I'm honestly trying to figure out whether you do know what you're talking about and I'm misunderstanding, or you're just spouting jargony nonsense. I'm not saying that to be mean...I'm having trouble telling, and you may be making a great point.
Even if I were to "uncritically accept outliers," I'm not sure why that's mutually exclusive or at tension with accepting that good statistical modeling can sometimes generate counterintuitive results. If anything, the premise behind including outliers, assuming that's what you mean by "uncritically accepting them, is that it's better to throw valid data points (or apparently valid points) together in the pot and hopefully let methodological quirks, sampling error, etc., cancel each other out. I also have no earthly idea what point you're making with the Upshot link.
Polling results are extraordinarily noisy under the best of circumstance. If you want empiricism, simulate an election in which underlying voter intentions remain at 52-48, and commission one poll per day for 100 days, each with a 3 MoE and no nonrandom error. It looks like an EKG in tachycardia, except less regular. Feel free to adjust those trendlines after every new survey, but you're just chasing noise. I'm not an idiot. I know how statistical distributions work
Are you somehow under the impression that Silver is just extrapolating trendlines, and not accounting for the obvious fact that small movements are oftentimes simply fluctuations based on statistical noise? If so,
what do you base this belief on? And, before you ask me on what basis I assume that Silver
isn't tempering the pitch of his trendlines based on the (often-likely) possibility they're simply statistical noise, here's why:
1. Because that would require assuming Silver selectively doesn't account for margin of error and the likelihood of statistical noise in this component of his model, while he frequently writes about this elsewhere, and accounts for much more complex "unknown unknowns" like the historical probability of systematic polling error.
2. Because this would make no sense in light of his claim that there's empirical basis to his trendline adjustments model, unless you're arguing that his data set of past trendlines vs. final outcomes coincidentally happened to match the modeling he's now doing that you deem overly aggressive.
Being that neither of those seem particularly plausible to me, I don't think I can agree with the assumptions you seem to be making about Silver's model.
Differential nonresponse is an interesting topic, and I have some thoughts on Silver's approach to it. I don't have time to write them out now. (Trust me -- this isn't a dodge. Look at my post history. I'm a dork and would do it!)
I'm a staunch opponent of overfitting and complex models meant to hide weak logic. I just don't think that all complication is inedible number garnish.
