because stars can be placed on or removed from any belly by a machine, and multiple outcomes can be observed for a single Sneetch. Therefore, one could readily answer the counterfactual question, saying with certainty what would have happened to a Plain-Belly Sneetch had he or she been a Star-Belly Sneetch (or vice versa).1 The phenomenon of a black individual passing as white (or vice versa) is an example of how race can be manipulated in this way in our society; thus, it is potentially interpretable causally. However, almost all the information on passing is anecdotal and there are few attempts to measure it systematically. Except under these circumstances, it is nearly impossible in the real world to observe the difference in outcomes across race for a single person; one must instead draw causal inferences.

DRAWING CAUSAL INFERENCES

In the context of measuring racial discrimination, researchers have developed alternative methods to answer the above counterfactual question and assess the incidence and effects of racial discrimination. A formal account of the counterfactual approach to causal inference provides a foundation for evaluating alternative solutions.

Counterfactuals and Potential Outcomes

Counterfactual analysis, combining elements of counterfactual and manipulability theories, is the dominant causal paradigm in recent literature in statistics. The past two decades have witnessed a growing literature formalizing the assumptions and the deductive process needed to draw cause-and-effect inferences from statistical data (Freedman, 2003; Holland, 1986, 2003; Pearl, 2000; Pratt and Schlaifer, 1984, 1988; Rubin, 1974, 1977, 1978; Spirtes et al., 1993; see Box 5-1 for a discussion of graphical approaches). The counterfactual approach to causal inference underlies work in sociology, appearing in both methodological discourse and substantive applications (see Gamoran and Mare, 1989; Lucas and Gamoran, 1991, 2002; Morgan, 2001; Sobel, 1995, 1996; Winship and Morgan,

1  

This example, while nicely illustrating our methodological point about causality, over-looks a key point. A world in which individuals could change their race as readily as Dr. Seuss’s Sneetches can add or remove the stars on their bellies would be a world in which deeply ingrained racial inequalities could not exist. Members of a disadvantaged group would merely exercise the option to join the privileged group. Although there are accounts of individuals “passing” as a different race (such as depicted in John Howard Griffin’s 1996 book Black Like Me), we generally do not live in such a world. Hence, the virtual immutability of race at the individual level is not only a barrier to drawing causal inferences about discrimination but also a necessary condition for the existence of a racial hierarchy in the first place.



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