We talk about molecular population and evolutionary GENETICS and GENOMICS. You know, the caliper measurement of a gene's evolvability in moles.Check out this gem from the London Times:
Fraud may also be good for science, according to Steve Fuller, Professor of Sociology at the University of Warwick. Since most scientific duplicity involves researchers "idealising" results that they probably would eventually have achieved anyway, such fact-fiddling actually oils the wheels of discovery. He even questions whether it should be labelled fraud at all.
Fuller does draw the line at drug studies, where people could be physically harmed if researchers fudged data. But everything else is fair game. Take the recent discovery of the heaviest element (atomic number 118 for those of you scoring at home), which had been "discovered" seven years earlier. Only the previous discovery was bullshit. A lie. A fraud. But Fuller thinks that's a-ok because the element would be was created anyway.
And, in the interest of academic integrity, the connection between Fuller's thesis and the discovery of element 118 was not made by me. Our graduate program secretary pointed this out to me. It's good to have the wheels of the local bureaucracy greased by intelligent folks.
Bonus point: Steve Fuller was an expert witness for the defense (the school board) in the Kitzmiller v. Dover trial. Yup. Nothing like a guy who defended creationism arguing that real scientists don't need real data.
Comments
Posted by: Mustafa Mond, FCD | October 19, 2006 5:17 PM
It's more like taking the governor off the engine of discovery. Sure you may be able to go faster for a bit; but it's not a good idea if you want to reach your destination. One wonders what Steve Fuller thinks experiments are for, seeing as how he doesn't seem to think the actual results are important. He'd fit right in with the Discovery Institute's "Queen of Hearts" school of science.
Posted by: Andrew Wade | October 19, 2006 6:42 PM
Posted by: sparc | October 19, 2006 11:34 PM
No, it absolutely does not "oil the wheels", but rather throws a spanner in them. New "discoveries" which are not based on real data will send other research groups on wild goose chases trying to repeat and verify the claims, thus squandering time and money that could have been put to better use in other efforts.
Besides, you have the "slippery slope effect": where do you draw the line between "idealising" and outright fraud?
Excluding outliers after a rigorous statistical analysis (and preferrably also publishing that analysis) is one thing, disregarding them because they don't fit with the result you "know" you are going to "achieve anyway" is something very different.
Posted by: Thinker | October 20, 2006 7:25 AM