Why science is self-correcting
There's no point in scientific misconduct; it is always found.
Posted Aug 10, 2010
I find cases like this both frustrating and reassuring at the same time.
The frustrating part of cases of misconduct is fairly obvious. As a scientist, all I really have is the integrity of my data. Theories are nice, of course. We create theories to help us to explain patterns of data. But, really, theories are most useful because they help use to develop new questions that we can ask that will help use to collect new data. Our understanding of all facets of the universe from the movements of the planets to the behavior of people is rooted in our ability to collect good data.
And scientists hold a special place in their hearts for people who collected and analyzed good data. Newton may have come up with the laws of motion, but he recognized the importance of previous scientists like Tycho Brahe and Johannes Kepler whose data was crucial in revising our beliefs about the way planets move around the sun. As Newton said, "If I have seen further, it is only by standing on the shoulders of giants."
So, it is frustrating to hear about misconduct that compromises the integrity of the data in the field.
At the same time, cases of misconduct are reassuring. Science is remarkably self-correcting. When we publish papers in scientific journals, we organize our papers in a way that reflects the ideals laid out by Francis Bacon. We give enough of the details about our methods that someone else could repeat the study we are presenting. We present details about the analysis of our data. After a paper is published, authors often make their data available to others who want to do additional analyses of the work.
Ultimately, though, the scientific method is self-correcting. The field is able to separate the good results from the bad fairly quickly. And that is reassuring.
There is probably a lesson in here for fraud in other sectors of the world like the financial community, business, and politics. There is something to be said for allowing others to have access to your data and your methods. But, we can take up that topic another time.
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