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General Discussion & Feedback => Just Chat! => Topic started by: MarkPawelek on 19/10/2013 20:04:08

Title: Fake, fluff : is this the consequence of "publish or perish"?
Post by: MarkPawelek on 19/10/2013 20:04:08
This leading article in a leading magazine has 300+ comments.

The Economist: How science goes wrong (
Title: Re: Fake, fluff : is this the consequence of "publish or perish"?
Post by: Bored chemist on 19/10/2013 21:26:04
Whatever the merits of the article, the irony of the fact that it is published in the economist is wonderful.
"One handed economist" joke, anyone?
Title: Re: Fake, fluff : is this the consequence of "publish or perish"?
Post by: alancalverd on 20/10/2013 08:49:52
Very few fakes, loads of fluff, in my experience.

A leading computer scientist frets that three-quarters of papers in his subfield are bunk.

Only 75%? That's almost kosher!

The problem isn't just "publish or perish" (though I have to say that pretty well every research proposal from academia that crosses my desk is fatuous, unlikely to produce a convincing result, incoherent, or just plain illiterate - how can I possibly approve a project whose principal investigator can't spell "principle"?). Practising professionals are required to attend Continuous Professional Development in order to justify the existence of their registration bodies, and presenting or listening to conference papers counts heavily in your CPD portfolio. Fine, except that in my principal field of interest, radiation protection, the law of the land changes about every 15 years (after much public debate and several drafts)  and the laws of physics (photons travel in straight lines until they interact with electrons) seem not to have changed since the Big Bang. So I have to listen to children who have just opened their textbooks, or misunderstood some trivial experiment, telling me the same story year after year in order to keep my licence current. And of course the conference proceedings are solemnly printed, bound, published, and added to the dusty heap as though they were important.     

Matters are not helped by do-gooders' insistence that all clinical trials must be published. Obviously a fair proportion won't reveal any startling insights into physiology or anatomy - it would be unethical to run a trial if there was no uncertainty about the outcome - so all sorts of dead ends are submitted for publication. But nobody wants to get a reputation for chasing up blind alleys, so it's natural to put some sort of positive gloss in the paper, even if you have advised the sponsor to scrap the product. 

At last the Dodo said, 'everybody has won, and all must have prizes.' Did Lewis Carroll predict the future of teritary education in Britain? By government edict, over 50% of the population now has a degree or equivalent, and each one of those degrees nowadays has a "research" element leading to a publishable paper or two. But how many are read (except by adoring mothers)?
Title: Re: Fake, fluff : is this the consequence of "publish or perish"?
Post by: SimpleEngineer on 21/10/2013 14:28:21
Funnily enough I have posted a few posts around the exact same concerns shown in that article. How peer review is flawed, which they say is due to the pressure to publish.

Too much fake and fluff is being generated to try and justify the myriad of researchers existence.  As Frankie Boyle once joked.. "Shall we have a crack at curing cancer?" " In a minute Joe, I am just finding out how many fruit pastilles it takes to choke a Kestral"..

Title: Re: Fake, fluff : is this the consequence of "publish or perish"?
Post by: CliffordK on 21/10/2013 22:43:58
There are a few bad apples.  However, I would tend to agree that the majority of the papers, at least in reputable journals, are not fakes.  FLUFF???  Maybe.

I think someone posted earlier about plagiarism.  In that case, the plagiarist was essentially using the stolen articles verbatim, but it would be easy enough to rewrite an article without repeating the experiments.  However, I would still think it would be rare.

Some people have said that a good statistician can always find something "significant".  In general the statistical analysis should be decided before starting the research, and if one's hypothesis is not supported, then one shouldn't just dig for something else interesting in the data.