The Law of Dismality
Joseph Bottum, the dismal scientist
Jul 2, 2012, Vol. 17, No. 40 • By JOSEPH BOTTUM
Back in the dark ages of superstition and disease, before science brought suffering humanity into our present era of perpetual peace and economic stability, people were very unenlightened. As Harris (2010) and Hitchens (2007) note, it was a dark time. Very dark.
We shouldn’t assume, however, that everyone who lived before us was entirely foolish. Yes, they were all under five feet tall, died at age 39, and smoked unfiltered cigarettes while driving nonelectric cars without seat belts. To examine their bleak lives, however, is to discover that many of them had a kind of prescientific intuition that—when put on a proper scientific foundation—can prove useful, even today.
Take, for example, the curious manner in which bad events seem to clump together. The car gets sideswiped, the sink backs up, the stock market falls, the Yankees win. And somehow it all seems to merge into a dark, amorphous mass of ill luck and ill will. The medieval people who lived in the last century would mark these misery clusters with such sayings as “Waiting for the other shoe to drop,” or “Deaths come in threes,” or “You got to know when to fold ’em.”
Thanks to Dennett (2006), we now understand that bad events are merely random occurrences given apparent meaning by the mechanisms of the physical brain. There exist, however, structured and unstructured forms of randomness, and the old people’s intuition of bad-event bunching has been given new life by the patterns uncovered in statistical analysis.
In my statistical analysis, as it happens, for after years of data collection I am here to announce that I have succeeded where so many earlier researchers failed—discovering a modern, scientific calculation of how adverse events increase our awareness that the universe is going bad. Very bad.
The math is straightforward. I began by entering the data as polynomial fractions in three-dimensional matrices, taking the square root of the determinants, and sorting the results from high to low to find the eigenvector. A few late-night sessions of data smoothing, using inventive techniques developed for climate research at the University of East Anglia (2009), and there it was, clean and simple—my newly discovered Law of Dismality:
The constant upsilon (υ) represents, of course, the famous Despondency Correspondency, first given mathematical form when, according to Runyon (1934), the great equinary algebrist S.T. Gonoph announced, “I long ago come to the conclusion that all life is six-to-five against.” Modern statistical modeling has adjusted the despondency constant somewhat, but for most horse tracks and gubernatorial campaigns, 5/6 remains the best approximation.
Note the marked limits of this result, valid only for 50 or fewer bad events. From 51 to 100, we enter what researchers call the Insensible Valley, where additional badness no longer appreciably increases melancholy—although alcohol consumption continues in geometrical progression. I was unable, unfortunately, to collect data on adversities beyond 100. In the Journal of Statistical Psycho-therapy, Santo and Banks (1997) hypothesize that people suffering more than 100 miseries within the time limits of induced depression either do not exist or are Chicago Cubs fans; in any event, they were unavailable for testing.
I confidently expect the Nobel Prize for this quantification of downheartedness, with the Fields Medal to follow for the mathematical demonstration of the sticky quality of badness and proof that the world is, in fact, going to hell in a hand basket whenever George Clooney gets nominated for an Oscar, Fox cancels Terra Nova, Wisconsin holds an election, and the NHL finals feature the sixth-seeded New Jersey Devils against the eighth-seeded Los Angeles Kings. My local Department of Tourism has already offered me a one-way bus ticket to promote my ideas out of state, and other honors and rewards should arrive shortly.