To try and answer your technical question: yes and no.
I know why you think this would be easy to do. But this is harder to do than you're thinking because the problem with education was both weighting and sampling.
So, yes, you can play with the weights and get a corrected result. (That's literally just tautological though -- of course in a parameterized model you can wiggle weights around to give the perfect result when you already know what the result should be...)
But, no, that doesn't tell you about what the effect of increasing the sample of these voters would be, and improving sampling is the only real way to get closer to ground truth.
So, some pollsters are sampling larger numbers of less educated people and also weighing those votes differently. But no, we can't know what the combined effect of those two things would've been in 2016. Why? because we can wiggle around the weights post hoc but can't go back in time and resample. And the question about correcting without resampling is kinda uninteresting because the fact that you can get the correct result by just wiggling around weights is literally just a mathematical tautology.
Hope that helps.
nl linked to a paper showing that the analysis I asked for was done and did not have the affect that newacct583 claimed it would have.
Yes, I'm disagreeing; the polls in 2016 reflected the actual outcome very well (they were off, but not unusually far; the entire idea that there was an unusual error is based on overemphasis of fairly new poll-based predictors, especially one at the NYTimes, that painted an extremely high probability of a Clinton win based on a flawed prediction methodology which was separate from any problem with the polls.)
> I was simply asking if it was verified by showing that weighting by education made the 2016 polls align with reality.
If you want to fit a particular single result you can change how you handle any factor and get a perfect match. You'd actually need to test against a different set of real data than you used to determine the adjustment to validate it, not the same single result.
That's not how it works. Weighting education samples to match the population they were sampled from is not fitting a particular result.
> Yes, I'm disagreeing
Then your point is irrelevant to the question I was asking. newacct583 said there was a particular problem with the polls, and I pointed out that if the polls had that particular problem, there is an easy way to check. I asked if that check had been done.
Semantic nitpicking. Clearly, my comment was about how well the polls reflected reality.
> Some of the poll-based forecasts made errors like....
You're making a different statement than the person I'm responding to, who said that the polls didn't align with reality because they did not weight for education. That is something that is easy to verify. I was simply asking if it was verified by showing that weighting by education made the 2016 polls align with reality.