If "All politics is local," as Tip O'Neill famously stated, then studying politics requires studying place. Yet place, as defined in many studies of "context effects" throughout the social sciences, is often so vague as to hinder the development of understandings about how place and politics interact. In this paper, we borrow from Parsons and Shils to offer a formal conceptualization of "context," for the purposes of using "context" to learn more about individual level political outcomes. Our conceptualization, and a recognition of the statistical Modifiable Areal Unit Problem, lead us to a new measurement strategy: We propose a map-based measure to capture how ordinary people use information about their environments to make decisions about politics. Respondents draw their contexts on maps-deciding the boundaries and limits of the relevant environment-and describe their perceptions of the demographic make-up of these contexts. The evidence is clear: people's pseudoenvironments do not resemble governmental administrative units in shape or content. By "bringing the person back in" to the measurement of context, we are able to marry psychological theories of information processing with sociological theories of racial threat. And, our measure of context allows us to sidestep the Modifiable Areal Unit Problem, a major stumbling block in research on context that prevents scholars from knowing whether they have substantive findings or simply statistical artifacts.

Nearly all hierarchical linear models presented to political science audiences are estimated using maximum likelihood under a repeated sampling interpretation of the results of hypothesis tests. Maximum likelihood estimators have excellent asymptotic properties but less than ideal small sample properties. Multilevel models common in political science have relatively large samples of units like individuals nested within relatively small samples of units like countries. Often these level-2 samples will be so small as to make inference about level-2 effects uninterpretable in the likelihood framework from which they were estimated. When analysts do not have enough data to make a compelling argument for repeated sampling based probabilistic inference, we show how visualization can be a useful way of allowing scientific progress to continue despite lack of fit between research design and asymptotic properties of maximum likelihood estimators.Somewhere along the line in the teaching of statistics in the social sciences, the importance of good judgment got lost amid the minutiae of null hypothesis testing. It is all right, indeed essential, to argue flexibly and in detail for a particular case when you use statistics. Data analysis should not be pointlessly formal. It should make an interesting claim; it should tell a story that an informed audience will care about, and it should do so by intelligent interpretation of appropriate evidence from empirical measurements or observations.—Abelson, 1995, p. 2With neither prior mathematical theory nor intensive prior investigation of the data, throwing half a dozen or more exogenous variables into a regression, probit, or novel maximum-likelihood estimator is pointless. No one knows how they are interrelated, and the high-dimensional parameter space will generate a shimmering pseudo-fit like a bright coat of paint on a boat's rotting hull.—Achen, 1999, p. 26

In An American Dilemma: The Negro Problem and Modern Democracy, Gunnar Myrdal (1944) argued that white Americans were caught in a dilemma, torn between their commitment to noble democratic principles-what Myrdal called the American Creed-on the one side, and their belief in the superiority of the white race, on the other. Myrdal was certain that in the struggle between democratic principles and race prejudice, the former would prevail. Prejudice, Myrdal famously predicted, was about to disappear. Acknowledging the considerable progress that has taken place in American race relations over the past 60 years, we show that on this particular point Myrdal was wrong. Contrary to his prediction, prejudice has not disappeared; nor has its political significance diminished. Prejudice remains and its importance for politics depends, today as in Myrdal's time, on political circumstance: on the vicissitudes of history and the actions of leaders.