Too much fudge
© 6 Feb 2012 Luther Tychonievich
Licensed under Creative Commons: CC BY-NC-ND 3.0
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Speculations on the trustworth of common knowledge.


“‍Put your best foot forward‍” An odd phrase, used at least as early as 1595 by Shakespeare in King John. When exactly it came to mean “‍make yourself look good‍” instead of “‍move with haste‍” I do not know. is a phrase I hear often in my work as a researcher. The implication here is to be optimistically honest, to cast the truths expressed in the most positive way conscionable. It makes sense; you want to convince people what you have to say is worth hearing, and against the competition of other voices trying to be heard. But it does lead to a perhaps overly-optimistic, selective view of the world.

And then the in-field magazines come along and grab just the juicy bits and spin them into a compelling story. And those stories get grabbed by book writers or more general media outlets and further optimized. And finally, little clips of the simplified and sensationalized stories get shared from person to person.

All of which leads me to wonder, how much of the things I know are actually true? How reliable and repeatable were the original studies? What caveats have been lost before they reached me? How many “‍cannot be excluded as a possibility by our data‍”s have passed through “‍suggests‍” before becoming “‍studies show‍”? How many correlations have been morphed into causations? How many “‍can be explained by‍”s have become “‍the way it works‍”?

And all of that’s assuming honest, well-meaning people at every step and no errors in the original research. But errors happen, and numbers are invented to unscrupulous “‍researchers‍”. There are people with reputations for making up data, but the difficulty in proving such accusations is so high they are rarely publicly challenged. I’ve heard some people assert “‍everyone fudges the numbers.‍” I dearly hope those assertions are wrong.

All of which leads me to wonder, how much of what I know it true? The mathematics I can check, and the simpler observations I can try out, but what of the rest? I suppose most of it has a solid footing, but I dare not trust it all.

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