Flav's Fav: No Good Men Among the Living
Maiello Hails The Mouse That Roared
In a veer to reality-based elections, Nate's total prediction this time, 49 right last gives us hope that the effects of the chattering class will be diminished next time.
After chumps like Dick Morris blew all credibility (did they have any left?) proclaiming a blowout to be, when any casual glance at the ground games in needed states proved it hoo-hah?
Well, casual glances have never been enough, and while I'm sure reality-challenged bravado will continue, the more specific indicators will allow immediate blowback.
What doesn't look good is the trend to micro-elections, where the rest of us chumps sit it out while the candidates focus on the opinion of 10,000 valuable independent swing voters in 3 truly swing states. Somehow I figure we'll adapt. Maybe.
But the truly big thing with Nate is he ushers back in science into the wooly chambers of the disbelieving class. Yeah, not just teabaggers and creationists - the media is awfully Barbie with its "math is tough" stuff. (they couldn't figure out Bush v. Gore social security plans, they couldn't understand Romney's (lack of a) budget or what Obama did with $700+ in medicare savings - in short, J School makes Drama school look like nuclear scientists).
So Big Data is the new black. Social media will go from soft and fluffy to analytical, projections and visualizations. And hopefully that will trend across polling issues, validating data on topics like climate change, or tracking the number of drone strike casualties this month.
I'm overall not a big fan of policy only by data-based analysis, but in a time where we've grown dumb as a pile of rocks, it's time to get back to basic arithmetic.
Facebook proved in its IPO that aggregation for aggregation's sake is no longer a winner - 30 million Jonah Goldberg's tweeting aids humanity not in the slightest, even if you combine them. That's where Nate's weighting comes in - separating the wheat from the truly useless chaff. Could be brutal - I long to be Big Data's grim reaper.