Bad data vs False Data

We here at Bad Data Bad would like to note that when we pick studies to criticize, we operate under the assumption that what the studies actually published are accurate, and that most of the mistakes are made in the interpretation or the translation of those findings in to news.

This article from the New York Times last week reminds us that this may not always be a good assumption.

A few fabricated papers have managed to make news headlines over the past few years….the Korean researcher who said he’d cloned a stem cell….the UConn researcher who falsified data in a series of papers on the health benefits of red wine….and a Dutch social scientist who faked entire experiments to get his data.

This is where the scientific principle of replication is supposed to step in, and why it’s always a decent idea to withhold judgement until somebody else can find the same thing the first study did.  Without that, it’s nearly impossible to know if someone falsified their data, without people in their own lab blowing the whistle.

If you’re curious about these retractions, the Retraction Watch blog is a pretty good source for papers that get yanked.

4 thoughts on “Bad data vs False Data

  1. I almost worked for one. I was crushed at the time that I didn't get the cool schizophrenia research job, but they later got busted for fudging some of their data. Pretty big names.

    The main researchers were untouched and still publish. Some smaller fish were fired. I don't know if it is because they were at fault or because they were scapegoats.


  2. You know when my brother was working for the Obama campaign, there was an article he forwarded me that was making the rounds with the young workers of both parties about “how not to be the scapegoat”. One point that made me laugh was something along the lines of “always have an unpredictable/unstable streak, so they'll never be sure if you'll take the hit quietly”. Maybe they saw too much fight in you.


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