Polling’s fuzzy math
American “political analysis” has become obsessed with demographics.
For example, pundits and pollsters held that the Democratic contests in Ohio and Pennsylvania between Hillary Rodham Clinton and Barack Obama turned on the vote of “white working-class men,” a constituency seemingly in thrall to Clinton. Those primaries supposedly showed Obama’s problem for the general election.
I suggest to you that this kind of analysis, though it comes in the form of numbers, is both fundamentally non-empirical and fundamentally non-explanatory.
Take an election, for example, that finishes 54% to 46% in Clinton’s favor. Now say that white working-class men constitute 12% of the vote, and 10 of every 12 of them (10% of the overall vote) go for Clinton. Obviously, white working-class men were the pivot on which the election turned. If Obama could have broken off half the vote that went to Clinton, he would have won: He would have increased his vote by 5% and reduced hers by 5%, and won 51% to 49%.
But notice that the vote of any like-sized segment is equally explanatory. If most “soccer moms” or most “people ages 35 to 44" or most people “with annual incomes between $50,000 and $70,000" or most “people in the southeast corner of the state” voted for Clinton, we can say that had they voted for Obama, he would have won.
So the assertion, for example, that the result turned on the votes of white working-class men is completely unsupported by the demographics. It no more turned on that group than on any other substantial group that supported Clinton.
Now, one reason for the claim that the white male working-class vote was decisive is that it coincides with the margin of victory in this instance. But notice, if the white working-class men had been split, that would have been decisive for Obama. That is, no matter how the votes of white working-class men are distributed, once you have picked them to study and focused your analysis of the outcome on how they voted, they are decisive.
Their importance is not something the data show. That is an a priori conceptual result of the methods, structure and use of the analysis.
The way that polling and demographics slice up the population is, ultimately, a matter of preference; it does not derive from, but is a presupposition of, the “science.” Searching for segments of the electorate that vote as a bloc, demographers split the population up into groups they decide are important or salient. And their decisions don’t necessarily reflect empirical results -- they are more an index of their own social attitudes, presumptions and prejudices.
It would be nearly as scientific to rig up any segment of the population and regard it as decisive: blue-collar women, black and white, under 35; black men plus Latino women; left-handed divorcees.
The results might be striking; the voting habits of such groups might be as, or more, strongly correlated than race, income and gender grouped in the conventional ways. But even if the results were not striking, even if the groups were evenly split, they would be decisive by the standards of this sort of demographic analysis.
When you bring a set of racial or gender-based categories to the data, the divisions these attitudes represent will always be confirmed as the most important divisions in our society. That just reinforces the problematic divisions that infested the attitudes of the pollsters in the first place. And then, at the end of each election, our divisions of race, gender and class are, in our imaginations, stronger.
The right response to the notion that “scientific polling” shows that the election outcome turns on white men or black women or soccer moms is a shrug of the shoulders and the arch of an eyebrow.