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Comment on The Big Data Brain Drain: Why Science is in Troubleparent

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Ah, but this isn't just a problem with coding. A mechanical or electrical engineer would have been horrified by my vacuum system or electronic circuitry. ;-) When I was in grad school, the mantra was: It only has to work long enough and well enough to produce a result. My experiment was declared a success when I got the MTBF up from a few seconds to a few minutes.

IMO the life sciences are full of a very special kind of stupid wherein computational science is performed by people who could barely pass Calculus I let alone Linear Algebra or Statistics. And this would be harmless except that a lot of what they publish turns out to either be training set-based prediction of the training set or horrifying misapplication of null hypothesis significance testing.

And all that would merely constitute black box ignorance except that often if you try to help them make their work more reproducible or point out that even 32-bit floating point roundoff error can be initially indistinguishable from a bug that makes the results useless, a lot of them become agitated and tune out the possibility of any of this being relevant to their work.

I left academic science for industry over a decade ago because I caught a big shot who then proceeded to threaten me instead of fix what I found.

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