3 ms·

> Men account for about 69 percent of the company’s work force, but they received a disproportionately higher percentage of the money. If women were underpaid,

> Men account for about 69 percent of the company’s work force, but they received a disproportionately higher percentage of the money. If women were underpaid, things are less equal on average. If men were underpaid, as the study suggests, things are more equal on average. That said, would it be fair to keep underpaying some people in order to keep it more equal on average? I think not.

logfromblammo 8y ago
Using aggregate measures like that rolls up the wrong numbers into a final metric. It tells me that the men who were underpaid had a lesser gap between what they were being paid and what they should be paid, or that the men who were overpaid were overpaid to a greater extent. They needed to compare the number of men who were underpaid as a proportion of all men to the number of women who were underpaid as a proportion of all women. Using bum-pulled numbers, your company has 1000 employees, 667 are men, and 333 women, and they all do pretty much the same job. Your payroll is $100M, and 70% of it goes to the male employees. The mean pay for men is $105k, and the mean pay for women is $90k. Mean pay is $100k--let's say this is fair pay for the work. Overall, the men are overpaid, and the women underpaid. But the mean is a fool's game; the median is more telling. Now say 445 men get $90k, and 222 get $135k. 2/3 of men are underpaid. Now let's say 222 women get $101k, and 111 get $68k. 1/3 of women are underpaid. On a per-person basis, a man working for the company is twice as likely to be underpaid as a woman, but the amount by which they would be underpaid is much less. Going by the aggregate numbers, one could say "men at Company X are overpaid, compared to the women" and then any given underpaid man might not even realize they are being underpaid, thanks to the misleading statistic. When one of the $68k-paid women complains (naturally, as the worst-off of the bunch), and the company analyzes its own payroll at a more detailed level, it realizes that men are more likely to be underpaid than women (and also that increasing its payroll by 8% would make no-one underpaid).

logfromblammo 8y ago

Using aggregate measures like that rolls up the wrong numbers into a final metric. It tells me that the men who were underpaid had a lesser gap between what they were being paid and what they should be paid, or that the men who were overpaid were overpaid to a greater extent. They needed to compare the number of men who were underpaid as a proportion of all men to the number of women who were underpaid as a proportion of all women. Using bum-pulled numbers, your company has 1000 employees, 667 are men, and 333 women, and they all do pretty much the same job. Your payroll is $100M, and 70% of it goes to the male employees. The mean pay for men is $105k, and the mean pay for women is $90k. Mean pay is $100k--let's say this is fair pay for the work. Overall, the men are overpaid, and the women underpaid. But the mean is a fool's game; the median is more telling. Now say 445 men get $90k, and 222 get $135k. 2/3 of men are underpaid. Now let's say 222 women get $101k, and 111 get $68k. 1/3 of women are underpaid. On a per-person basis, a man working for the company is twice as likely to be underpaid as a woman, but the amount by which they would be underpaid is much less. Going by the aggregate numbers, one could say "men at Company X are overpaid, compared to the women" and then any given underpaid man might not even realize they are being underpaid, thanks to the misleading statistic. When one of the $68k-paid women complains (naturally, as the worst-off of the bunch), and the company analyzes its own payroll at a more detailed level, it realizes that men are more likely to be underpaid than women (and also that increasing its payroll by 8% would make no-one underpaid).