Much of the discussion of inequality is hindered by a failure to acknowledge that most dynamic markets (whether in sports, ideas, or commerce) are winner-take-all in structure, that the Pareto distribution is the most common outcome of competition, that constraints are universal as is disparity in capabilities and, from a public policy perspective, the tyranny of Reynold's Law: "Subsidizing the markers of status doesn’t produce the character traits that result in that status; it undermines them."
Xie defines some terms that are usually left very general and those definitions are beneficial to have. For example,
By “inequalities,” I mean differences in three major domains: resources, research outcomes, and monetary or nonmonetary rewards.Which I would summarize more generally as the study of differences in resources, outcomes, and rewards.
Here is his description of winner-takes-all;
science has attributes that resemble a “winner-takes-all” market: high visibility of top winners, a large contestant base, accumulation of advantages, absence of physical or cultural boundaries, and intense competition. Thus, many scientists feel that merely being good at their jobs is not enough. Competition is all about priority, a scientist's claim to be the first to make a big discovery.That is a fairly robust definition and pertinent in many fields far beyond the ivied walls.
Xie has a lot of good observations.
Although these features have made scientific production faster and more voluminous, they have also rendered the evaluation of scientists less substance-specific and more “numbers-based.” Scientists are increasingly likely to be judged by whatever numbers they can generate in terms of publications, citations, research grants, prestigious awards, research team size, and memberships in elite academies than by their actual scientific contributions. This tendency may have been amplified by increasing specialization, such that scientists in one specialty area find it difficult to understand content in another. University administrators, faced with uncertainties and competing demands for scarce resources, have strong incentives to use externally generated and validated indicators.Xie also raises an interesting thought experiment. If academics are so interested income and wealth inequality, how does the world of the academy stack up? Not very well. Here are the Gini numbers for research dollars.
Xie doesn't provide the numbers (they don't appear to exist) but indicates that owing to both high standard deviations in academic salaries as well as they strategic shift among universities towards a much higher percentage of low paid adjunct professors (versus full-time tenured professors) the Gini Index for professors is likely higher than that for the nation as a whole.
One is left with the impression that academics care about income inequality and wealth inequality only to the extent that it doesn't affect them. Research and income inequality in their own backyard may be much higher but as the beneficiaries of those inequalities, they are not interested in addressing that inequality.
It calls to mind that other dictum of Professor Reynolds: "I’ll believe it’s a crisis when the people who tell me it’s a crisis start acting like it’s a crisis."
The commenters over at Gini coefficient for U.S. universities by Tyler Cowen are having fun with the hypocrisy/insularity blindness of academics.