Showing 4 posts tagged academe
LUNCH with a colleague from work should be a time to unwind - the most taxing task being to decide what to eat, drink and choose for dessert. For Rick Mabry and Paul Deiermann it has never been that simple. They can’t think about sharing a pizza, for example, without falling headlong into the mathematics of how to slice it up. “We went to lunch together at least once a week,” says Mabry, recalling the early 1990s when they were both at Louisiana State University, Shreveport. “One of us would bring a notebook, and we’d draw pictures while our food was getting cold.”
The problem that bothered them was this. Suppose the harried waiter cuts the pizza off-centre, but with all the edge-to-edge cuts crossing at a single point, and with the same angle between adjacent cuts. The off-centre cuts mean the slices will not all be the same size, so if two people take turns to take neighbouring slices, will they get equal shares by the time they have gone right round the pizza - and if not, who will get more?
Of course you could estimate the area of each slice, tot them all up and work out each person’s total from that. But these guys are mathematicians, and so that wouldn’t quite do. They wanted to be able to distil the problem down to a few general, provable rules that avoid exact calculations, and that work every time for any circular pizza.
» via New Scientist
Yup, this behavior has long been typical when academics form competing groups, whether the public hears about such groups or not. If you knew how academia worked, this news would not surprise you nor change your opinions on global warming. I’ve never done this stuff, and I’d like to think I wouldn’t, but that is cheap talk since I haven’t had the opportunity. This works as a “scandal” only because of academia’s overly idealistic public image.
It is a shame that academia works this way, and an academia where this stuff didn’t happen would probably be more accurate. But even our flawed academic consensus is usually more accurate than its contrarians, and it is hard to find reliable cheap indicators saying when contrarians are more likely to be right.
Seen at Overcoming Bias