Last year, OC Republican Rep. John Campbell offered a resolution congratulating UC Irvine's men's volleyball team for winning the national championships. Seems simple enough. Not quite.
Bay Area Congressman George Miller asked House Majority Leader Steny Hoyer of Maryland to stop Campbell's measure from reaching the floor for a vote. The reason? Payback. Miller had introduced a water bill that Campbell eventually helped kill last October. And according to the OC Register, Campbell stopped the measure because Miller didn't back an effort to keep open pumps at the Sacramento Bay Delta Pumping Station.
Campbell recalled confronting Miller over the volleyball team resolution:
"I go up to George on the floor, and I said, 'George, what was the problem?' And he says, 'You voted against my water bill. ... There has to be a penalty for that, and this is the penalty.'"
So, naturally, Campbell did what any snubbed Anteaters-loving politician would do: He got even. On Tuesday, Hoyer proposed a resolution congratulating the University of Maryland's Terps for making the NCAA tourney. Campbell opposed it and delayed the vote by asking for a roll call.
In his floor speech, Campbell said teams that are "just in the playoffs" shouldn't be honored and points to a Washington Post story on the Terps' dismal graduation rate.
Is there a lack of informed consent when a surgeon deliberately lies to a patient about malpractice suits, professional discipline and experience? An appellate court says no. Physicians are free to lie their asses off about lawsuits and disciplinary action taken against them. So much for patients asking questions.
Sanjay Srivastava makes a point that is often forgotten when researchers refer to error variance:
I think we’d all be better off if we remembered that the word “error” refers to an error of a model or theory. On the first day of my grad school regression course, Chick Judd wrote on the board: “DATA = MODEL + ERROR”. A short while later he wrote “ERROR = DATA – MODEL.” Error is data that your model cannot explain. Its existence is a sign of the incompleteness of your model. Its ubiquity should be a constant reminder to all scientists to stay humble and open-minded.