Oh, yawn, the "but what about cell phones" thing again?
I think the no-call-backs & single-day bits are relevant too, no?
So long as you can prove either would directly impact the data in a reliably biased way that is not fixable with weighting.
I'm not sure what same day polling would do to introduce game-changing error -- and would certainly not be something visible in their daily tracking poll. You could say that the people who answer phone calls at time x have different demographic data than those who would answer at time y -- and you'd be right, of course -- but again, that's the point of weighting. If you get an unusually high number of housewives and retirees over businessmen in their 40s, you use statistical methods to balance that out.
As for the call back issue -- again, can you say that there's a clear consistent ideological bias in people who answer phones when measured against those who do not answer phones? Or that there's a strong compelling reason why not asking for the person who has the next birthday introduces a statistically significant error?
Silver presents reasons why Rasmussen could be bad without actually showing that those reasons have significant statistical impact. He goes through a lot of (needless and nigh pointless) calculation of who may be reachable when, but he fails to do a comparison of value -- past results of pollsters who use method x against pollsters who use method y.
And I can understand why -- both Rasmussen and SurveyUSA (who uses automated polling very similar to Rasmussen) have fairly strong track records, especially when matched up against some of the "traditional" pollsters like Zogby.