Friday, June 26, 2015

on measuring and assuming racism and other isms

Lew Rockwell on trying to define and measure "racism" (or other isms)...

If we locate/define it as a heart matter, we'll find it difficult to measure. If we look to behavior-- and move beyond obvious examples-- it becomes quite difficult to measure well (if that matters to those who use the term). 

The usual efforts to measure such things are curious and unsatisfying. Two key examples: 1.) Folks often rely on simple aggregate stats-- comparing all members of group X to all members of group Y. (The most common example here is men vs. women.) No other variables are held constant-- and all of the differences are assumed to be caused by discrimination. The comparisons are quite selective. (For example, nobody uses this method to compare Asian-Americans to the average.) And theory/logic is ignored. (Under what contexts would the market tolerate paying X a modest percentage of what they pay Y? Why aren't labor markets assumed to be reasonably competitive in such cases? Why wouldn't greedy folks hire a lot of X to max profit?) 

2.) Folks measure certain outcomes and not others. Here, people seem to start with a theory/story of where an ism might be-- and then look for anecdotal or statistical differences. If one doesn't imagine that an ism could exist (perhaps mixing in the supposed existence of "good intentions"), we don't look (or ignore outcomes when they're presented). Examples: How we measure police violence by race. How we ignore policy outcomes and policy stances against African-Americans on Social Security, minimum wage, and K-12 education. 


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