Epistemology of Journalism

There’s been a bit of a debate lately about Nate Silver, the number cruncher at Five Thirty Eight election polls blog.

Silver is a stats guy who plugs the public poll numbers into a computer model that he has developed to give the probability of various scenarios — such as Barack Obama winning the presidential election next Tuesday.

Right now Silver’s model gives an 82.7% likelihood of an Obama victory.

The dust-up is over the fact that many pundits (especially, but not exclusively, right-leaning pundits) think that the race is far closer than this, and indeed, may even be in Romney’s favor at the moment.

These claims are based on the fact that the national polls have Romney and Obama effectively tied, and several have Romney in the lead. Further, many argue that Romney has “momentum” since not too long ago he trailed in the national polls, and now the race is neck-and-neck.

So, do we trust the geeky numbers guy, or do we trust the savvy well-connected pundits?

Mark Coddington has a very nice discussion of the philosophical differences underlying the debate:

Silver’s process — his epistemology — is almost exactly the opposite of this:
Where political journalists’ information is privileged, his is public, coming from poll results that all the rest of us see, too.
Where political journalists’ information is evaluated through a subjective and nebulous professional/cultural sense of judgment, his evaluation is systematic and scientifically based.

There’s lots more there, and in the pieces he links to, including discussion of “savviness” as a jounalistic ideal. Jay Rosen has made the case that journalists pride themselves as being “objective,” above the partisan fray, and as privy to the facts of how things really work (in contrast to the partisan public’s misconceptions of how things work).

We see this too, I’d suggest, in the response of the NYT public editor to Silver’s offer to make a wager (for charity) on the outcome of the election. If Silver’s jounalistic critics are correct that Silver’s odds are off, they shouldn’t mind betting on it, and Silver is willing to put his money behind his numbers.

The NYT editor views this as unseemly, however:

the wager offer is a bad idea – giving ammunition to the critics who want to paint Mr. Silver as a partisan who is trying to sway the outcome.
It’s also inappropriate for a Times journalist.

Notice the sins that Silver is supposedly guilty of here. By being willing to put money on the probabilities he’s calculated he’s opening himself up to partisanship. And (according to the NYT journalism ethos) this is inappropriate for a journalist.

Because journalism isn’t about getting the facts right (according to journalists). It is about being “objective” and being “above the fray” — even, unfortunately, when the fray is about the facts themselves. (Which is an example of the fallacy of false balance.)

Another point mentioned by Coddington is that many people are conflating probabilities with predictions. This brings to mind a little exchange I had with Roger Pielke Jr. last year.

People who downplay the science of climate change also seem to have trouble distinguishing between estimates of probability and predictions.

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2 responses to “Epistemology of Journalism

  1. Because journalism isn’t about getting the facts right (according to journalists). It is about being “objective” and being “above the fray” — even, unfortunately, when the fray is about the facts themselves.

    This is what I find so troubling about journalism today. Truth no longer matters. It is political balance that matters. I probably get more of my news from NPR than from other sources, but they suffer from this same problem.

    There is a place for balance, and that’s in the op-ed pages. But it does not belong in the news itself.

    And a comment on Nate Silver’s numbers:

    When election polls show that one side is favored by 59%, people rightly think of that as a likely landslide. And then they see Nate with 82%. Apparently, they do not understand the huge differences in what is being measured, and this is why they misunderstand Nate. Alas, probability and statistics are poorly understood by the majority of the population.

    • Yeah, that’s a good point. Being 99% sure that one candidate is going to get 51% of the vote is a lot different from predicting that one candidate will get 99% of the vote. People in general are really bad at thinking about probabilities. The Vegas strip stands as testament to this fact.

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