by Race and sex as causes In the potential outcomes approach to causality, sex and race are often not considered causes since they do not fit within this counterfactual manipulation/intervention framework of causal inference. Sex and race cannot be directly manipulated or intervened on, which is said to make it difficult to conceptualize what the ‘potential outcomes’ would be for individuals if they were of a different sex or race. This leaves us in a somewhat unfortunate place: if causation must be defined by intervention, and interventions on race and the whole of SES are vague or impractical, how is one to frame discussions of causation as they relate to this and other vital issues? Rather than stretching and twisting the sense of “intervention” to try
Topics:
Lars Pålsson Syll considers the following as important: Theory of Science & Methodology
This could be interesting, too:
Lars Pålsson Syll writes Randomization — a philosophical device gone astray
Lars Pålsson Syll writes Keynes on the importance of ‘causal spread’
Lars Pålsson Syll writes Use your brain!
Lars Pålsson Syll writes The pitfalls of randomization
Race and sex as causes
In the potential outcomes approach to causality, sex and race are often not considered causes since they do not fit within this counterfactual manipulation/intervention framework of causal inference. Sex and race cannot be directly manipulated or intervened on, which is said to make it difficult to conceptualize what the ‘potential outcomes’ would be for individuals if they were of a different sex or race.
This leaves us in a somewhat unfortunate place: if causation must be defined by intervention, and interventions on race and the whole of SES are vague or impractical, how is one to frame discussions of causation as they relate to this and other vital issues? Rather than stretching and twisting the sense of “intervention” to try to make it conform with scientific and common usage about causation, we suggest that “causation” is not univocal. There is a counterfactual/ interventionist notion of causation—of use when one is designing a public policy to intervene and solve a problem—and a historical, or more exactly, etiological notion—often of use when one is identifying a problem to solve …
Consider sex: Susan did not get the job she applied for because the prejudiced employer took her to be a woman; she presented as a woman because she was raised as a girl; she was raised as a girl because she was biologically female; and so on. The causation is palpable—Susan’s sex caused her not to get the job she applied for. The counterfactual, if Susan were male and had applied for the job, she would have gotten it, suggests a vague, miraculous transformation of Susan into some unspecified male (maybe one with the same qualifications, provided Susan did not attend any all-female schools)— but it makes no literal sense as a practical intervention. Suppose, however, a past intervention to make Susan male, say one of her X chromosomes was to be changed to some Y in utero. To make the counterfactual come out true, the intervention must be expanded to also bring it about that in the course of life as an adult male she applies for the job. Pretty much all of the world history that would interact with her in the course of her male life would have to be intervened upon to bring it about that she, as a male, applied for the job. That would be a remarkably prescient intervention indeed and certainly not a reasonable one. The counterfactual, if Susan had been made a male in utero, Susan would have gotten the job, is almost certainly not true. Etiological causation does not direct us to practical interventions—for that, we need to focus on other causes that are feasibly and ethically manipulable. But it can provide us with a rationale for wanting to change outcomes: Susan did not get the job because of a biological fact about her that is irrelevant to her qualifications, and we think that is unjust.
Limiting causes to only those that are manipulable in the potential outcomes framework excludes important factors like sex and race. But telling us that only well-specified interventions should count as causes sounds utterly contorted to most social scientists. Causal inference frameworks should be flexible enough to account for causes like sex and race, even if they do not fit neatly into the traditional experimental model.