Esther12
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I actually thought that this was less interesting than some of his other papers which have been highlighted on this forum previously (this could be because I'm not well informed about genetics or the controversies in this area), but it's short and open access so I thought I'd post it up
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3596761/
Also, some parts of it, about the churning out of data which doesn't increase understanding reminds me of the standard CFS papers which get pumped out, like this one I started a thread on yesterday (on parental expectations of their children's IQ): http://forums.phoenixrising.me/inde...rental-expectations-of-their-childs-iq.22629/
I'm sure we all recognise these problems:
I thought that this was a bit interesting on 'merit' in science, and I've been surprised by the willingness to congratulate those researchers who seem simply to have gained the funding to do certain research. I wonder if there's also an important political component to this, with those in positions of social power increasingly able to select those who gain access to funding, and thus become recognised as 'good' scientists. Ioannidis talks about bias, and of course the biases of those with social power will hold more sway than the biases of those in positions of social weakness, but there is also room for a more intentional corruption of the meritocracy of science, with funding allowing for increasing prestige to flow to those who can be 'trusted' to be on-side. It easy to talk in a way which allows others to dismiss you as a conspiracy theorist, but it seems foolish to assume that there is no political interest in promoting those with certain views to positions of scientific authority.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3596761/
Also, some parts of it, about the churning out of data which doesn't increase understanding reminds me of the standard CFS papers which get pumped out, like this one I started a thread on yesterday (on parental expectations of their children's IQ): http://forums.phoenixrising.me/inde...rental-expectations-of-their-childs-iq.22629/
I'm sure we all recognise these problems:
Based on what we have started to surmise empirically, most of these claimed discoveries are likely to be either totally false preliminary observations (Ioannidis, 2005) or substantially exaggerated results (Ioannidis, 2008), a consequence of the extreme multiplicity of the probed data-space, the winner's curse (Zollner and Pritchard, 2007), and other biases. “Negative” results have almost disappeared from many scientific fields, especially those with “softer” measurements and more flexible analytical tools (Fanelli, 2010). Results procured by the most popular research sub-fields seem to have the lowest reliability (Pfeiffer and Hoffman, 2009).
I thought that this was a bit interesting on 'merit' in science, and I've been surprised by the willingness to congratulate those researchers who seem simply to have gained the funding to do certain research. I wonder if there's also an important political component to this, with those in positions of social power increasingly able to select those who gain access to funding, and thus become recognised as 'good' scientists. Ioannidis talks about bias, and of course the biases of those with social power will hold more sway than the biases of those in positions of social weakness, but there is also room for a more intentional corruption of the meritocracy of science, with funding allowing for increasing prestige to flow to those who can be 'trusted' to be on-side. It easy to talk in a way which allows others to dismiss you as a conspiracy theorist, but it seems foolish to assume that there is no political interest in promoting those with certain views to positions of scientific authority.
It seems likely that there is an extraordinary large number of small, weak effects and links (“risks” in epidemiological language), barely discernible from measurement error and diverse potential biases. Single discoveries made in single databases are likely to mean very little, they are mostly a nuisance that propagates confusion in the literature. Exceptions certainly occur, and some strong/large effects may still exist, awaiting discovery. Even then, it is unlikely that the discoverer who hits upon them will have any more merit than the thousands of other researchers who only come across the flooding multitude of weak or false effects. The process of rewarding discoverers claiming large effects (be that with grants, tenure, or Nobel prizes) may eventually become indistinguishable from running a lottery. If we add human nature, biases, and conflicts (Ioannidis, 2011), a lottery system may be even preferable.