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July 18, 2008
Lowe's Law of Diurnal Distribution
Here’s an appropriate topic for a Friday, although at first many of you may think I’ve lost my mind. What would happen if you combed the full text of the experimental sections of the chemistry journals, looking for how long people ran their reactions?
I’m pretty sure that I know what you’d see: there would be a lot of scatter in the short time periods, with some peaks at the various half-hour and hour marks just for convenience. But as you went out into the multiple-hour procedures, I feel sure that you’d see pronounced spikes in the data at around sixteen to twenty hours and again at around 72 hours.
Some readers have doubtless started nodding their heads, having done the math. Those times correspond to "overnight" and "over the weekend", and I'm willing to bet that they're over-represented (and how) in the data set. I'll go on to predict scarce examples in, say, the 14-hour or 38-hour ranges - there's not much way to run a reaction for those intervals and not be in the lab too early in the morning or too late at night.
A second-order prediction is that when such reactions are found, that their origins will skew heavily toward academia rather than industry. And I'm also willing to bet that patent procedures will tend to follow the working-day timelines more than the general literature, for the same reasons. My last higher-order prediction is that the reaction times would not, in fact, obey Benford's Law, as many other data sets of this kind do.
As far as I know, no one's ever done this sort of analysis, but I suppose it would be possible, especially for someone at Chemical Abstracts or at one of the scientific publishers. If someone wants to try it, please let me know what comes out. And if the results follow my predictions, please feel free to refer to the title of this post or something similar. I won't object.
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