¹ Key, V. O. Jr., Southern Politics (New York: Knopf, 1949), pp. 5–10, 317–344 Google Scholar. A suggestive, but by no means exhaustive list of these studies in the area of voting would include: Black, Earl, “The Militant Segregationist Vote in the Post-Brown South,” Social Science Quarterly, 54 (June, 1973), 66–84 Google Scholar; Pettigrew, Thomas F. and Campbell, Ernest Q., “Faubus and Segregation: An Analysis of Arkansas Voting,” Public Opinion Quarterly, 24 (Fall, 1960), 436–447 CrossRefGoogle Scholar. On Negro voter registration, see: Price, Hugh D., The Negro and Southern Politics (New York: New York University Press, 1957)Google Scholar; Fenton, John H. and Vines, Kenneth N., “Negro Registration in Louisiana,” American Political Science Review, 51 (September, 1957), 704–713 CrossRefGoogle Scholar; Matthews, Donald R. and Prothro, James W., “Social and Economic Factors and Negro Voter Registration in the South” American Political Science Review, 57 (March, 1963), 24–44 CrossRefGoogle Scholar; Cnudde, Charles F., Democracy in the American South (Chicago: Markham, 1971)Google Scholar. And on resistance to racial integration, see: Pettigrew, Thomas F., “Demographic Correlates of Border-State Desegregation,” American Sociological Review, 22 (December, 1957), 683–689 CrossRefGoogle Scholar; Pettigrew, , “Regional Variations in Anti-Negro Prejudice,” Journal of Abnormal Social Psychology, 59 (July, 1959), 28–36 CrossRefGoogle Scholar; Pettigrew, Thomas F. and Cramer, M. Richard, “The Demography of Desegregation,” Journal of Social Issues, 15 (October, 1959), 61–71 CrossRefGoogle Scholar; Matthews, Donald R. and Prothro, James W., “Stateways Versus Folkways: Critical Factors in Southern Reactions to Brown v. Board of Education ,” in Essays on the American Constitution, Dietze, Gottfried, ed. (Englewood Cliffs, N.J.: Prentice-Hall, 1964), 139–156 Google Scholar; Prothro, James W., “Stateways Versus Folkways Revisited: An Error in Prediction,” Journal of Politics, 34 (May, 1972), 352–364 CrossRefGoogle Scholar.

² Schoenberger, Robert A. and Segal, David R., “The Ecology of Dissent: The Southern Wallace Vote in 1968, Midwest Journal of Political Science, 15 (August, 1971), 585 CrossRefGoogle Scholar.

³ Wrinkle, Robert D. and Polincard, Jerry L., “Populism and Dissent: The Wallace Vote in Texas,” Social Science Quarterly, 54 (September, 1973), 319 Google Scholar; Black, Earl and Black, Merle, “The Wallace Vote in Alabama: A Multiple Regression Analysis,” Journal of Politics, 35 (August, 1973), 730–736 CrossRefGoogle Scholar; Bridsall, Stephen S., “Preliminary Analysis of the 1968 Wallace Vote in the Southeast,” Southeastern Geographer, 9 (November, 1969), 61–62 Google Scholar.

⁴ Strong, Donald S., “Further Reflections on Southern Politics,” Journal of Politics, 33 (May, 1971), 249 CrossRefGoogle Scholar; Parker, Glenn R. and Wainscott, Stephen H., “Political Consequences of Racial Prejudice: A Causal Interpretation.” Paper presented at the Annual Meeting of the Southern Political Science Association, New Orleans, November 8, 1974 Google Scholar.

⁵ Wasserman, Ira M. and Segal, David R., “Aggregation Effects in the Ecological Study of Presidential Voting,” American Journal of Political Science, 17 (February, 1973), 177–181 CrossRefGoogle Scholar.

⁶ Ibid., p. 180.

⁷ Wrinkle, and Polincard, , “Populism and Dissent,” p. 311 Google Scholar.

⁸ The relationship between black electoral participation and black concentration appears to be changing over time, and perhaps varies in different areas of the South. The relationship was negative throughout the South in the 1950s (Matthews and Prothro, “Social and Economic Factors and Negro Voter Registration in the South”), positive in Alabama in the 1960s ( Daniel, Johnnie, “Negro Political Behavior and Community Political and Socioeconomic Structural Factors,” Social Forces, 47 (March, 1969), 274–280 CrossRefGoogle Scholar, and curvilinear in the late 1960s in Mississippi ( Kernell, Sam, “Comment: A Re-evaluation of Black Voting in Mississippi,” American Political Science Review, 69 (December, 1973), 1311–1315 Google Scholar.

⁹ Przeworski, Adam, “Contextual Models of Political Behavior,” Political Methodology, 1 (Winter, 1974), 44–50 Google Scholar. See also, Valkonen, Tapani, “Individual and Structural Effects in Ecological Research,” in Dogan, Mattei and Rokkan, Stein, eds., Quantitative Ecological Analysis in the Social Sciences (Cambridge, Mass.: The MIT Press, 1969), pp. 66–68 Google Scholar.

¹⁰ Ibid., pp. 47–49.

¹¹ County-level variables are taken from U.S. Bureau of the Census, County and City Data Book, 1949 (Washington, D.C.: G.P.O., 1952), Table 3Google Scholar; County and City Data Book, 1972 (Washington, D.C.: G.P.O., 1972), Table 2Google Scholar. State-level variables discussed below are taken from U.S. Bureau of the Census, Statistical Abstracts of the United States: 1942, 64th edition (Washington, D.C.: G.P.O., 1943), p. 13 Google Scholar; Statistical Abstracts of the United States, 1973, 94th edition (Washington, D.C.: G.P.O., 1973), p. 29 Google Scholar.

¹² For a more complete description of the CSEP data set, see Fischer, Elizabeth M. and Kovenock, David M., Guide to the Comparative State Elections Project Survey Data (Chapel Hill, N.C.: Institute for Research in Social Science, 1975)Google Scholar.

¹³ Price, H. D., The Negro and Southern Politics: A Chapter of Florida History (Westport, Conn.: Greenwood Press, 1957), pp. 35–54 Google Scholar. For a discussion of the political socialization literature on the effects of early learning for later adult attitudes and behavior, see Searing, Donald S., Wright, Gerald C. Jr. and Rabinowitz, George B., “The Primacy Principle: Attitude Change and Political Socialization,” British Journal of Political Science, 6 (January, 1976), 83–113 CrossRefGoogle Scholar.

¹⁴ Matthews, and Prothro, , “Social and Economic Factors,” p. 28 Google Scholar.

¹⁵ Repeating the analysis that follows using the 1970 percentage black data does not affect the conclusion reached. The only difference is a consistent pattern of lower contextual effects. Also state percentage black, measured at each decennial census from 1900 through 1970, was correlated with white support for Wallace in 1968. The 1940 data yielded the highest of these correlations.

¹⁶ Wasserman, and Segal, , “Aggregation Effects,” p. 179 Google Scholar.

¹⁷ Two regions are used in the present study. Deep South states include: Alabama, Georgia, Louisiana, Mississippi, and South Carolina. The Marginal South (called the Peripheral South in CSEP publications) includes: Arkansas, Florida, Kentucky, Maryland, North Carolina, Oklahoma, Tennessee, Texas, Virginia, West Virginia, and Washington, D.C. For a discussion of the reasons underlying this division, see Black, Merle, Kovenock, David M. and Reynolds, William C., Political Attitudes in the Nation and the States (Chapel Hill, N.C.: Institute for Research in the Social Sciences, 1974), pp. 6–8 Google Scholar.

¹⁸ Blalock, Hubert M. Jr., “Causal Inferences, Closed Populations and Measures of Association,” American Political Science Review, 61 (March, 1967), 130–136 CrossRefGoogle Scholar; Wright, Gerald C. Jr., “Linear Models for Evaluating Conditional Relationships,” American Journal of Political Science, 20 (May, 1976), 349–373 CrossRefGoogle Scholar.

¹⁹ The slopes here, with a dichotomous (1,0) dependent dummy variable measuring voting for and against Wallace, may be interpreted as the average change in percentage voting for Wallace that would be expected from a change of one per cent in the local percentage black. Alternatively, the regression coefficients may be interpreted as the average difference in the probabilities of voting for Wallace between whites living in all-white areas and whites living in all-black areas. The latter interpretation is sometimes not quite as desirable because the estimated coefficients can imply probabilities greater than 1.0 or less than zero.

²⁰ Ward, Joe H. Jr. and Jennings, Earl, Introduction to Linear Models (Englewood Cliffs, N.J.: 1973)Google Scholar. For an exposition of the regression techniques employed here using political science examples see Gerald C. Wright, Jr., “Linear Models for Evaluating Conditional Relationships.”

²¹ The criterion here for comparison of models will be whether a difference in their explained variance is statistically significant. The strategy followed is to first postulate a “full” model with K parameters to be estimated. Restrictions are then put on these parameters (i.e., assuming one or more is equal to zero, or that two or more parameters are equal to each other). These restrictions are incorporated into a “restricted” model with L parameters (where K > L).The test for the difference in models is explained in Ward and Jennings, and Wright, ibid.

²² The use of dichotomous dependent variables in multiple regression analysis is a matter of some controversy. The regression mode of analysis is chosen for its familiarity and for the nice substantive interpretation of the regression coefficients. Each of our models was estimated using multiple discriminant analysis and the results in terms of models retained, the relative importance of variables, and the significance of differences between models are identical throughout. See Ladd, George W., “Linear Probability Functions and Discriminant Functions,” Econometrica, 34 (October, 1966), 873–885 CrossRefGoogle Scholar; Kort, Fred, “Regression Analysis and Discriminant Analysis: An Application of R. A. Fisher's Theorem to Data in Political Science,” American Political Science Review, 67 (June, 1973), 555–559 CrossRefGoogle Scholar. Peter H. Lemieux, “Communications,” and Kort, Fred, “Communications,” American Political Science Review, 68 (March, 1974), 202–205 Google Scholar.

²³ The data presented in Table 2 and throughout the remaining analysis are derived from linear correlation and regression (e.g., W = a + b₁C + e, where W is vote for Wallace and C is proportion black in the county; a and b ₁ are to be estimated). Two nonlinear forms are hypothesized by Blalock, Hubert, Toward a Theory of Minority Group Relations (New York: John Wiley and Sons, 1967), pp. 143–186 Google Scholar. The first is based on a theory of economic competition and posits a positive monotonically decreasing slope between racial discrimination and percentage black (i.e., W = a + b ₁ log C); the second is based on a theory of political threat and predicts a positive monotonically increasing slope (i.e., W = a + b(C/1−C)). Both of these models were tested and found to yield no higher correlations than did the simpler linear model.

²⁴ Key, , Southern Politics, p. 5 Google Scholar; Blalock, , Toward a Theory of Minority Group Relations, pp. 174–175 Google Scholar.

²⁵ Black, Earl, “Southern Governors and Political Change: Campaign Stances on Racial Segregation and Economic Development,” Journal of Politics, 33 (August, 1971), p. 713 CrossRefGoogle Scholar.

²⁶ Wrinkle and Polincard, “Populism and Dissent,” and the literature reviewed therein.

²⁷ Crespi, Irving, “Structural Sources of the George Wallace Constituency,” Social Science Quarterly, 52 (June, 1971), 124–125 Google Scholar; Lipset, Seymour Martin and Rabb, Earl, “The Wallace Whitelash,” Transaction, 7 (December, 1969), 23–25 Google Scholar.

²⁸ The impact of Wallace's home state advantage was also checked in two additional ways. First, we began by regressing Wallace voting on the Alabama dummy variable and then added the variables of Models I through VI, as outlined above. Beginning with “Alabama” in the equation did not influence the results presented above in any notable way. Second, the analysis was repeated with Alabama voters completely excluded; the results were not changed.

Models I–VI were also re-run with Republicans and Independent leaning toward the Republican party excluded to determine if the larger percentage of Republicans in the Marginal South could be influencing the regional differences. The results, in all important respects, again remained unchanged.

²⁹ The interaction between the state and local contextual effects was checked and the addition of a multiplicative interaction term does not add significantly to Model VI.

³⁰ Coleman, James S., “Relational Analysis: The Study of Social Organization with Survey Methods,” Human Organization, 17 (Winter, 1958–1959), 28–36 CrossRefGoogle Scholar.

³¹ Putnam, Robert D., “Political Attitudes and the Local Community,” American Political Science Review, 60 (September, 1966), 640–654 CrossRefGoogle Scholar.

³² For a complete discussion of the procedures for constructing the relative primary group support index see Beardsley, Philip, “The Methodology of Electoral Analysis,” in Explaining the Vote, Kovenock, David M., Prothro, James W. and Associates (Chapel Hill, N.C.: Institute for Research in Social Science, 1973), Part I, pp. 53–55 Google Scholar.

³³ Beardsley, “The Methodology of Electoral Analysis” provides a rather complete discussion of the construction of relative issue proximity measures. A more thorough description and analysis of the particular items used here to construct the measure of relative issue proximity is contained in Wright, Gerald C. Jr., “Community Structure and Voting in the South,” Public Opinion Quarterly, 40 (Summer, 1976), 201–215 CrossRefGoogle Scholar.

³⁴ These three expectations follow from path analysis definitions of intervening models. For example, see Blalock, Hubert M. Jr., “Theory Building and Causal Inferences,” Methodology in Social Research, ed. Blalock, H. M. Jr. and Blalock, A. M. (New York: McGraw-Hill, 1968), pp. 175–176 Google Scholar; Land, Kenneth C., “Principles of Path Analysis,” in Borgatta, Edgar F. (ed.), Sociological Methodology 1969 (San Francisco: Jossey-Bass, 1968), pp. 29–33 Google Scholar.

³⁵ The dotted line in Figure 2 indicates an expected relationship, but it is one that will not be explored here. Fortunately, for our purposes, it is not necessary to disentangle the effects of primary group support and issue proximity on one another; it will be quite sufficient if together these variables are found to be major mechanisms intervening between contextual factors and voting choice.