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Education Science

New Stanford Institute To Target Bad Science 86

ananyo writes "John Ioannidis, the epidemiologist who published an infamous paper entitled 'Why most published research findings are false', has co-founded an institute dedicated to combating sloppy medical studies. The new institute is to focus on irreproducibility, waste in science and publication bias. The institute, called the Meta-Research Innovation Centre or METRICS, will, the Economist reports, 'create a "journal watch" to monitor scientific publishers' work and to shame laggards into better behaviour. And they will spread the message to policymakers, governments and other interested parties, in an effort to stop them making decisions on the basis of flaky studies. All this in the name of the centre's nerdishly valiant mission statement: "Identifying and minimising persistent threats to medical-research quality."'"
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New Stanford Institute To Target Bad Science

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  • by Anonymous Coward on Tuesday March 18, 2014 @03:33PM (#46518785)

    The intention of this effort may appear worthwhile and good, but the result, as predicted, is going to be useless and waste of time, and may do just the contrary to what it claims. The key reason is that, they are addressing a problem where the evil are precisely those powerful people in the so-called top universities such as Stanford itself. Can they target anyone with power that control unlimited resources, yet fabricate data on a daily basis, for their own fame and power, and publish in Science, Nature, or Cell? Do they dare to? If they don't dare to do anything like this, but only target those schools that are lower in the academic ranks and those less privileged people, then what is the sense of doing all this in the first place? Eventually it will be simply another tool by those already powerful to evict those who they don't like, who they think are threats, and who don't knee down to obey their rules. Disgusting.

  • by gstoddart ( 321705 ) on Tuesday March 18, 2014 @04:21PM (#46519195) Homepage

    For instance, there are the innumerable parallel computing papers that use O(N^2) algorithms to show a speedup on a GPU or supercomputer where there exists a serial O(log N) algorithm that runs faster on a PC. (No joke.)

    Except that while there might be some problems which have O(log N) solutions as well as O(N^2) solutions, there are still things which still only have O(N^2) solutions, correct?

    So if you can learn how to solve a known O(N^2) problem better (even if there is a known O(log N) solution), what you learn is still applicable to to other O(N^2) problems for which there isn't a known O(log N) solution.

    I'm not sure what you're describing is evidence of malfeasance, or that they're working on solving a class of solution, and not necessarily that specific problem.

    To me it sounds more like they're probably aware of the O(log N) solution, but that's irrelevant because they're looking at how to use parallelism to address things which are O(N^2), because there's many many of those.

    So much of math comes down to solving an equivalent problem you already know how to solve.

    Maybe they're figuring out how to address a problem which is O(N^2) by one method, so that once they know how to solve it faster with parallelism, they can learn how to solve other problems which nobody has an O(log N) solution for.

    It may not be all about solving that particular problem, but that class of problem. Because mostly it seems like we've never figured out how to do real parallelism except for things which are classed as 'embarassingly parallel' because it already lends itself to breaking it up -- like SETI@Home.

Man is an animal that makes bargains: no other animal does this-- no dog exchanges bones with another. -- Adam Smith