Not the JVC peer review ring, an actual gambling ring. Credit: China Daily
It's something of a mild joke in science circles - you can figure out who is peer-reviewing your paper by looking for the common author in the citations you 'missed' in your submission.
It was only a matter of time before peer review cabals became an actual strategy somewhere.
They're data mining our children, notes Politico writer Stephanie Simon
. She is talking about education technology startup Knewton
and their use of data analytics to find out how kids think. They want to be able to predict who will struggle with fractions next week.
Exciting, right? Obviously this can be misused and the fact that its potential problems (if they can forecast it, they can manipulate it) are so obvious is why policymakers will address that. The brilliance will be what this sort of capability can do for science.
has issued an expression of concern
about a study it published where Facebook attempted to manipulate the emotions of members by controlling their news feed (10.1073/
pnas.1320040111). But they only bothered to notice and say anything after the outrage after the fact.
So the USA lost to Belgium in the World Cup elimination round. I predicted a win for the US for a simple reason - Belgium, I said, does not know how good it is, whereas the US does.
That's fuzzy logic, right? Well, that is what a lot of sports analysis is, because analysis at its heart relies on subjective scouting. Pundits can pretend to science it up all they want, but they are just doing a Bayes analysis based on real results after they happen. Something like a 68% chance of a victory is useless in the real world unless you are a bookie. It sounds science-y, but sports is a 0 or a 1. Anything in between is a waste of time.
IBM takes data seriously, as seriously as they took Business Machines back in their early days.
They want to be the resource for the blanket concept of The Internet Of Things. Someone will have to do it, because the amount of information available today is overwhelming. When you can produce 250 gigabytes of data an hour, you have too much data.
Or you are onto something big.
How deep is science writing these days? Pretty darn deep.
Way back when Science 2.0 started there were not a lot of great science writers. There were well-known ones, but not great ones. Journalism was in flux and mainstream media didn't respect it much, and scientists respected science journalism even less than media corporations did. The best writers just didn't go into science journalism. One of the reasons that a pillar of the Science 2.0 mission was revamping science 'communication' was because the public had stopped respecting journalists and scientists felt like they got a lot of things wrong. If science journalism couldn't win Pulitzer Prizes, at least it could be accurate and that meant making scientists the journalists.