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sexism

How I Stopped Annoying Women

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In high school I was in love with a girl who had long, dark, very straight hair, brown eyes, a heart-shaped face, and a demur attitude. (Some will say I was not really in love, which is in some sense true. They will say I was merely infatuated, but the fact is, having experienced both infatuation and real love, I can say with some authority that they feel the same. The main difference, as far as I can tell, is that infatuation makes you insane, but real love is always eminently reasonable. But once again, when you’re in the midst of it, insanity seems oh, so reasonable.) We were in the same grade, so we had some classes together. We also attended some of the same religious meetings. Whenever she was near, I was very aware of her presence, and I schemed to be with her and show her attention without seeming to intend it. Crazy, right? At prayer meetings, I would sit next to her, so I could hold her hand during prayers. My prayers were not exceptionally spiritual, but I did make a number of extravagant promises to God which I have since forgotten. He probably still chuckles over them.

Girls did not flock around me. In fact, they avoided me as if I had cooties. With the advantage of hindsight, I know now that in my teens I was uncommonly ugly and socially awkward. It would be hard to imagine a combination more deadly to incipient romance. I lacked both grace and good looks. I was also naive. All I had going for me was an impressive grasp of calculus—not a trait over which many girls were known to swoon.

After high school I spent a decade with my heart on my sleeve, always ready to be in love with any young woman who was civil to me. If she were more than civil—if she flirted even in the most desultory fashion—I was instantly smitten and made myself intolerable until she utterly spurned my affections. This happened more than once. Possibly more than 5 times. It is still painfully embarrassing to contemplate.

As I grew older, despite remaining absurdly naive, my physiognomy changed. I became more or less average-looking and acquired enough social grace to pass for an ordinary guy. By the time I met the woman who is now my wife, I effortlessly and unwittingly impressed her with my erudition and aplomb. But she was different, too, from the kind of woman who usually attracted me. She was not demur. She was vivacious. She acted as if life were a present she was just about to unwrap. She had firecracker eyes, and she was infectiously alive. She dragged me out of my woebegone stupor and loved me unflinchingly.

These old bones live to learn her wanton ways:
(I measure time by how a body sways).
Theodore Roethke

Suffice it to say, I stopped annoying all woman and began to annoy just one. (At least, I think I stopped. One can never be entirely sure.) For some reason I have yet to grasp, she considers knowing me a privilege for which a little annoyance is not too steep a price.

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Meaningless Statistics

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Once again the Minnesota Department of Transportation is putting the word out that drunk drivers cause 1 in 4 traffic deaths. I begin with this example of a meaningless statistic, not because it is especially egregious, but because it exemplifies what makes statistics meaningless.

Of course, it is not entirely meaningless. We all have a gut feeling that drunk drivers do not drive 1 out of 4 miles driven in America. We strongly suspect that the vast majority of our fellow travelers are not drunk even at 1:00 AM. So it doesn’t take much thought to realize that 1 out of 4 traffic deaths is out of all proportion to the number of miles drunk drivers actually drive. In fact, the National Highway Traffic Safety Administration estimates that drunk drivers drive 1 out of every 140 miles driven on America’s highways. So drivers doing only 1/140th of the driving are responsible for 1/4th of the fatalities. That’s 35 times the expected number.

But most people seeing the signs have no idea what the context is. They do not know what fraction of miles driven are driven drunk. Statistically speaking there is no difference between “Drunk drivers cause 1 in 4 traffic deaths” and “Sober drivers cause 3 in 4 traffic deaths.” Yet the latter statement seems to make a case for drinking before driving! The lack of context is what empties the statistic of its meaning.

In the same way, there is an oft-quoted statistic that women earn $0.77 for every $1.00 men earn that also suffers from lack of context. (Apparently in 2015 the pay gap went down $0.02. Women now earn $0.79 on average for every $1.00 men earn.) The pay gap is an aggregate of all the income women earn compared to all the income men earn. It is commonly used as evidence of continuing sexism in corporate America. But as evidence it fails because there are so many other factors involved. Missing from the statistic are a lot of facts. For example, men work more hours than women. Women also tend to be over-represented in care-giving and hospitality occupations, which do not pay as well as more male-dominated occupations. This may be due to cultural sexism, but it’s hard to see what actions businesses or governments could take to close whatever portion of the gap is due to this kind of income difference. The truth is most companies in America already have policies prohibiting gender discrimination.

Statistics always present an aggregate view of data. That is what makes statistics valuable. However, aggregating data always also loses some information. The reports on which popularized statistics are based are usually careful to include methodology and context and indicate other possible interpretations of the data. But when the statistic shows up in Facebook meme or a highway sign, all that context is lost. The power of statistics is in simplifying complex data into a few numbers. We understand by simplifying. We should not, however, mistake our understanding for a grasp of the truth.

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