gets the answer right, but that it fails forward by learning from its mistakes…
1. Our early forecasts of Trump’s nomination chances weren’t based on a statistical model, which may have been most of the problem.
2. Trump’s nomination is just one event, and that makes it hard to judge the accuracy of a probabilistic forecast.
3. The historical evidence clearly suggested that Trump was an underdog, but the sample size probably wasn’t large enough to assign him quite so low a probability of winning.
4. Trump’s nomination is potentially a point in favor of “polls-only” as opposed to “fundamentals” models.
5. There’s a danger in hindsight bias, and in overcorrecting after an unexpected event such as Trump’s nomination…
So when the next Trump-like candidate comes along in 2020 or 2024, might the conventional wisdom overcompensate and overrate his chances? It’s possible Trump will change the Republican Party so much that GOP nominations won’t be the same again. But it might also be that he hasn’t shifted the underlying odds that much. Perhaps once in every 10 tries or so, a party finds a way to royally screw up a nomination process by picking a Trump, a George McGovern or a Barry Goldwater. It may avoid making the same mistake twice — the Republican Party’s immune system will be on high alert against future Trumps — only to create an opening for a candidate who finds a novel strategy that no one is prepared for.
Cases like these are why you should be wary about claims that journalists (data-driven or otherwise) ought to have known better. Very often, it’s hindsight bias, sometimes mixed with cherry-picking17 and — since a lot of people got Trump wrong — occasionally a pinch of hypocrisy.18
Still, it’s probably helpful to have a case like Trump in our collective memories. It’s a reminder that we live in an uncertain world and that both rigor and humility are needed when trying to make sense of it.
According to the most recent YouGov poll, 61 percent of Sanders voters have an unfavorable view of Clinton, against just 38 percent with a favorable one. YouGov has been tracking these numbers for several months,1 and they’ve gradually gotten worse for Clinton
The prospect of a drawn-out Democratic fight is deeply troubling to party leaders who are eager for Mrs. Clinton and House and Senate candidates to turn to attacking Mr. Trump without being diverted by Democratic strife. Mr. Sanders has won nearly 10 million votes, compared to Mrs. Clinton’s 13 million, and Democratic leaders say she needs time to begin courting the young voters, liberals and other Sanders supporters who view her as an ally of corporate and big-money interests…
Mr. Sanders’s street-fighting instincts have been encouraged by his like-minded campaign manager, Jeff Weaver, who has been blistering against the Clinton camp and the party establishment. On Wednesday, he took to CNN to accuse Representative Debbie Wasserman Schultz of Florida, the Democratic national chairwoman, of “throwing shade on the Sanders campaign from the very beginning.”
For weeks, some current and former Sanders campaign workers have privately acknowledged feeling disheartened about Mr. Weaver’s determination to go after the Democratic National Committee, fearing a pitched battle with the party they hope to support in the general election. The intraparty fighting has affected morale, they say, and raised concerns that Mr. Weaver, a longtime Sanders aide who more recently ran a comic book store, was not devoted to achieving Democratic unity. Several described the campaign’s message as having devolved into a near-obsession with perceived conspiracies on the part of Mrs. Clinton’s allies.