His latest piece, “ Why Are Harvard Graduates in the Mailroom?” is more accurately titled "In Praise of Exploitation." When you strip his argument down, it amounts to: “A lot of people choose to be exploited, and voluntarily take jobs where they are paid less than they deserve because they hope to be big winners.” As in really big winners. Davidson repeatedly compares the payoffs to various activities (working the the mail room at William Morris, being a low level drug dealers, acting, working in a law firm or investment bank) to a lottery.
The lottery analogy, which Davidson uses through the entire piece, is wonderfully, nails-on-the-chalkboard screechingly at odds with his claim: “That’s the spirit of meritocratic capitalism!” Lotteries involve random, blind draws of “lots”. Modern lotteries, the kind that plug holes in government deficits, are such astonishingly low odds affairs that they are described as “a tax on people who are bad at math.” So Davidson appears to be telling us that success in modern capitalism is painfully unlikely and pretty much random.
And there are ample proofs that meritocracy is a fantasy. A devastating 1992 paper by Patrick D. Larkey and Jonathan P. Caulkin, “All Above Average and Other Unintended Consequences of Performance Appraisal Systems,” declared that 100 years of dealing with performance review systems proved they were inherently unable to produce objective results. Among the reasons: the complexities of the boss-subordinate relationship, the fact that virtually all performance appraisals are subjective (even ones of salesmen should allow for who has better or worse territories), and that it is pretty much impossible to devise sensible ways to compare staff caliber across departments. When I was a young person on Wall Street, getting comp right was management’s most important job, and at Goldman, they spent the better part of six weeks of the year on it.
Or consider the example portrayed in Michael Lewis’ book Moneyball. The baseball industry has always measured players’ skill and achievements by a handful of well-known statistics. To make the most of a limited budget, Oakland A’s general manager Billy Beane relied on statistical analysis to sign low-salaried players that appeared to be dramatically undervalued. The result: The team, with one of baseball’s lowest payrolls, has placed first or second in its division for eight seasons running.
Remember: baseball is a business where the recruiting is unusually transparent, the basic rules have remained unchanged for decades, competitive encounters are in full view, and the incentives for success are high. This would seem to be the perfect environment for developing good rules for hiring and promotion, yet the entire industry was largely wrong.‘
And that’s before we get to the role of good old fashioned bias. A 1997 Nature paper by Christine Wenneras and Agnes Wold, “Nepotism and Gender Bias in Peer-Review,” determined that women seeking research grants need to be 2.5 times more productive than men to receive the same competence score. Similarly, Tom Ferguson has combed though the data sets underlying a recent study claiming that the executive ranks of large firmswere meritocratic, and the underrepresentation of “out groups was due to their lack of skills. Ferguson found that the distribution suggested otherwise: ethnic groups are in fact over-concentrated in a few pockets, when they should be scattered evenly if merit selection dominated.